phenomena-based process synthesis-intensification · to specially thank shivangi, ishan, alay,...

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Phenomena-based Process Synthesis-Intensification

Garg, Nipun

Publication date:2019

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Citation (APA):Garg, N. (2019). Phenomena-based Process Synthesis-Intensification. Technical University of Denmark.

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DTU Chemical EngineeringDepartment of Chemical and Biochemical Engineering

Phenomena-based Process Synthesis-Intensification Nipun Garg

Phenomena-based

Process Synthesis-Intensification

PhD Thesis

Nipun Garg

October 2019

KT Consortium

Department of Chemical & Biochemical Engineering

Technical University of Denmark

i

Preface

This dissertation is submitted as partial fulfillment of the requirements for the degree of Doctor

of Philosophy (PhD) in chemical engineering at the Technical University of Denmark (DTU).

The PhD project has been carried out at the KT Consortium research group of the Department

of Chemical and Biochemical Engineering, from October 15, 2016 to October 14, 2019, under the

supervision of Professor John M. Woodley (from Process and Systems Engineering (PROSYS))

and Professor Georgios M. Kontogeorgis (from Center for Energy Resources Engineering (CERE))

at the Department of Chemical and Biochemical Engineering, Technical University of Denmark.

The project has been funded by scholarship from KT Consortium and Chemical and Biochemical

Engineering Department at Technical University of Denmark.

Nipun Garg

Kgs. Lyngby, October 2019

iii

Acknowledgements

This dissertation is a result of exponential learning, experiences and several challenges that I

could not have succeeded in dealing alone. So, I would like to thank my supervisors, colleagues,

friends in Denmark and India and my family to make these years a fulfilling adventure.

First and foremost, I would like to take this opportunity to express my sincere gratitude and also

appreciation to my supervisors Prof. John M. Woodley and Prof. Georgios M. Kontogeorgis for

their invaluable guidance, their insights, their support and encouragement during tough periods

and their teaching during these three eventful years. Their feedback, constructive criticism,

motivation, belief and confidence in me has surely transformed me into a better researcher and

a person with improved technical and interpersonal skills. I will always be grateful to them for

their valuable time over these years.

I would like to genuinely thank my former supervisor, Prof. Rafiqul Gani for not only providing

this opportunity to work on a challenging and innovative project, but also for sharing his own

viewpoint and perspectives about Process Systems Engineering (PSE). His teachings and the

guidance have been very inspiring and instrumental in shaping and broaden my thought process.

I would also like to express my gratitude to Anjan, who has always been available for technical

conversations and moral support. Thank you Anjan for long invigorating discussions. I am also

thankful to Eva, who has always been there to help me with a smiling face. Thank you for being

a motherly figure to me in Denmark. I was also fortunate to be in a positive working environment,

surrounded by colleagues from KT Consortium, Spardha, Yuqiu, Olivia and Xinyan. So, a thanks

to them for exchange of ideas and all fruitful discussions over these three years.

My friends in Denmark have played a huge role during these three years. For that, I would like

to specially thank Shivangi, Ishan, Alay, Harshit, Fazeel, Mayur, Yash, Swati and Chitta for their

belief and trust. Without their support, it won’t have been possible to complete this journey.

Above all, I would like to thank my parents, my brother Shagun, as well as my friends Anish

(specially), Balwinder, Sukhchain, Gurpreet, Bhupinder, Sonam, Seema and Priyanka in India for

their continuous support and understanding over the past three years.

Thank-you once again to all!

Nipun Garg

Kgs. Lyngby, October 2019

v

Abstract

Process synthesis methods generally deals with identification of reactions required to produce

desired products, identification of downstream processes to obtain desired product purity and

decision making in terms of their sequencing. These process synthesis problems are generally

open ended and combinatorial that can generate number of solutions using different approaches.

However, the solution entirely depends on the considered search space and thus are limited to

existing unit-operations hindering the generation of innovative solutions that could significantly

improve the process performance and efficiency by effectively using the maximum driving force

available for a task. Thus, one of the practical ways to generate more efficient, economic and

sustainable process alternatives, counter ongoing challenges and future problems is to develop

approaches and methods that are generic in nature and can be applied over a wide search space

to determine innovative and hybrid/intensified solutions. Process Intensification (PI) is one of

the approach that has enormous potential to achieve this objective. A recent trend in terms of

holistic PI approaches is the use of bottom-up approach that diverts from traditional unit-

operation based approaches within process synthesis and process intensification. These bottom-

up approaches are based on the physicochemical phenomena/functions/building blocks at the

lower level of aggregation increasing the search space and thus generating novel and innovative

solutions at higher level i.e. unit-operation level. The research work done in this project is based

on phenomena-based bottom-up approach.

The main objective of this work is the development and application of systematic phenomena-

based synthesis-intensification framework for direct and indirect synthesis of novel, innovative

and intensified solutions without pre-postulation of possible unit-operations. The fundamental

pillars of this framework are definition and use of the phenomena building blocks (PBBs) that

includes all possible phases (spanning vapor, liquid and solid), identification of phenomena using

thermodynamic insights that are combined using the combination rules and generation of a

phenomena-based superstructure to systematically identify novel, innovative and intensified

flowsheet alternatives. The generated flowsheet options are ranked based on Enthalpy Index (EI)

to identify potential alternatives for detailed analysis (economics, sustainability and life cycle

analysis). One of the novel features of this framework is that it is capable of not only generating

more economic and sustainable novel intensified solutions for an existing process flowsheet

(indirect synthesis or retrofit) but also allows the simultaneous direct synthesis-intensification

by generating phenomena-based superstructure using the phenomena-based approach without

any prior information about the process. Alongside, new phenomena and their classes are

introduced over entire search space, systematic algorithms based on thermodynamic insights are

developed to identify the desirable phenomena and combine them in order to generate novel

vi

and intensified solutions. The developed framework is multiscale as it operates at phenomena,

task and unit-operation scale.

The framework developed in this work along with associated algorithms, knowledge bases and

tools are tested with three case studies: production of Dimethyl Ether (DME) from methanol,

production of benzene by Hydrodealkylation (HDA) of toluene and biological production of

succinic acid. The framework is tested for both direct and indirect synthesis-intensification

application. In each of the case study, several novel, innovative and intensified alternatives are

systematically generated using this approach.

vii

Resumé På Dansk

Metoder til processyntese beskæftiger sig generelt med identificering af de nødvendige

reaktioner til at producere det ønskede produkt, identificering af oprensningsprocesser for at

opnå de ønskede produkt renhed samt beslutningen om hvorledes deres rækkefølge skal være.

Processyntese problemstillingen er som regel åbne og kan kombineres til at generere adskillige

løsninger ved brug af forskellige fremgangsmåder. Disse løsninger er helt afhængige af det

søgefelt der er taget i betragtning og er dermed begrænset til på forhånd eksisterende

enhedsoperationer, hvilket forhindrer genereringen af innovative løsninger der kunne forbedre

processernes ydeevne ved effektivt brug af den maximale drive kraft tilgængelig for den givende

opgave der skal udføres. Derfor, er en af de mest praktiske måder til at generere mere effektive,

billigere og mere bæredygtige procesalternativer der er med til at bekæmpe nuværende og

fremtidige udfordringer at udvikle fremgangsmåder og metoder der er generiske i deres natur og

som kan bruges i et bredt søgefelt til at identificere innovative og hybride løsninger (proces

intensivering). Proces Intensivering (PI) er en fremgangsmåde der har et enormt potentiale til at

opnå dette mål. De seneste tendenser i forbindelse med holistiske PI fremgangsmåder er brugen

af ”bottom-up” metode der adskiller sig fra den traditionelle enhedsoperation, baserede

fremgangsmåder indenfor processyntese og proces intensivering. Disse bottom-up-

fremgangsmåder er baseret på de fysisk-kemiske fænomener/funktioner/ byggeblokke på det

lavere aggregeringsniveau, hvilket øger søgerummet og genererer således nye og innovative

løsninger på højere niveau, dvs. enhedsdriftsniveau. Forskningsarbejdet udført i dette projekt er

baseret på fænomenbaseret bottom-up-tilgang.

Hovedformålet med dette arbejde er at udvikle og anvende en systematik fænomen baseret

syntese-intensivering ramme til at syntetisere direkte og indirekte nye, innovative og intensiveret

procesløsninger uden nogle på forhånd postulater angående mulige enhedsoperationer.

Fundamentet for denne ramme er at definere og anvende fænomen byggeblokke (phenomena

building blocks (PBBs)) der inkludere all faser (gasfase, væskefase og fastfase), at identificere de

nødvendige fænomener ved brug af termodynamisk indsigt der kombineres ved brug af

kombinationsregler samt at generere fænomenbaserede superstruktur til systematisk

identifikation af nye, innovative og intensiveret processkema alternativer. De genereret mulige

processkema er rangeret i forhold til deres Entalpi Indeks (EI) til at identificere potentielle

alternativer til en mere detaljeret analyse (økonomisk, bæredygtighed og livscyklus analyse). En

af nøglefunktionerne for denne ramme er at den er i stand til ikke kun at generere mere

økonomiske og bæredygtige nye intensiveret løsninger for et eksisterende processkema

(indirekte syntese eller retrofit) men også muliggøre samtidigt direkte syntese-intensivering ved

at generer fænomen baserede superstruktur ved brug af det fænomen baserede fremgangsmåde

viii

uden nogle på forhånd kendskab til processen. Yderligere, nye fænomener og deres klassifikation

er introduceret over hele søgefeltet, systematiske algoritmer baseret på termodynamiks indsigt

er udviklet til at identificere de ønskede fænomener og kombinere dem til at generer ny

intensiveret løsninger. Den udviklet ramme er multiskala siden den opererer på fænomen,

opgave og enehedes operation skalaer.

Den udviklede ramme i dette arbejde sammen med de tilhørende algoritmer, viden og værktøjer

er testet på tre casestudier: produktionen af Dimethyl Ether (DME) fra metanol, produktionen

af benzen ved Hydrodealkylering (HDA) af toluen samt biologisk produktion af ravsyre. Rammen

er testet for direkte og indirekte syntese-intensivering applikationer. I hvert tilfælde var der flere

systematiske nye, innovative og intensiverede alternativer ved brug af denne fremgangsmåde.

Tak til Adem for dansk oversættelse af abstraktet.

ix

Contents

Preface ................................................................................................................................................................... i

Acknowledgements ........................................................................................................................................ iii

Abstract ................................................................................................................................................................ v

Resumé På Dansk ........................................................................................................................................... vii

Contents ............................................................................................................................................................... ix

Abbreviations and Nomenclature ........................................................................................................... xiii

PART - I

Chapter 1: Introduction ................................................................................................................................. 3

1.1. Process synthesis .................................................................................................................................. 4

1.2. State of the art: Process intensification ........................................................................................ 5

1.2.1. Classification of process intensification ............................................................................................... 7

1.2.2. Bottom-up approaches ............................................................................................................................... 9

1.3. Chapter summary .............................................................................................................................. 12

Chapter 2: Thesis Scope .............................................................................................................................. 13

2.1. Background and motivation .......................................................................................................... 14

2.2. Objectives of the thesis .................................................................................................................... 15

2.3. Thesis structure ................................................................................................................................. 16

2.4. Dissemination of the PhD project results ................................................................................. 16

2.5. Chapter summary .............................................................................................................................. 19

PART - II

Chapter 3: PBS-Intensification: Definitions and Concepts ............................................................. 23

3.1. Definitions ............................................................................................................................................ 24

3.1.1. General definitions .................................................................................................................................... 24

3.1.2. Phenomena related definitions ............................................................................................................ 24

3.2. Concept behind phenomena-based synthesis ......................................................................... 25

3.2.1. Phenomena building blocks (PBBs) ................................................................................................... 25

3.2.2. Simultaneous phenomenon building block (SPB) ........................................................................ 27

3.2.3. Basic structure of SPBs ............................................................................................................................ 28

x

3.2.4. Phenomena-based synthesis ................................................................................................................. 29

3.3. Chapter summary .............................................................................................................................. 30

Chapter 4: PBS-Intensification: Methodology and Framework .................................................... 31

4.1. Overview of methodology ............................................................................................................... 32

4.2. Systematic framework ..................................................................................................................... 33

4.2.1. Stage I: Synthesis analysis (step 1-2) ................................................................................................. 33

4.2.2. Stage II: Base case analysis (step 3-4) ............................................................................................... 38

4.2.3. Stage III: Generation of feasible flowsheet alternatives (step 5-11) .................................... 41

4.2.4. Stage IV: Ranking, analysis and comparison (step 12-13) ........................................................ 48

4.3. Chapter summary .............................................................................................................................. 50

Chapter 5: PBS-Intensification: Algorithms, Knowledge bases and Supporting tools ......... 51

5.1. Overview ............................................................................................................................................... 52

5.2. Algorithms ............................................................................................................................................ 53

5.2.1. Algorithms: Stage I ..................................................................................................................................... 53

5.2.2. Algorithms: Stage II ................................................................................................................................... 54

5.2.3. Algorithms: Stage III ................................................................................................................................. 58

5.2.4. Algorithm: Stage IV .................................................................................................................................... 72

5.3. Knowledge bases ............................................................................................................................... 73

5.4. Supporting tools ................................................................................................................................. 74

5.5. Chapter summary .............................................................................................................................. 75

PART - III

Chapter 6: Case Studies ............................................................................................................................... 79

6.1. Case study 1: Production of Dimethyl Ether (DME) .............................................................. 80

6.1.1. Framework application ........................................................................................................................... 80

6.1.2. Discussion ..................................................................................................................................................... 99

6.2. Case study 2: Hydrodealkylation (HDA) of Toluene ...........................................................100

6.2.1. Framework application ......................................................................................................................... 100

6.2.2. Discussion ................................................................................................................................................... 119

6.3. Case study 3: Production of Bio-Succinic Acid ......................................................................121

6.3.1. Synthesis and design using superstructure based optimization .......................................... 121

6.3.2. Application of extended phenomena based synthesis method ............................................. 132

6.3.3. Framework application ......................................................................................................................... 135

xi

6.3.4. Discussion ................................................................................................................................................... 153

6.4. Chapter summary ............................................................................................................................154

PART - IV

Chapter 7: Conclusions .............................................................................................................................. 159

7.1. Achievements ....................................................................................................................................160

7.2. Conclusions ........................................................................................................................................161

Chapter 8: Future Perspectives .............................................................................................................. 163

8.1. Open challenges and future work ..............................................................................................164

References ...................................................................................................................................................... 165

Appendix A ..................................................................................................................................................... 179

Appendix B ..................................................................................................................................................... 180

Appendix C ...................................................................................................................................................... 181

Appendix D ..................................................................................................................................................... 192

Appendix E ...................................................................................................................................................... 194

Appendix F ...................................................................................................................................................... 197

Appendix G ..................................................................................................................................................... 218

xiii

Abbreviations and Nomenclature

Abbreviations

A, B, C, D, Component identities

A1, A2, A3, Algorithm

ATP Aquatic Toxicity Potential

C Cooling

CAMD Computer Aided Molecular Design

CRZ Crystallizer

D Dividing

DME Dimethyl Ether

DPVSU Distillation-Pervaporation in a Single Unit

DVPSU Distillation-Vapor Permeation in a Single Unit

EI Enthalpy Index eq. Equivalent

ES Energy Supply

ES(D) Energy Supply (Direct)

ESA Energy Separating Agent

EWC Energy and Waste Cost

GMF Generalized Modular representation Framework

GWP Global Warming Potential

H Heating

HDA Hydrodealkylation

HEX Heat exchanger

HTC Human Toxicity Carcinogenic

HTPE Human Toxicity Potential by Exhalation

HTPI Human Toxicity Potential by Ingestion

ICAS Integrated Computer Aided System

KB Knowledge Base

L Liquid

LCA Life Cycle Analysis

LD Lethal Dose

L-L Liquid-Liquid

LLE Liquid-Liquid Equilibria

LS Liquid-Solid

M Mixing

M$ Million USD

MeOH Methanol

xiv

MINLP Mixed Integer Non-Linear Programming

MLL Membrane Liquid-Liquid

MoT Modelling template

MSA Mass Separating Agent

MVA Material Value Added

MVL Membrane Vapor-Liquid

MVV Membrane Vapor-Vapor

NBP Number of binary pairs

NC Number of Components

NDV Number of Discrete Variables

NEQ Number of Equations

NF Number of Feeds

NP Number of Product

nPBBMAX Maximum number of PBB

NS Number of processing Steps

NS Number of Streams

nSPBMAX Maximum number of SPB

NV Number of Variables

OP Open Path

OPEX Operating expenditures

PBB Phenomena Building Block

PBS Phenomena-based Synthesis

PC Phase Contact

PCOP Photochemical Oxidation Potential

PI Process Intensification

ProCAPRS Process Computer Aided Reaction Path Synthesis

PS Phase Separation

PSE Process Systems Engineering

PSIN Processing Step Interval Network

PT Phase Transition

PV Pervaporation

R Reaction

RM Raw Material

S Solid

SA Separating Agent

SLE Solid-Liquid Equilibria

SPB Simultaneous Phenomena Building block

SS Solid-Solid

TVA Total Value Added

xv

UOM Units of Measurement

V Vapor

VL Vapor-Liquid

VLE Vapor-Liquid Equilibria

VP Vapor permeation

VS Vapor-Solid

VV Vapor-Vapor

Y Year

Y/N Yes/No

Nomenclature

$ U.S. Dollar

Avw vander Waals area

CC Cost of chemicals

CRAW Raw material cost

CU Cost of utilities

d Kinetic diameter

dm Dipole moment

Gf Ideal Gas Gibbs Energy of Formation

h Hour

Hcomb Standard Net Heat of Combustion

Hf Heat of Formation

Hfus Heat of Fusion

Hvap Heat of vaporization

i, j components

k Number of PBB

K Kelvin

kg Kilo gram

Kow Octanol water partition coeff

kt Kilo ton

m2 Square meter

Mv Molar volume

Mw Molecular weight

NM Number of inlet streams

NST Number of separation tasks

PA Property of a component

PB Property of a component

Pc Critical pressure

Ptp Triple point pressure

xvi

Pvap Vapor pressure

R Reaction

rg Radius of gyration

Rij Binary ratio

SIG Ideal Gas Absolute Entropy

SPROD Product sales

Tazeotrope Azeotrope temperature

Tb Normal Boiling point

Tc Critical temperature

Teut Eutectic temperature

Tm Melting Point

TST Thermal stability temperature

TTD Thermal degradation temperature

Ttp Triple point temp

Vc Critical volume

Vvw vander Waals volume

Zc Critical compressibility factor

α Diffusivity

γ Surface tension

γr,s Stoichiometric coefficient

δ Solubility parameter

ΔHrxn Heat of reaction

ΔH Enthalpy change

δi,j Split fraction

Δvp Stoichiometric coefficient of product

Δvr Stoichiometric coefficient of reactant

ε Separation factor

η Reaction conversion

μ Molar flowrate

σ Molecular diameter

ω Acentric factor

1

PART - I

First part of the thesis consists of two chapters. The first chapter

gives brief introduction about process synthesis and the current

need for innovation. Then, the current state of the art for process

intensification (PI) is presented. This includes, the classification

of PI in different categories performed at different scales, level

and within different domains. A summary of different limitations

identified for primary tasks that can be overcome using process

intensification approaches are also mentioned. Further, a novel

approach for PI i.e. bottom-up approach is discussed primarily as

current work is based on it. An overview of different bottom-up

approaches is presented along with their challenges. Bottom-up

approaches generate innovative intensified solutions using non-

traditional approach that departs from unit-operation. In chapter

2, the objectives and the scope of the thesis are defined based on

the background and motivation behind this work. The thesis

structure is also presented which is divided into 4 parts and 8

chapters. A brief overview of the PhD project results that are

disseminated through various journal articles, international peer

reviewed conference publications, oral and poster presentations

is also presented in chapter 2.

Nomenclature

2

1.1. Process synthesis

3

Chapter 1

Introduction

Chapter outline:


1.2. State of the art: Process intensification

1.2.1. Classification of process intensification

1.2.2. Bottom-up approaches

1.3. Chapter summary

These journal articles are partially based on this chapter:

Garg, N., Kontogeorgis, G.M., Gani, R. and Woodley, J.M., 2019, “A process synthesis-

intensification method for generation of novel and intensified solutions”, in preparation.

Garg, N., Woodley, J.M., Gani, R. and Kontogeorgis, G.M., 2019, “Sustainable solutions

by integrating process synthesis-intensification”, Computers and Chemical Engineering,

126, 499-519.

In this chapter, first, an overview of the need for novel and innovative solutions is

explained. Then, the process synthesis and process intensification are introduced

and described. An overview of the state of the art for process intensification is

discussed from the Process Systems Engineering (PSE) point of view. Different

approaches to perform PI are also discussed. A particular emphasis has been given

on bottom-up approaches as research in this thesis is based on phenomena-based

synthesis which is also a bottom-up approach. Bottom-up approaches are ones

that depart from the conventional unit-operation based approach and thus

operate at lower level of aggregation. Here, an overview of several other bottom-

up approaches developed over the years is also presented.

Introduction

4

The journey to attain sustainable production in chemical and related industries is still in its early

stages and there is a continuously rising expectation for improvement and innovation in the

coming years (Välimäki, 2018). These chemical and biochemical processes produce products that

are essential in daily life and become more and more important in meeting the requirements of

today’s modern world. Simultaneously, they are also exerting negative impacts on the ecosystem.

These impacts are generated because of many factors like excessive and inefficient use of natural

resources, waste discharge into the environment, ecological effect of the products, inefficient

methods of production to name a few. These industrial processes span the chemical, petroleum,

pharmaceutical, food, textile, electronic and bio-industry. For all these industries, along with

economic benefits, maintaining sustainability, i.e., conserving the resources, preventing waste

generation and increasing productivity have also become top priority. Thus, there is an increased

interest in generation of innovative processes that are not only economically beneficial but are

sustainable as well.


The aim of process synthesis is to identify an optimal processing route to convert a set of raw

materials into the desired products subject to any predefined performance criteria or design

constraints (Gani and Babi, 2014). The performance criteria can be defined in many different

ways for example, product (s) purity, reduced energy consumption, and better environmental,

life cycle or sustainability factors. An overview of process synthesis problem is given in Figure 1.1.

Figure 1.1: Overview of process synthesis problem

Several process synthesis approaches are developed in past many years that are primarily

categorized as heuristics or knowledge based methods (Siirola et al., 1971; Stephanopoulos &

Westerberg, 1976; Douglas, 1985; Jaksland et al., 1995; Siirola, 1996; Jaksland & Gani, 1996; Seader

& Westerberg, 1997; Sempuga et al., 2010; Fox et al., 2013), mathematical optimization based

methods (Floudas et al., 1986; Floudas, 1987; Yee and Grossmann, 1990; Kokossis, 1990; Kokossis

& Floudas, 1994; Papalexandri & Pistikopoulos, 1996; Zondervan et al., 2011; Quaglia et al., 2012)

and hybrid methods (Lu & Motard, 1985; Steffens et al., 2000; Hostrup et al., 2001; Rigopoulos

and Linke, 2002; Tula et al., 2014).


5

However, process synthesis is generally limited to existing unit operations and thus, novel and

intensified/hybrid solutions are not generated or included (Bednik et al., 2004; Li et al., 2011;

Babi et al., 2015). Thus, an extension of search space in process synthesis is required to generate

innovative solutions meeting the desired objectives. Therefore, traditional concepts of process

synthesis need to be expanded to generate novel and innovative solutions. These concepts can

be expanded in a way that considered problem incorporates additional constraints for desired

performance or targets the maximum driving force behind every task.

One of the ways to achieve this objective is by integrating process synthesis and intensification.

By performing process synthesis-intensification, the current search space of process synthesis

can be increased to generate new, novel and innovative solutions.


Process Intensification (PI) aims to significantly improve the process performance and bring

improvements both in terms of sustainability and economics. It has emerged to be an important

tool providing development opportunities and solutions for the challenges generating more

efficient and sustainable processes. Ozokewlu, 2014 has presented a list of an interdisciplinary

application of PI to different industrial sectors. A brief overview of the applications but not only

limited to is shown in Figure 1.2.

Figure 1.2: An overview of process intensification application to industrial sectors

The term Process intensification first attracted serious attention in the early 1970’s but has one

of the earliest references in a paper published by Wightman et al. (1925). Back then the term

Process Intensification

Chemical manufacturing

✓Integrated process steps

✓Modular processes

Petroleum refining

✓Gas to liquid conversion

✓Wastewater treatment

Oil and gas extraction

✓Hydro-fracturing

✓Gas processing and recovery

Biochemical production

✓Integrated fermentation

✓Choice of host

✓Engineered strains

Power generation

✓Gas separation

✓Carbon capture

Waste and recycling

✓Membrane systems

✓Electronics recycling

Introduction

6

process intensification was mainly described as process improvement (Reay et al., 2008). Since

then, in past many decades, understanding of PI has changed and thus different definitions have

been proposed by different researchers. As per the Rapid Advancement in Process Intensification

Deployment (RAPID) manufacturing Institute, PI is considered as a transition from pure unit

operation thinking to a more integrative approach (https://www.aiche.org/rapid). An extensive

and comprehensive review of different definitions, technologies, and tools to perform PI and

increasing interest over time is given by Tian et al. (2018). Tian et al. (2018) mentions that, “PI is

often considered as a toolbox having certain examples for process improvement rather than a

powerful, systematic and strategic approach for innovation”. Thus, the full potential of PI is yet

to be explored in generating systematic, more sustainable, innovative and efficient solutions.

One of the best-known, commercial applications of PI is the methyl acetate production process

using reactive distillation by the Eastman chemical company (Agreda et al., 1990). Here, five

processing steps are integrated to achieve 80% reduction in energy and a large reduction in

capital cost. Other successful developments of PI are membrane reactor (Gallucci et al., 2008),

static mixers (Kim et al., 2017), membrane distillation (Calabro et al., 1994), heat exchanger

reactor (Anxionnaz et al., 2008), reverse flow reactor (Smith and Mackley, 2006) etc. Also, in

bio-processes, PI principles are applied, for example, in fermentation operations. Opportunities

like application of cell retention and insitu removal of products can significantly improve

fermentation processes. The main challenge here for PI is to have reasonably accurate estimates

to find the optimal balance between transport, mixing and kinetics - improving the performance

of fermentation processes (Noorman et al., 2018). Besides, there are PI technologies that are

developed at a lab scale but have not yet found application at industrial level (for example

technologies using external energy sources like microwave, ultrasound, centrifugal and electric

fields). Some of the challenges that restrict the deployment of developed intensified technologies

include the risk of failure, scale-up unknowns, unreliability of equipment performance, and

uncertain safety, health, and environmental impacts (Quadrennial Technology Review, 2015).

Table 1.1: Summary of limitations addressed in reaction and separation tasks

Reaction Task Separation task

Energy consumption Energy consumption

Low selectivity (reaction) Limited mass transfer

Unfavorable equilibrium

or low yield

Difficult separation (low

driving force)

Limited heat transfer Limiting equilibria/azeotropes

High contact time High capital costs/large

volume/no. of units High capital cost, large

volume, no. of units


7

Lutze, (2011) explained that, the main driver behind PI is to overcome limitations behind driving

the task in the process identified as process hotspots. In a detailed literature survey performed

by Lutze, (2011), the main limitations that have been overcome by using PI in reaction and

separation task are shown in Table 1.1.

PI can be performed in many ways i.e. by integrating unit operations (for example, a sequence of

the reactor and distillation columns), integrating tasks (for example, an integrated reaction and

separation in the membrane reactor or reactive distillation column) or by integration and/or

enhancement of phenomena/physiochemical functions affecting the driving force of a task or set

of tasks (Lutze et al., 2013; Babi et al., 2015; Garg et al., 2019).

Figure 1.3: Different ways to perform PI (R and S denotes reaction and separation)

As shown in Figure 1.3a and 1.3b, there are not many alternatives when PI is performed at unit

operation or task levels. However, as shown in Figure 1.3c, the same task (left-hand side of Fig

1.3c) can lead to new intensified equipment such as reactive distillation, membrane-based

reactor-separator (right-hand side of Fig 1.3c) through different combinations of phenomena

(middle of Fig 1.3c). Note that in Fig 1.3c, only a few combinations of phenomena are highlighted.

1.2.1. Classification of process intensification

Process intensification can be classified into various approaches as shown in Table 1.2. These are

explained as follows:

a) Integration of Unit Operations b) Integration of Tasks

R-S-Task

c) Integration and/or enhancement of phenomena

M(VL)=2phM

M(VL)=2phM=R=PC(VL)=PT(PVL)=PS(VL)

M(V)=C

R-Task S-Task

M=C=2phM=PC(VL)=PT(VL)=PS(VL)

M=2phM=PC(VL)=PT(VL)=PS(VL)

M=2phM=R=PC(VL)=PT(VL)=PS(VL)


M=H=2phM=PC(VL)=PT(VL)=PS(VL)

M=PC(LL)=PS(LL)

M=C=PC(LS)=PT(LS)=PS(LS)

S-Task

M=PC(MLL)=PS(LL)

M=ES(C)

M=PT(LS)=PS(LS)

M=ES(C)=2phM=PC(VL)=PT(VL)=PS(VL)




M=ES(H)=2phM=PC(VL)=PT(VL)=PS(VL)

M=2phM=R=ES(C)

M=PC(MVL)=PS(VL)

Introduction

8

Table 1.2: Overview of process intensification approaches

Process

Intensification

Categories Heuristic based methods, Mathematical programming

based methods, Hybrid methods

Levels Process level, Unit-operation level (section of process)

Scales Phenomena scale, Task scale, Unit-operation scale

Domains Process structure domain, Energy domain, Synergy

domain, Time domain

Categories and levels of PI

Process intensification approaches can be broadly classified into different categories performing

at different levels: heuristic, mathematical programming, and hybrid approaches.

o Heuristic based PI approaches: Heuristic approaches are based on information or rules

which are built over time from experiences, different problem insights, engineering data,

and thumb rules. Several heuristics-based process intensification methods are developed

where research from Bessling et al. (1997) and Kiss et al. (2007) focuses on intensification

of a particular section of a process while work from Siirola, (1996) and Portha et al. (2014)

intensify the entire process.

o Mathematical programming-based PI approaches: The mathematical programming

approaches determine the optimal solution through superstructure based optimization

techniques. Examples of the mathematical programming approaches are Caballero and

Grossmann, (2004), Ramapriya et al. (2014), Chen and Grossmann, (2017) where section

of a process is intensified, while, methods from Papalexandri and Pistikopoulos, (1996),

da Cruz et al. (2017), Li et al. (2017) and Demirel et al. (2017) perform intensification of

the entire process or a part of the process at different scales.

o Hybrid approaches for PI: Hybrid approaches aim at combining the advantages of both

heuristic and mathematical programming approaches. These generally concentrate on

narrowing down the search space to reduce the size of the problem by removing

redundant alternatives. Examples of hybrid approaches are Freund and Sundmacher,

(2008), Peschel et al. (2012) and Seifert et al. (2012) intensifying a section of process

while Lutze et al. (2013), Babi et al. (2015), Tula et al. (2017) and Garg et al. (2019) have

reported multiscale methods to intensify the whole or a part of process.

All these categories have certain advantages and disadvantages. Heuristic based approaches are

simple, fast and generally give suggestions for improvement/optimization of an existing process

or development of a new process similar to the existing ones. However, these approaches lack

generality and also requires an extensive knowledge base for reliable results. Mathematical

programming based approaches are advantageous in a way that the optimization of both process

and conditions are done simultaneously, thus all the interactions are considered while solving


9

the problem. However, the solution relies highly on the superstructure of alternatives

considered. Thus, in order to have the most optimal solution, it has to be present in the original

search space. Hybrid approaches have simple structure (comes from heuristics) and narrows

down the search space by eliminating the redundant solutions using the thermodynamic

insights. However, the screening may remove non-intuitive optimal solutions.

Scales and domains of PI

PI can be achieved at various scales across different domains. According to Babi et al. (2015), PI

can be performed at different scales, i.e., unit operation, task and phenomena scale. At unit

operation scale, individual unit operations that constitute the process are considered for

intensification. Further, at the task scale, the functions performed by a specific unit-operation

are considered. A task can be defined as a purpose that it fulfills in the process such as reaction,

separation, mixing or energy supply. Examples of PI performed at unit operation and task scales

are dividing wall column, membrane reactor and reactive distillation (Inoue et al., 2007; Asprion

and Kaibel, 2010; Halvorsen and Skogestad, 2011; Holtbruegge et al., 2015; Demirel et al., 2017).

At phenomena scale, different phenomena affecting the driving force to perform a task are

identified and further combined to generate innovative and intensified alternatives. Some of the

examples of PI methodologies that operates at the phenomena scale are Papalexandri and

Pistikopoulos, (1996), Arizmendi-Sánchez and Sharratt, (2008), Rong et al. (2008), Lutze et al.

(2013), Babi et al. (2015), Garg et al. (2019). According to Van Gerven and Stankiewicz, (2009),

these improvements or enhancements can be achieved across four different domains that are

process structure, energy, synergy and time. Time domain involves improvement of the kinetics,

reduction of time, i.e., maximization of the speed and effectiveness of the events at different

scales. Space domains consider maximization of homogeneity, for example, creation of identical

conditions for each molecule within the considered system. Energy (or thermodynamics) domain

includes relaxation of transport limitations thus maximizing the driving forces and various

transfer areas. Synergy domain aims to maximize the integration of different tasks, for example,

reaction combined with heat exchanger or alternative energy source like microwave to improve

overall performance.

1.2.2. Bottom-up approaches

The latest trends in the holistic and systematic PI is use of the bottom-up approaches that are

departing from the conventional unit-operation based approach and instead using processing

task, physicochemical phenomena and functions to increase the search space and generate

innovative solutions. These approaches focus on generating intensified solutions starting from a

lower scale of aggregation and gradually moving upwards to the unit-operation scale. Bottom-

up approaches are also advantageous in comparison to traditional process synthesis and design

methods as unit operation-based representation may hinder the exploration and discovery of

out-of-the-box solutions and design alternatives.

Introduction

10

Over the years, several bottom-up approaches have been proposed (Figure 1.4). Papalexandri and

Pistikopoulos, (1996) introduced phenomena scale for the first time and proposed a “phenomena

based generalized modular representation framework (GMF)” that uses fundamental mass/heat

transfer principles and optimizes them based on Gibbs free energy. The framework also involves

the generation of superstructure which is optimized with mixed integer non-linear programming

(MINLP) formulation to find the process alternatives.

Figure 1.4: An indicative timeline tree of bottom-up approaches

Rong et al. (2004, 2008) introduced a 3-stage phenomena-based approach for PI using physical

and chemical insights to overcome the thermodynamic limitations. In the first stage, the process

bottlenecks are identified. In the second stage, phenomena are identified on basis of bottlenecks

and finally, in stage 3 alternatives are generated via replacing actual equipment with better suited

equipment. Arizmendi-Sánchez and Sharratt, (2008) developed a framework for phenomena-

Papalexandri

and

Pistikopoulos

1996

Rong et al.

2004, 2008

2008

Arizmendi-Sánchez

and Sharratt

2008Freund and

Sundmacher

2010, 2011

Peschel et al.

2013

Lutze et al.

2015

Babi et al.

2017, 2018Demirel et al.

and Li et al.

2017

Kuhlmann and

Skiborowski;

Kuhlmann et al.

Tian et al.Garg et al.

2018

2019


11

based PI using the modularization principles. In this work, the physicochemical phenomena are

arranged to represent the behavioural level consisting of accumulation, generation and transport

of mass and energy bounded by structural phenomena. Modularization criteria are then used to

ensure consistency of qualitative (knowledge based) and quantitative (causal graphs) models.

Freund and Sundmacher, (2008) introduced functional modules (in terms of linear combination

of elementary process functions and flux vectors) to represent equipment independent process

flowsheets. This assisted in identifying potential areas where intensification can be applied.

Peschel et al. (2010, 2011) used this novel description of a chemical process to develop a 3-level

approach generating novel reactor network system. This included the selection of an optimal

reaction route amongst different alternatives followed by mass and energy balance for catalyst

packing and then finally, technical constraints were determined for the equipment.

Demirel et al. (2017) and Li et al. (2017) proposed a 2-D grid representation of abstract building

blocks (ABB) similar to phenomena/functions where a structure of different types of blocks

results in an intensified unit-operation. Overall design problem includes vapor-liquid search

space and is formulated as a single MINLP problem. The work has been extended to perform

simultaneous synthesis, integration and intensification. Tian and Pistikopoulos, (2018) proposed

an integrated approach that enables automated generation of safely operable PI systems from

phenomena level using the GMF developed by Papalexandri and Pistikopoulos, (1996). Here, a

multiperiod GMF representation for vapor-liquid systems is developed to ensure that the design

configurations can be operated under a specified range of uncertain parameters.

Lutze et al. (2013) with inspiration from Papalexandri and Pistikopoulos, (1996)’s phenomena-

based research, proposed an innovative and systematic methodology analogous to CAMD

performing process intensification at phenomena scale. The methodology uses phenomena

building block (PBB) to describe the process and sequentially using predefined rules and

algorithms, combine them to generate simultaneous phenomena building blocks (SPBs) which

are translated to unit operations. The phenomena-based methodology initially proposed by

Lutze et al. (2013) was extended by Babi et al. (2015) adding economic, sustainability and Life

cycle considerations to intensify an existing entire process. Babi et al. (2015) proposed a 3-stage

approach wherein stage 1 and 2, a base case flowsheet is identified and designed in detail to

identify process hotspot and set design targets followed by generation of improved, innovative

and intensified alternative using phenomena based intensification (stage 3). The 3 stages can also

be performed independently, depending on available input information. For example, if a process

flowsheet already exists, stage 2 can be performed directly. The phenomena-based methodology

from Babi et al. (2015) has been further enhanced to generate innovative solutions involving

solid-liquid and liquid-liquid systems in addition to vapor-liquid and membrane systems that

could be intensified previously (Garg et al., 2019). Kuhlmann and Skiborowski, (2017), proposed

a methodology generating intensified flowsheet variants for predefined separation tasks based

Introduction

12

on a superstructure of the PBBs that are subsequently translated into specific equipment. The

methodology is further updated for reaction-separation tasks by Kuhlmann et al. (2017). Here,

among these approaches, an existing process flowsheet or a base case is required to perform

process synthesis-intensification at different levels.


An overall concept of process synthesis, related approaches and associated methods has been

presented. Process synthesis approaches being generally limited to existing unit-operations

limits the creativity to find novel and intensified solutions. Thus, an opportunity to expand the

current search space provided by PI was discussed. Process intensification is a valuable tool for

the development of more sophisticated and more efficient processes aimed at the sustainable

production in chemical and related industries. One of the many objectives of Process Systems

Engineering (PSE) domain is to generate innovative solutions which is well in harmony with all

or several of the process intensification approaches. Thus, PSE community is making continuous

efforts within PI to address the key issues like: (i) efficient use of process systems methods to

utilize wide search space and develop systematic methods that can generate out of the box

solutions (ii) ensuring operability performance of the generated intensified solutions at an early

design stage (Tian and Pistikopoulos, 2018).

This chapter also provided an overall concept of process intensification with a detailed overview

of bottom-up approaches, different thoughts, associated methods, and applications to achieve

process intensification. There are several approaches developed under PI, out of which the latest

trend is the bottom-up approaches. Bottom-up approaches provide an opportunity to create out

of the box solutions by operating at the lowest level of aggregation and thus moving upwards

towards unit-operation based flowsheets generating intensified solutions and its configurations.

Summarizing, some of the big challenges for Process Systems Engineering (PSE) based process

synthesis-intensification approaches are as follows:

o Systematic identification: How systematically novel and innovative intensified process

pathways can be identified spanning wide search space.

o Systematic synthesis: How systematically novel, innovative and intensified process

alternatives can be generated from the beginning i.e. without needing any base case or

an existing process hotspot information.

o Systematic validation: How systematically generated novel and innovative intensified

solutions can be validated in terms of safety and operability.


13

Chapter 2

Thesis Scope

Chapter outline:

2.1. Background and motivation

2.2. Objective of the thesis

2.3. Thesis structure

2.4. Dissemination of the PhD project results


This chapter firstly, presents the background and motivation behind this project

and also explains the scope of the thesis. The need for a systematic and integrated

approach for process synthesis and process intensification generating novel and

innovative solutions is also described. The objectives of the thesis are explained

on the basis of the literature review presented in chapter 1. Then, the structure of

the thesis is presented that consists of eight chapters across four parts which are

introduction, developed framework (includes concept, framework, algorithms and

knowledge bases), application examples and conclusion. An overview of the PhD

project results disseminated via various journal articles, international conference

publications, oral, and poster presentations is also presented.

Thesis Scope

14

2.1. Background and motivation

In order to meet ever-growing demands, chemical and related industries are constantly looking

for solutions that are economical, sustainable, efficient, and are easily applicable and scalable.

The major challenges associated and being faced while achieving these objectives are:

a) How systematically, innovative and sustainable solutions can be achieved?

b) How different solutions can be efficiently and quickly screened and assessed?

c) How the complexities of the industrial processes can be managed?

d) How to achieve guaranteed non-trade off solutions for example from an environmental,

technical and economic perspective?

Thus, in recent years, a major focus in process technology has been on hybrid/intensified and

novel equipments that can dramatically improve the performance of chemical and biochemical

processes. Therefore, tools, techniques, and methodologies that potentially could transform the

basics of process synthesis and design; generating novel, innovative and sustainable solutions are

highly desirable. The key attributes of such methods and tools should be that they are systematic,

flexible in applicability and approach as well as covering a wide range of domains and scales from

molecular to process or from phenomena to unit operation scale (Figure 2.1).

Figure 2.1: Key attributes for methods to generate sustainable solutions

Also, from the literature study, we came to know that, bottom-up approaches are beneficial as

they depart from conventional unit-operation based approaches and thus bears the potential to

Key to Methods for Sustainable Solutions

Systematic

Flexible and

versatile

Multi disciplinary and multi

scale

Quick and efficient

Generate innovative

alternatives

Manage complexity

2.2. Objectives of the thesis

15

generate novel solutions that are economic and sustainable. Several methodologies over the years

have been developed under bottom-up approaches that can generate a variety of solutions for

different problems. Most of the mentioned approaches are limited to vapor-liquid systems or

reaction/separation systems or requires an existing process flowsheet to generate or synthesize

intensified solutions and thus spans across existing intensified equipment or its configurations.

There is a need of a framework that can systematically generate novel, innovative and intensified

unit-operation/unit-operation based flowsheets while considering the complete search space of

vapor/liquid/solid systems. Also, the framework is not constrained to the presence of existing

process flowsheet or unit-operations to generate innovative and intensified alternatives i.e. it can

perform direct synthesis-intensification. If required, the framework is flexible and can also

perform retrofit or indirect synthesis-intensification to generate more sustainable and economic

solutions than the existing process. Furthermore, it also considers special energy sources for

example microwave, ultrasound to name a few expanding the current search space.

The research performed in this thesis is based on the hybrid approach for process intensification.

Further, the developed framework is a bottom-up approach operating at phenomena scale and

gradually moving towards unit-operation scale to generate novel and innovative solutions. The

research done by Lutze, (2012) and Babi, (2014) is taken as a starting point for this work, to be

adapted and thus develop a novel and unique framework for a variety of applications.

2.2. Objectives of the thesis

Motivated by the needs and identified gaps, in this PhD project a significant effort has been made

to cover most of the challenges covering systematic identification and synthesis; thus, developing

a systematic framework to generate novel, innovative and intensified solutions.

The main objectives of this PhD thesis are as follows:

➢ Direct and indirect synthesis-intensification: To develop a systematic framework

performing direct and indirect synthesis-intensification for chemical and biochemical

processes generating novel, innovative and intensified flowsheet alternatives.

➢ Systematic generation of the novel and innovative solutions: Development of the

methodology for systematic generation of novel and potentially feasible intensified unit-

operations without any apriori postulation for the same.

➢ Search space spanning vapor/liquid/solid systems: Use of the entire search space

covering phenomena/physicochemical functions across vapor, liquid and solid systems.

➢ Phenomena based superstructure: To generate a phenomena based superstructure

based on physical property and thermodynamic insights constituting the entire search

space of alternatives generated from mathematical combination of compounds.

Thesis Scope

16

➢ Special energy sources: Inclusion of the special energy sources to expand phenomena

database generating innovative solutions.

➢ Ranking of generated alternatives: Development of a method capable of evaluating

and ranking the generated alternatives without using rigorous models.

Further, applicability of the developed framework to be tested with case study examples.

2.3. Thesis structure

This PhD thesis is divided into four parts including eight chapters described as follows:

PART I (Chapter 1-2) Part I is introductory, consisting of chapters 1 and 2. Here, in chapter 1, state of the art for process

intensification with bottom-up approaches is presented. Chapter 2 presents the thesis scope

including the background and motivation for this work. Further, the main objectives of this work

are stated along with various dissemination activities performed over the course of three years.

PART II (Chapter 3-5) Part II is the core of this thesis consisting of chapters 3, 4 and 5. Chapter 3 presents the basics

and builds the conceptual understanding about the phenomena-based synthesis-intensification

method. In chapter 4, the methodology and the framework developed is presented while chapter

5 consists of algorithms, knowledge bases and supporting tools required to apply the framework.

PART III (Chapter 6) Part III consists of chapter 6, where 3 application case studies of the developed framework are

presented. The three case studies solved are production of DME (direct synthesis-intensification

application of the framework), hydrodealkylation of toluene to produce benzene (indirect

synthesis-intensification application of the framework), and the production of bio-succinic acid

(indirect synthesis-intensification). The difference between second and third case study is that

in second case study the base case is identified from literature while in third case study the base

case is synthesized using superstructure based mathematical optimization approach.

PART IV (Chapter 7-8) Part IV presents the conclusion and future work of the thesis. Chapter 7 outline achievements

and conclusions of this work while chapter 8 provides future perspectives and directions for

further expansion or improvements.


This section contains a list of publications, conference presentations and other contributions

related to this PhD project. The results from this PhD work including different collaborations is

disseminated in the form of research articles in scientific journals and articles published in


17

international conference proceedings. Furthermore, conference presentations (both oral and

poster) presented in various international conferences during the course of PhD study are also

listed. The research work has also been disseminated during several annual meetings via oral and

poster presentations.

Journal publications

1. Garg, N., Kontogeorgis, G.M., Gani R. and Woodley, J.M., 2019, “A process synthesis-


2. Chen Y., Garg, N., Kontogeorgis, G.M. and Woodley, J.M., 2019, “Systematic screening of

Ionic liquids for bio-processing”, in preparation.

3. Garg, N., Woodley, J.M., Gani, R. and Kontogeorgis, G.M., 2019, “Sustainable solutions

by integrating process synthesis-intensification”, Computers & Chemical Engineering, 126,

499-519.

4. Tula, A.K., Befort, B., Garg, N., Camarda, K. and Gani, R., 2017, “Sustainable process

design & analysis of hybrid separations”, Computers & Chemical Engineering, 105, 96-104.

Peer reviewed international conference publications

1. Garg, N., Kontogeorgis, G.M., Woodley, J.M. and Gani, R., 2018, “Sustainable and

Innovative Solutions through an Integrated Systematic Framework”, Computer Aided

Chemical Engineering, 44, 1165-1170.

2. Garg, N., Tula, A.K., Eden, M.R., Kontogeorgis, G.M., Woodley, J.M. and Gani, R., 2018,

“Hybrid Schemes for Intensified Chemical and Biochemical Process Alternatives”,

Chemical Engineering Transactions, 69, 517-522.

3. Garg, N., Kontogeorgis, G.M., Woodley, J.M. and Gani, R., 2018, “A Multi-stage and

Multi-level Computer Aided Framework for Sustainable Process Intensification”,

Computer Aided Chemical Engineering, 43, 875-880.

Contribution to international peer reviewed conferences

1. Garg, N., Kontogeorgis, G.M. and Woodley, J.M., 2019, “A Phenomena based method for

Process Intensification”, Type: Poster, presented at: FOCAPD-2019 conference, Colorado

Springs, Colorado, USA.

2. Garg, N., Kontogeorgis, G.M., Woodley, J.M. and Gani, R., 2018, “A Multi-stage and

Multi-level Computer Aided Framework for Sustainable Process Intensification”, Type:

Oral, presented at: ESCAPE-28 conference, Graz, Austria.

3. Garg, N., Tula, A.K., Eden, M.R., Kontogeorgis, G.M., Woodley, J.M. and Gani, R., 2018,

“Hybrid Schemes for Intensified Chemical and Biochemical Process Alternatives”, Type:

Oral, presented at: Distillation and Absorption-2018 conference, Florence, Italy.

Thesis Scope

18

4. Garg, N., Kontogeorgis, G.M., Woodley, J.M. and Gani, R., 2018, “Sustainable and

Innovative Solutions through an Integrated Systematic Framework”, Type: Oral,

presented at: PSE-2018 conference, San Diego, California, USA.

5. Garg, N., Woodley, J.M. and Gani, R., 2017, “A Method for Chemical and Biochemical

Sustainable Process Synthesis, Design and Intensification”, Type: Oral, presented at:

WCCE10 conference, Barcelona, Spain.

6. Garg, N., Woodley, J.M. and Gani, R., 2017, “A Systematic Method for Chemical and

Biochemical Sustainable Process Synthesis, Design and Intensification”, Type: Oral,

presented at: AIChE-2017 conference, Minneapolis, Minnesota, USA.

7. Gani, R., Babi, D.K., Bertran, M., Frauzem, R. and Garg, N., 2017, “The Sustainable

Synthesis-Design-Intensification of Chemical and Biochemical Processes”, Type: Oral

presented by Gani R., presented at: AIChE-2017 conference, Minneapolis, Minnesota, USA.

8. Andersen, T.G., Johansen, M., Andersen M.G. and Garg, N., 2017, “Systematic Process

Design of a Styrene Production Plant Using a Hierarchical 12 Task Procedure: Waste

Stream Utilization for Improved Sustainability”, Type: Poster presented by Andersen,

T.G., Johansen, M. & Andersen M.G., presented at: AIChE-2017 conference, Minneapolis,

Minnesota, USA.

9. Tula A.K., Garg, N., Woodley, J.M., Gani, R. and Befort B., 2016, “Multi-Scale Computer

Aided Synthesis–Design–Intensification Method for Sustainable Hybrid Solutions”, Type:

Oral, presented at: AIChE-2016 conference, San Francisco, California, USA.

Other contributions

1. Garg, N., Kontogeorgis, G.M. and Woodley, J.M., “A generic phenomena-based synthesis

method for process intensification”, Type: Oral, presented at: KT Consortium Annual

Meeting-2019, Helsingør, Denmark.

2. Garg, N., Kontogeorgis, G.M. and Woodley, J.M., “Phenomena based synthesis-

intensification: generalized method and case studies”, Type: Poster, presented at: KT

Consortium Annual Meeting-2019, Helsingør, Denmark.

3. Garg, N., Kontogeorgis, G.M. and Woodley, J.M., “Sustainable and Innovative Chemical

and Biochemical Solutions through an Integrated Systematic Framework”, Type: Oral,

presented at: KT Consortium Annual Meeting-2018, Rungsted Kyst, Denmark.

4. Garg, N., Kontogeorgis, G.M. and Woodley, J.M., “A multi scale and multi-level computer

aided approach for Process Intensification”, Type: Poster, presented at: KT Consortium

Annual Meeting-2018, Rungsted Kyst, Denmark.

5. Garg, N., Woodley, J.M. and Gani, R., “Conversion of Biomass to value added chemicals”,

Type: Poster, presented at: Pro BioRefine-2016, Auburn, Alabama, USA.


19

6. Garg, N., Woodley, J.M. and Gani, R., “Systematic Chemical and Biochemical Sustainable

Process Synthesis, Design and Intensification”, Type: Oral, presented at: KT Consortium

Annual Meeting-2017, Helsingør, Denmark.

7. Garg, N., Woodley, J.M. and Gani, R., “Phenomena based Process Intensification”, Type:

Poster, presented at: KT Consortium Annual Meeting-2016, Technical University of

Denmark, Lyngby, Denmark.


This chapter provided insights about the thesis scope and objectives set to be achieved during

this project. These objectives are set based on the identified needs and gaps in current PSE based

PI approaches and thus tackles many of the unsolved challenges like synthesis of novel flowsheets

without any apriori postulation, wider search space including all the possible phases, alternative

energy sources to name a few. Further, an overview of the thesis structure was presented followed

by a list of dissemination activities during this PhD project.

Thesis Scope

20


21

PART - II

This part of thesis consists of three chapters. These chapters set

the base to understand the developed framework and how it can

be applied to different case studies generating novel, innovative

and intensified solutions. The first chapter in this part (chapter

3) states the general definitions and explains the fundamental

concepts behind the phenomena-based synthesis. The second

chapter in this part (chapter 4) presents step by step, developed

phenomena-based synthesis (PBS)-intensification framework.

The framework consists of 4 stages and 13 steps that are capable

of performing direct and indirect (or retrofit) phenomena-based

synthesis. Each step of the stage has its workflow and data flow,

where the output of one step is input to the following step; that

are also described in detail in this chapter. Also, there are various

algorithms, knowledge bases and tools, which are included in the

framework. All these associated algorithms, knowledge bases

and supporting tools are explained in the third chapter of this

part (chapter 5). This chapter consists of the 12 algorithms and 4

knowledge bases developed across four stages of the framework.

Finally, the simulation software and analysis tools for evaluation

are also presented.

Thesis Scope

22

23

Chapter 3 PBS-Intensification: Definitions and Concepts

In this chapter, all the definitions and concepts related to this work are presented.

This chapter sets the foundation to apply the systematic framework for various

applications. The definitions provide necessary information and understanding

about the different terminologies that are used either directly or developed in this

project. The phenomena-based synthesis approach is similar to Computer Aided

Molecular Design (CAMD) and thus, the comparison is also explained. In order to

systematically generate the novel and innovative process flowsheet alternatives,

the basic understanding behind the phenomena concepts are also reviewed.

Additionally, general application of these definitions and concepts is also stated

where phenomena are combined at the lower scale of aggregation that can

perform tasks at the higher scale and are converted to unit-operation performing

required task or a set of tasks.

Chapter outline:

3.1. Definitions

3.1.1. General definitions

3.1.2. Phenomena related definitions

3.2. Concepts

3.2.1. Phenomena building blocks (PBBs)

3.2.2. Simultaneous phenomena building block (SPB)

3.2.3. Basic structure of SPBs

3.2.4. Phenomena based synthesis







126, 499-519.

PBS-Intensification: Definitions and Concepts

24

3.1. Definitions

3.1.1. General definitions

Binary Ratio Matrix

Binary ratio matrix is defined as the matrix of differences for considered or selected properties,

primarily as their ratio for all possible component binary pairs present in the problem.

Process synthesis

Process synthesis is defined as identification of an optimal processing route (base case) to convert

a set of raw materials into desired products from numerous feasible alternatives, subject to

process constraints and predefined performance criteria (adapted from Gani and Babi, 2014).

Direct and Indirect synthesis

Direct synthesis is defined as generation of process alternatives without any prior information of

an existing flowsheet (or base case) for a target production of desired product, while indirect

synthesis is defined as generation of process alternatives while improving upon an existing

process flowsheet or identification of completely new flowsheets with better performance.

Process intensification

Process intensification (PI) is defined as a significant improvement of a process at unit operation,

functional and/or phenomena level that can be obtained by integration of unit operations,

integration of physiochemical phenomena or functions or targeted enhancement of the

phenomena for a set of target operations (adapted from Lutze et al., 2013).

Phenomena based synthesis-intensification

Phenomena based process synthesis-intensification is defined as the generation (or synthesis) of

intensified process alternatives (includes existing and innovative) from the combination of

phenomena building blocks (PBBs) at the lowest scale (phenomena) that performs a task or a set

of tasks at the higher scale (adapted from Babi et al., 2015).

Sustainable process synthesis-intensification

Sustainable process synthesis-intensification is defined as the generation of more sustainable

process alternatives that correspond to improved values of a set of targeted performance

parameters obtained by integration of unit operations, integration of functions and phenomena’s

or targeted enhancement of the phenomena for a set of target operations (adapted from Lutze et

al., 2013 and Babi et al., 2015).

3.1.2. Phenomena related definitions

Phenomena or a Phenomena Building Block (PBB)

A phenomena or a phenomena building block is defined as the smallest unit at the lowest level

of aggregation that individually or in combination can perform a task or a part of a task in a

3.2. Concept behind phenomena-based synthesis

25

chemical or a biochemical process. These phenomena are the ones that directly affect the driving

force for a task or a set of tasks to occur (adapted from Babi et al., 2015).

Simultaneous Phenomenon Building block (SPB)

A SPB is defined as the combination of one of more PBBs using predefined combination rules

and adjacency matrix that can perform a task or a part of task in a chemical or biochemical

process (adapted from Babi et al., 2015).

Principle PBBs

Principle PBBs are defined as a set of single or multiple non-repetitive PBBs that constitutively

defines a preliminary task or a set of task that they may perform. In other way, principle PBBs

can be called as an unstructured SPB.

Basic structure of SPBs

A basic structure is defined as a single or a combination of multiple SPBs using predefined

combination rules that can perform a targeted or a set of the targeted tasks in a chemical or

biochemical process (adapted from Babi et al., 2015).

Phenomena based synthesis

Phenomena based synthesis is defined as generation of flowsheet alternatives by combining

identified set of PBBs at the lowest level to form feasible SPBs that are further combined using

combinatorial rules to generate basic structures performing a certain task in a process which are

then translated to unit-operation as a part of different process alternatives.


Phenomena based synthesis is a rule-based approach and analogous to Computer Aided

Molecular Design (CAMD) (Harper and Gani, 2000). In phenomena based synthesis, innovative

process alternatives are generated by combining PBBs (analogous to atoms) at the lowest

aggregation level to generate SPBs (analogous to groups). These SPBs are combined to generate

basic structures (analogous to new feasible molecules) that perform a task or set of tasks that are

further translated to unit-operations constituting which flowsheet alternatives are synthesized.

These steps are constrained in a way that they satisfy predefined performance criteria similar to

CAMD where generated molecules satisfy a set of desired properties. An overview of the

comparison of phenomena-based synthesis to CAMD is given in Figure 3.1.

3.2.1. Phenomena building blocks (PBBs)

A chemical or biochemical process can be represented by combinations of different phenomena

occurring within the process in terms of mass, energy and momentum transfer (Lutze et al., 2013;

Babi et al., 2015). A comprehensive list along with new phenomena developed in this work is

shown in Table 3.1. They are divided into five categories (Mixing, Reaction, Mass transfer, Energy


26

transfer and Division) and are further classified based on possible phases and sources. An

example of a PBB is ‘R(L)’ where R denotes reaction while ‘L’ within brackets denotes the phase

in which reaction is taking place, immaterial of phases present within the system.

Figure 3.1: Comparison of phenomena based synthesis approach to CAMD

Table 3.1: List of Phenomena building blocks (PBBs) and their classification

Phenomena Building Block

(PBB) Category Class/Phase

Mixing (M) Mixing

V, L, S, VL, LS, VS, LL

Two-phase Mixing (2phM) LL, VL, LS, VS

Reaction (R) Reaction V, L, S, VL, LS, VS

Energy Supply (ES) Energy transfer C, H, D

Phase Contact (PC)

Mass transfer

VL, LS, LL, VS, SS

Phase Transition (PT) VL, MVL, LS, LL, MLL, VS, MVV

Phase Separation (PS) VL, LS, VS, VV, LL, SS

Dividing (D) Division -

Mixing (M) - Mixing of two or more streams, mixing of compounds occurring in a task (within

one phase or between several phases). For example, two liquid streams entering into the system

or a single stream consisting of multiple compounds.

Select PBBs

e.g. M(L), R(L), ES(C)

Generate SPBs

e.g. M(L)=ES(C), M(L)=R(L)=ES(C)

Combine SPBs to structures to

unit-ops

Screen feasible flowsheet

alternatives

Select atoms

e.g. C, H, O

Generate groups

e.g. CH2, CH3, OH

Combine groups to molecules

e.g. CH3-OH, CH2=CH2

Screen feasible candidates

e.g. CH3-OH

Select building

blocks

Generate

alternatives

Screen

alternatives

Connectivity rules


27

Two-phase mixing (2phM) - If a task is driven by mixing of two-phase system, the mixing of

the two phases is required. For example, two phases can be two different phases like mixing of

liquid and gas or mixing of two different liquid phases like organic and aqueous phase.

Reaction (R) - If a reaction is taking place, i.e., raw materials entering the system are being

converted to products, a “R” PBB is required.

Energy Supply (ES) - If a single phase or multiple phases are present and enthalpy change occurs

due to direct (microwave, ultrasound etc.) or indirect (heating or cooling) energy source, “ES”

PBB is required. For example, cooling of a vapor stream using cooling water, heating of a liquid

stream using steam or use of microwave energy source.

Phase Contact (PC) – If two phases are present in a system and phase contact between them

drives the task, ‘PC’ phenomena is selected. For example, contact of ‘V’ and ‘L’ in distillation.

Phase Transition (PT) - If a transition from one phase to another is happening during a task,

then ‘PT’ phenomena is required. For example, transition of liquid to solid on cooling.

Phase separation (PS) – If separation of two phases is taking place, then a ‘PS’ phenomena is

required. For example, separation of solid and liquid or vapor and liquid.

Dividing (D) - If dividing of a stream is required with same set of properties, ‘D’ phenomena is

selected. For example, dividing a liquid stream into 3 streams.

Note: Here, V, L and S denote vapor, liquid and solid phases respectively, while C, H and D

denote cooling, heating and direct (microwave, ultrasound etc.) that are classes of energy supply

phenomena. MLL, MVL and MVV are special membrane phenomena for different phases. Among

these phenomena, Mixing (M) phenomena is always selected for any task defined. Also, the

entrance of two similar phases within a system is not considered as 2 phase mixing and any

notation of phase is not required for a two-phase mixing PBB within a simultaneous PBB.

3.2.2. Simultaneous phenomenon building block (SPB)

A single or multiple PBBs can be combined in different ways to generate SPB that can perform

an activity/action/task within a process. An SPB is read from left to right for a task or a set of

task. An order of PBBs within a SPB is as follows (not necessarily including all in a single SPB):

M = 2phM = R = ES = PC = PT = PS

Within a SPB, PBBs are separated with ‘=’ symbol denoting the occurrence of these phenomena

at the same time under same operating conditions. For example, consider M(VL), 2phM, PC(VL),

PT(VL), PS(VL) and R(VL) PBBs. Using these, several SPBs can be generated. An example being,

combining M(VL) and R(VL) phenomena, M(VL)=2phM=R(VL) SPB can be generated which is a

reaction SPB. Similarly, M(VL)=2phM=PC(VL)=PT(VL)=PS(VL) denotes a separation SPB, while

the reaction-separation SPB is denoted as M(VL)=2phM=R=PC(VL)=PT(VL)=PS(VL). The SPBs


28

constituting different PBBs may lead to generation of both feasible and infeasible SPBs. Thus, a

set of rules and adjacency matrix to generate feasible list of SPBs is presented in chapter 4.

3.2.3. Basic structure of SPBs

The combination of single or multiple SPBs form basic structure (s) that can perform a task or

set of tasks. These tasks when are further connected, form task-based flowsheets that are

translated to unit-operation. The SPB may or may not fulfill desired objective but a combination

of SPBs forming a basic structure should fulfill the desired objective or activity. For example,

consider a simple example of two SPBs shown in Table 3.2. These SPBs perform individual tasks.

But the combination of these forming a basic structure achieves the objective of a microwave

reactor (Table 3.3). The same task i.e. microwave reaction can also be performed by a single SPB

i.e. M=R=ES(D).

Table 3.2: List of SPBs for microwave reaction

SPB Task Inlet

M=R Reaction 1…..n(V, L…)

M=ES(D) Energy supply (direct) 1…..n(V, L…)

Table 3.3: Basic structure performing a task

Basic structure of SPBs Task Objective

Reaction in the presence

of microwave energy

source

Microwave

reaction

A single SPB can also perform multiple tasks but may not be sufficient to achieve the objective.

Thus SPBs performing multiple tasks can also be combined to form a basic structure that fulfills

the required objective. For example, consider a set of three SPBs as shown in Table 3.4.

Table 3.4: List of SPBs performing multiple tasks

SPB Task Inlet

M=2phM=PC(VL)=PT(VL)=PS(VL) Separation of compounds 1…..n(V, L, VL)

M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL) Cooling + Separation 1…..n(V, L, VL)

M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL) Heating + Separation 1…..n(V, L, VL)

The concept here is when selected SPBs are combined they fulfil multiple tasks reducing the

number of different unit-operations required to fulfil the objective of a unit-operation. The tasks

collectively performed by the basic structure is shown in Table 3.5.

M=R

M=ES(D)


29

Table 3.5: Basic structure performing multiple tasks

Basic structure of SPBs Task Objective

- Cooling of vapor-liquid

Separation of vapor-liquid

- heating of vapor-liquid

Distillation

separation

Thus, when a basic structure performs multiple tasks, the search space of unit-operations is

expanded and can lead to the generation of novel and innovative solutions. A basic structure is

read upwards for an order of task performed by different SPBs not necessarily being the initiator

of the task.

3.2.4. Phenomena-based synthesis

An overview of basics behind phenomena-based synthesis is highlighted in Figure 3.2. The figure

shows example of a SPB within a basic structure and a PBB within an SPB. The basic structures

are translated to unit-operation.

Figure 3.2: An overview of phenomena based synthesis concept

Consider an example of an exothermic liquid phase reaction performing reaction task. It can be

described in terms of phenomena as ‘M(L)’ i.e. mixing of the liquid components in the reaction

‘R(L)’ where ‘L’ represents the reaction phase and ‘ES(C)’ is cooling required to remove the heat

generated because the reaction is exothermic. In the case of a microwave reactor, the energy

supply phenomena ‘ES(C)’ in exothermic reaction is replaced with ‘ES(D)’ that denotes special

energy sources like microwaves. Thus, using these PBBs simultaneously in combination for an

exothermic reaction task becomes a simultaneous phenomenon building block (SPB). Similarly,

R-Task M(L)=R(L)=ES(C)

M(L)=R(L)=ES(D)

M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)


M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)


M=2phM=R=ES(D)=PC(VL)=PT(VL)=PS(VL)


S-Task R-S-Task

R-Task

Basic structures combined to

generate new basic structures

Exothermic

reaction

Microwave

reaction

Distillation

Microwave reactive

distillation

Reactive

distillation

A ‘PBB’ A ‘SPB’ A ‘Basic structure’








30

for a distillation column separating two compounds, simultaneously occurring phenomena ‘M,

2phM, PC(VL), PT(VL), PS(VL)’ along with energy supply phenomena ‘ES(C)’ and ‘ES(H)’ are

selected. Using these phenomena different SPBs are generated that combine to form a basic

structure performing separation task which is translated to distillation.

Now to generate innovative solutions, consider the combination of basic structures for an

exothermic reaction (performing reaction task) and distillation (performing separation task)

using combinatorial algorithms, a new basic structure is generated that performs reaction and

separation task together. This new basic structure is translated to reactive distillation column.

Combining this new basic structure with another similar structure of distillation can be then

translated into a reactive divided wall column. In another case of microwave reaction and

distillation column, a new type of basic structure is generated that performs reaction and

separation task simultaneously with reaction taking place in presence of special energy source of

microwaves. This structure is then translated to microwave reactive distillation. Thus, in a similar

way using a set of algorithms, many novel and innovative solutions can be generated while

performing phenomena based synthesis.


The chapter provides an essential idea about phenomena-based synthesis-intensification and

related terminologies. An extensive list of phenomena building block is defined which can be

combined in many ways at the lower scale to generate innovative solutions at the higher scale.

An example is provided in Figure 3.3 to give an overview of different scales. The phenomena-

based synthesis (PBS) is analogous to Computer-Aided Molecular Design (CAMD), as both these

approaches are multi-level and operate at different levels of aggregation.

Figure 3.3: Different level of aggregation for a reactive distillation column

PC

PT

PT

M, R

2phM

2phM

PC

PS

PS

ES(C)

ES(H)

R-S Task

PBBs

PBBs combined to SPBs

combined to basic structure

Basic structure

performing task

Basic structure

translated to unit-op





31

Chapter 4 PBS-Intensification: Methodology & Framework

Chapter outline:

4.1. Overview of methodology

4.2. Systematic framework

4.2.1. Stage I: Synthesis analysis

4.2.2. Stage II: Base case analysis

4.2.3. Stage III: Generation of feasible flowsheet alternatives

4.2.4. Stage IV: Ranking, analysis and comparison


This journal article is partially based on this chapter:



A systematic methodology to generate novel, innovative and intensified solutions

is presented in this chapter. The methodology is based on phenomena-based

synthesis that operates at the lower level of aggregation (phenomena) to move up

towards the unit-operation scale generating innovative solutions. Further, the

framework developed in this thesis is presented to perform phenomena-based

synthesis-intensification. The framework is capable of performing the synthesis-

intensification both for an existing process (indirect synthesis) and a completely

new problem (direct synthesis). There are 4 stages in the framework, where stage

1 performs problem analysis, stage 2 analyses the base case if exists, stage 3

performs phenomena-based synthesis and stage 4 ranks, validates and compares

generated alternatives. The framework is multiscale as it operates at phenomena,

task and unit-operation scale.

PBS-Intensification: Methodology & Framework

32

4.1. Overview of methodology

The methodology developed for phenomena-based process synthesis-intensification consists of

13 steps across 4 stages, a set of algorithms, knowledge bases and associating tools. Associated

algorithms, knowledge bases and tools are presented in chapter 5. An overview of the framework

developed for the methodology is given in Figure 4.1.

Figure 4.1: An overview of phenomena based synthesis-intensification (Direct and indirect synthesis-intensification)

The methodology developed is not constrained to use an existing process or process flowsheet to

generate intensified solutions and is not restricted to the vapor-liquid systems limiting the

generation of wide range of solutions. The key features of the methodology include:

• Systematic direct and indirect synthesis of the novel, innovative and intensified process

alternatives without any a priori equipment postulation.

• Problem definition

• Problem analysis

• Reaction analysis

• Mixture analysis

I. Synthesis Analysis

• Mathematical combinatorial superstructure

• Phenomena superstructure

• Reduction of alternatives• Logical rules

• Feasibility rules

• Translation of phenomena to flowsheet alternatives

III. Generation of feasible flowsheet

alternatives

• Ranking of all alternatives

• Verification of the selected alternatives

• Detailed analysis and the comparison of top ranked alternatives

IV. Ranking, analysis and comparison

Mw

Tb

rg

Tm

Tc

Pc

ΔHr

Mv

Vvw

TtpPtp

Δ

Avw

PT(LL) 2phM

PS(LS)PT(LS)

PT(MVL) PS(VL)

PS(VL)

ES(D)

PT(VL)R(V)

PC(VL)

M(VL)

ES(C)

A B + C----B/C




M=R(V)=PT(VL)=PS(VL)

N=R(V)=ES(C)

M=PT(MVV)=PS(VV)

M=R=PC(VS)=PS(VS)*

A B + C

--ABC-- A/BC

A/CB

C/AB

C/BA

B/C

B/AC

B/CA

A/C

A/B

06

216

48

103

Total

alternatives

Before

combinationFor selected

phenomena

Mathematical

alternatives

• Generation of the task and phenomena based flowsheet

• Identification of desirable task and phenomena based on process hotspots

II. Base Case analysis

Base case

available?

Yes

Base case

available?

No


33

• Phenomena based synthesis (covering vapor, liquid and solid phases including special

energy sources like microwave, ultrasound etc.) based on physical properties and

thermodynamic insights affecting driving force performing a task or set of tasks.

• Novel phenomena-based superstructure approach to identify potentially feasible novel

solutions.

• Reduction of alternatives using feasibility and logical rules.

• Ranking of all the feasible alternatives to identify promising solutions that are further

analyzed in detail.

In stage I, the main objective is to set up the problem and perform synthesis analysis i.e. defining

problem, collecting reaction information, raw material and product data, mixture analysis and

generation of binary property ratio matrix. In stage II, the analysis of base case i.e. existing

process flowsheet (if available) is performed. Here, an initial list of tasks and phenomena along

with the desired list of phenomena mitigating the process hotspots from the base case is

identified. In case of no base case flowsheet, stage II is skipped. In stage III, firstly a mathematical

combinatorial superstructure of compounds is generated followed by identification of principle

PBBs. Further, using the total list of phenomena and thermodynamic-property algorithms,

phenomena-based superstructure is generated. In this phenomena-based superstructure, the

alternatives are reduced by following a set of the logical and the feasibility rules. The reduced

superstructure consisting of principle PBBs is then translated to basic structures and thus using

combinatorial algorithms and translation of the basic structures to unit operations, potential

flowsheet alternatives are generated. Finally, in stage IV, selected flowsheet alternatives are

ranked based on Enthalpy Index (EI) to identify top alternatives which are further analyzed to

identify potentially innovative and intensified solutions.


The detailed workflow of the developed systematic framework for phenomena-based synthesis-

intensification method is shown in Figure 4.2. The framework consists of 13 steps within 4 stages

operating at the phenomena scale, task scale and unit-operation scale.

4.2.1. Stage I: Synthesis analysis (step 1-2)

Objective – The objective of stage I is to set up, analyze and collect information about the

problem in order to synthesize innovative and intensified solutions in further steps of stage II,

III and IV.

Information required

The information required to accomplish the objective is as follows:

- Problem type (direct or indirect)


34

Figure 4.2: Systematic framework for direct and indirect PBS-intensification

I. Synthesis Analysis

III. Generation of feasible flowsheet alternatives

IV. Ranking, analysis & comparison

Step 5: Generation of mathematical combinatoral

superstructure of compounds

Innovative and intensified

solutions

General workflowMethods and Tools Information flow

II. Base case Analysis

YES

NO

Unit-op to task and phenomena

database

Process hotspots to additional

task and phenomena database

Base case

Flowsheet?

Product info, input and output

compounds, reaction data and

conditions, flowrate

Literature search, ICAS

database

Properties database (ICAS),

Literature, AzeoPro, ProPed

Step 1: Problem definition

Step 2: Problem Analysis

Step 6: Identification of principle PBBs

Step 7: Generation of list of feasible SPBs

Step 9: Reduction of alterantives and generation

of basic strucutres

Information from step-1

Step 10: Combination of basic structures to

generate flowsheet alternatives

Step 3: Generation of task and phenomena based

flowsheet

Step 4: Identification of additional task and

phenomena

Step 11: Translation of the basic structures to

unit-operation

Step 12: Ranking and verification of generated

flowsheet alterantives

Mixture phase, Binary ratio

matrix, azeotropes, eutectic

points, miscibility gaps

Logical and feasibility rules

Combination rules

ICAS-MoT, PRO/IITM

, Aspen

PlusTM

SPBs calculation and

Combination rules

Translation of property to

phenomena database

Translation of basic structure to

unit-op database

Base case flowsheet

Process hotspots

Task and phenomena (PBB)

based flowsheet

Information from step-2

Number of compounds

Total list of PBBs

List of feasible SPBs

Phenomena based

superstrucutre

Generated flowsheet

alternatives

Step 8: Generation of phenomena based

superstrucutre

Step 13: Analysis and comparison of selected

flowsheet alterantivesECON, LCSoft, SustainPro

Selected flowsheet alternatives

Knowledge base

Algorithm

Outflow

Steps

Inflow


35

- Information about product(s) and raw material(s)

- Reaction(s) to convert raw material into desired product(s)

- Operating conditions of the reaction

- Production capacity or flow rate

- Pure component and mixture properties

- Binary ratio matrix

Algorithms needed

- Algorithm A1.1 (section 5.2.1)

Steps/Action

Step 1: Problem definition

The objective of this step is to define the problem and the performance criteria to generate novel,

innovative and intensified solutions.

• S1.1. Problem type

The problem can be of two type i.e. direct or indirect synthesis-intensification. A base

case flowsheet is known for indirect synthesis and then the problem is defined as:

generation of more economical and sustainable solutions than an existing process

flowsheet based on predefined performance criteria. While, for direct synthesis no such

information is available and the problem definition is to generate novel, innovative and

intensified flowsheet alternatives for the production of desired product using selected

raw materials matching the predefined performance criteria.

• S1.2. Information collection

Collect reaction information or perform a literature/online search to identify possible

reaction pathways for producing the desired product using selected raw materials. The

keywords related to the product and raw material can be used for easy search. ProCARPS

(Cignitti, 2014), a reaction path synthesis tool can also be used to identify the potential

reaction routes. Also, retrieve the reaction conditions. Having the reaction, only input

and output components are known for a new synthesis-intensification problem (direct

synthesis). Thus, the task is to determine correct, innovative and intensified sequence of

unit operations that will produce the desired product matching the performance targets.

In addition, for retrofit problems or an indirect synthesis problem where one seeks to

improve upon an existing process flowsheet or find a completely new process flowsheet

with better performance than an existing alternative, step S1.2 includes the collection of

information about reaction from a base case, with raw material inlets, and the desired

product outlets.

The information flow of step 1 is illustrated in Figure 4.3.


36

Figure 4.3: Information flow for step 1

Step 2: Problem analysis

In this step the problem is analyzed in terms of reaction and mixture analysis including pure

component property analysis for the compounds involved in the system.

• S2.1. Reaction analysis

For the identified reaction pathway retrieve conversion data and the reaction phase. The

phase can be solid, liquid and vapor or a combination of above. Also identify the catalyst

(if used in the reaction), that can be heterogeneous or homogenous along with reaction

equilibrium data to identify if the reaction is an equilibrium or forward reaction.

Additionally, identify the reaction kinetics data as per availability. Once the required

information is collected, the reaction is analyzed as follows:

o Identify product(s) and by-product(s) phase involved in the system. Then, calculate

the heat of reaction as follows:

∆Hrxn = ∑ ∆vp ∗ ∆Hf (products) − ∑ ∆vr ∗ ∆Hf (reactants)

(4.1)

Here, ∆Hrxn = Heat of reaction.

vp and vr are the stoichiometric coefficient of the reactant and the product from

the balanced reaction

Hf = Heat of formation of the reactant or product.

o Define the reaction system that can be either one or a combination:

- Forward reaction

- Reversible reaction

o Using heat of reaction data, state the reaction type as follows:

- For ∆Hrxn< 0, reaction is defined as exothermic

- For ∆Hrxn> 0, reaction is defined as endothermic

• S2.2. Mixture analysis

In the mixture analysis task, following two types of analysis are performed for all the

components present in the defined problem. This is to generate information/data for

identification of feasible phenomena that are required to achieve the desired task.

Input information

Raw materials, products,

production rate, reaction,

Pressure, Temperature

Methods/Tools used

Literature search,

ICAS database

Output information

Inlet and outlet

information, Performance

criteria


37

o Pure component analysis: This section of the analysis is performed by collecting

the pure component property data (Table 4.1) from the literature search or ICAS

database (Gani et al. 1997; Gani 2002). The required property data missing for

compounds or new compounds can be calculated using ProPred (property prediction

software) which is available in Integrated Computer Aided System (ICAS) (Gani et al.

1997; Gani 2002). Thus, based on collected property information, the binary ratio

matrix is generated by using algorithm A1.1.

o Mixture property analysis: The mixture property analysis is performed by starting

with identifying the mixture state or phase (after reaction) followed by identifying

the state of pure components at the reference temperature (mixture conditions and

ambient conditions). Then the analysis is performed in terms of the binary pairs of

all the components that are identified in step 1. For each binary pair, a list of analysis

is performed to determine presence of azeotropes, eutectic points, miscibility gaps

i.e. liquid-liquid phase splits or potential MSA’s (mass separation agents) if required.

Azeotropes can be identified by plotting VLE phase diagram using adequate

thermodynamic model. If an azeotrope exists, its pressure sensitivity should also be

checked by varying the pressure for example from 1 to 10 bar and see if the VLE plot

shifts. A hint of an azeotrope between the binary pair can also be identified from

binary ratio of boiling point i.e. if the boiling point ratio is close to unity, then an

azeotrope may exist. Azeopro (Azeotrope analysis toolbox from ICAS), can be used

to identify azeotropes present in the system. Miscibility gap can be hinted from

octanol-water coefficient being much greater than 1 while, eutectic point can be

identified by plotting SLE phase diagrams.

Table 4.1: Selected list of properties for mixture analysis task

Property Symbol UOM

Molecular weight Mw g/mol

Normal Boiling point Tb K

Radius of gyration rg nm

Melting Point Tm K

Solubility parameter δ √(kJ/m3)

vander Waals volume Vvw m3/kmol

Vapor pressure Pvap Pa

Molar volume Mv m3/kmol

Heat of vaporization Hvap J/mol

Dipole moment dm Debye

Heat of Fusion at Tm Hfus kJ/kmol

Diffusivity α m2/s


38

Surface tension γ J/m2

Critical temperature Tc K

Ionic charge - -

Kinetic diameter d pm

Molecular diameter σ pm

Critical pressure Pc bar

Heat of Formation Hf kJ/kmol

vander Waals area Avw m2/kmol

Octanol water partition coefficient Kow -

Standard Net Heat of combustion Hcomb MJ/kmol

Acentric factor ω -

Critical volume Vc m3/kmol

Critical compressibility factor Zc -

Triple point temp Ttp K

Triple point pressure Ptp Pa

Ideal Gas Gibbs Energy of

Formation Gf kJ/kmol

Ideal Gas Absolute Entropy SIG kJ/(kmol · K)

Flash point - K



4.2.2. Stage II: Base case analysis (step 3-4)

Objective – The objective of stage II is to analyze the existing process flowsheet (base case) in

terms of existing task and phenomena, identify additional task and principle phenomena

mitigating the process hotspots and further set design targets that needs to be achieved while

generating innovative and intensified flowsheet alternatives.

Note: This stage is only performed in case of availability of existing process flowsheet and the

objective of the problem is to find retrofit solutions or to identify more sustainable and economic

intensified process alternatives.

Input information

List of components and its

information, reaction

information

Methods/Tools used

Pure component properties,

Literature search,

ICAS database, Azeopro,

ProPred, ProCAMD,

Output information

Binary ratio matrix,

azeotropes, miscibility

gaps, eutectic points


39



- Existing process flowsheet (base case)

- Process hotspots

- List of task and phenomena

- Design targets

Algorithms needed

- Algorithms A2.1, A2.2 and A2.3 (section 5.2.2)

Knowledge base needed

- Knowledge base KB2.1 and KB2.2 (Appendix C.1 and C.2)

Steps/Action

Step 3: Generation of task and phenomena based flowsheet

The objective of step 3 is to generate task and phenomena based flowsheet by identifying the

tasks and initial search space of phenomena that are responsible for existing unit-operations.

• S3.1. Task based flowsheet

The first action of this step is to translate the base case flowsheet into a task-based

flowsheet (for example a reactor unit operation performs a reaction task, or a distillation

column performs a separation task). Apply algorithm A2.1 that uses the knowledge base

KB2.1 to generate task based flowsheet.

• S3.2. Phenomena based flowsheet

The base case flowsheet is further translated to phenomena-based flowsheet to identify

an initial list of principle PBBs. Apply algorithm A2.2 that uses knowledge base KB2.1 to

generate phenomena based flowsheet. Identified list of phenomena in this step is the

initial search space and is further used in stage III.



Input information

Unit-operation based

flowsheet

Methods/Tools used

Unit-operation to task and

phenomena database

Output information

Initial list of task and

phenomena


40

Step 4: Identification of additional task and phenomena

In this step, additional set of tasks and phenomena are identified to overcome the process

hotspots for an existing process flowsheet that expands the current search space. Additionally,

design targets are identified to be achieved while generating more economic, sustainable,

innovative and intensified solutions for an existing process.

• S4.1. Process hotspots and design targets

The process hotspots for the base case flowsheet, are identified by performing economic,

sustainability and LCA analysis based on a matrix developed by Babi et al. (2015). The

matrix is presented in Appendix A. The simulation data or real plant data in terms of

mass and energy balance is required to perform above analysis. If both simulation data

and real plant data is not available for the base case flowsheet, the required data can be

generated by following the systematic approach by Babi, (2015). The economic analysis

of the existing process includes utility cost, operational and capital costs and can be

performed using ECON (Saengwirun, 2011) if a computer-aided tool is not available. The

sustainability indicators like MVA (Material Value Added), EWC (Energy and waste cost)

and TVA (Total value added) are calculated using SustainPro (Carvalho et al., 2013).

Additionally, LCA analysis (LCSoft) (Kalakul et al., 2014) is performed to calculate carbon

footprint and other environmental indicators (like Global Warming Potential (GWP),

Ozone Depleting Potential (ODP), Human Toxicity Potential by Ingestion (HTPI),

Photochemical Oxidation Potential (PCOP) to name a few). Once this information is

available, the matrix developed by Babi et al. (2015) (Appendix A) is used to translate the

indicator values to the process hotspots.

The process hotspots are further used to set design targets additional to the objective set

for the problem (for example lesser number of equipment, waste minimization, reduction

in loss of raw material). These design targets are required to be achieved while generating

non-trade off solutions for the base case. An indicative list to identify the design targets

using process hotspots is presented in Appendix B (Babi et al., 2015). These design targets

are compared for the base case with the selected set of alternatives in stage IV.

• S4.2. Additional task and phenomena

A list of additional tasks and desirable phenomena are identified using algorithm A2.3

and knowledge base KB2.2 based on identified process hotspots for existing process.

These phenomena are desirable as they may assist in overcoming identified bottlenecks.

They are also beneficial as it expands the existing limited search space, therefore

providing an option to innovate and improve on base case flowsheet or generate

completely novel and innovative flowsheet alternatives.



41


4.2.3. Stage III: Generation of feasible flowsheet alternatives (step 5-11)

Objective – The objective of stage III is to generate novel, innovative and intensified feasible

flowsheet alternatives by performing phenomena based synthesis. This stage operates at different

levels i.e. phenomena, task and unit-operation starting from phenomena level where different

phenomena are identified to perform tasks that are further translated to unit-operations.



- List of compounds and binary pairs

- Binary ratio matrix

- Mathematical combinatorial superstructure of compounds

- Principle PBBs for all binary pairs

- Phenomena based superstructure

- Logical and feasibility rules

- Combination rules

Algorithms needed

- Algorithms A3.1, A3.2, A3.3, A3.4, A3.5, A3.6 and A3.7 (section 5.2.3)

Knowledge base needed

- Knowledge base KB3.1 and KB3.2 (Appendix C.3 and C.4)

Steps/Action

Step 5: Generation of mathematical combinatorial superstructure of compounds

In this step, the mathematical combinatorial superstructure of compounds is generated that

consists of all the alternatives mathematically possible for all the compounds present in the

problem. Here, any phase or conditions of the compound is ignored to cover the whole search

space with the possibility to separate all the compounds. This superstructure is generated using

Input information

Process hotspots

Methods/Tools used

Process hotspots to

desirable task and

phenomena database

Output information

Design targets and

additional task and

phenomena


42

algorithm A3.1. The only information required for this step is the number of components present

in the system.

Step 6: Identification of principle PPB’s

The objective of this step is to identify a set of principle PBBs for all the identified binary pairs

and tasks. The list of principle PBBs are identified using knowledge base KB3.1 and algorithm

A3.2. The knowledge base is developed on the basis of physical insights based method (Jaksland

et al., 1995) and thermodynamic insights that transform the pure and mixture property analysis

into a set of phenomena that may assist in achieving the required task. These identified

phenomena are the ones that drive the task. The physical insights method is based on the fact

that, a binary pair of component can be separated based on binary ratios above threshold values

of one or more pure component properties. These set of properties are explored in terms of

phenomena to generate the knowledge base and thus identify the feasible set of phenomena.

Also, using thermodynamics insights i.e. by looking at energy requirement in a reaction task or

SLE, VLE and LLE plots for a binary pair, a set of phenomena database is established that can

perform the task.

The principle PBBs identified in this step are combined with the PBBs identified from stage II

constituting the complete list of phenomena for each considered case. The information flow of

step 6 is illustrated in Figure 4.7.


Step 7: Generation of list of feasible SPBs

In this step, a list of feasible SPBs is generated based on total number of PBBs that are identified

from step 6 in stage III in addition to the one’s identified in stage II, if a base case is available. ‘D’

phenomena is always selected as an additional PBB and added to the identified list.

• S7.1. Operating window for identified PBBs

The first action in step 7 is to identify the operating window for each of the identified

PBBs. The operating window is the thermodynamical limitation for all the identified

phenomena as their operational constraint. A table to identify the operating window for

different PBBs is given in Table 4.2.

Input information

List of components, binary

ratio matrix, mixture

property analysis

Methods/Tools used

Database translating pure

and mixture property

analysis to phenomena

Output information

List of principle PBBs for

all the binary pairs


43

Table 4.2: Operating window guide for identified PBBs (adapted from Babi et al., 2015)

Task PBB Operating

variables

Properties to

be checked Example

Reaction R T, P Tb, Tazeotrope,

Tm, Teut

Single phase (L),

P-Reaction pressure (reported in literature)

T-Lowest boiling compound or minimum

boiling azeotrope

T-Highest boiling compound or maximum

boiling azeotrope

Multiple phase (V-L)

P-Reaction pressure (reported in literature)


boiling azeotrope


boiling azeotrope

Mixing M T, P Tb, Tazeotrope,

Tm, Teut

Liquid Mixing: T- Lowest melting compound

Liquid Mixing: T- Highest boiling compound

Vapor Mixing: T-Lowest boiling compound

or minimum boiling azeotrope

Two-phase mixing 2phM T, P Tb, Tazeotrope,

Tm, Teut


boiling azeotrope (for V-L systems)


boiling azeotrope(for V-L systems)

T-Lowest melting compound or eutectic

point (for L-S systems)

T-Highest melting compound or eutectic


Energy Supply ES T TST, TTD -

Phase Contact PC - - Phases need to be present

Phase Transition PT

T, P

Tb, Tazeotrope,

Tm, Teut


boiling azeotrope (for V-L systems)


boiling azeotrope(for V-L systems)

T-Lowest melting compound or eutectic


T-Highest melting compound or eutectic


Affinity - Component affinity (MVL, MVV, MLL)

Phase Separation PS - - Phases need to be present

Dividing D - - -


• S7.2. Feasible SPBs

The maximum number of possible SPBs (feasible and infeasible) from which a list of

feasible SPBs is generated as following:

o Maximum number of SPBs (feasible and infeasible): The maximum number of

SPBs that can be generated from the identified search space of PBBs is calculated

using the following equation (adapted from Lutze et al., 2013).

nSPBMax = ∑ [(nPBB − 1)!

(nPBB − k − 1)! k!]

nPBBMax

k=1

+ 1 (4.2)

nSPBMax is total number of possible SPBs,

nPBB is the total number of identified PBBs,

nPBBMax is the maximum number of PBBs within a SPB.

In equation 4.2, nPBBMax i.e. the maximum number of PBBs possible within a single

SPB can be 7 which is developed from the basic form of all the phenomena in Table

3.1 in chapter 3. Dividing phenomena is not included in nPBBMax, as it is considered

as a single SPB.

o Generation and screening of feasible SPBs: The feasible list of SPBs is generated

by following a set of rules. These rules are as follows:

- Maximum possible PBBs within a SPB and their order should be as follows:

M = 2phM = R = ES = PC = PT = PS

- A feasible SPB consisting of mass transfer PBBs should have same phase and

associating mixing phenomena having same or similar phase to mass transfer

PBBs.

- The rule regarding the maximum number of different mass transfer PBBs within

a SPB if present is as follows:

∑ PBBPC = ∑ PBBPT = ∑ PBBPS = 1

- The rule regarding the energy supply PBBs within a SPB if present is as follows:

∑ PBBES(C) + ∑ PBBES(H) + ∑ PBBES(D) = 1

- A PBB cannot be repeated within a SPB.

An indicative list of the building blocks to generate SPBs is shown in Table 4.3.

Further, generate the list of feasible SPBs using the adjacency matrix that consists of

complete list of phenomena shown in Table 4.4.


45

Table 4.3: Building blocks to generate SPBs (adapted from Babi et al., 2015)

No. SPB Building

block Inlet Task

1 M=ES(C) 1…n(V, L, S,…..) Performs cooling

2 M=ES(H) 1…n(V, L, S,…..) Performs heating

3 M=ES(D) 1…n(V, L, S,…..) Special energy supply

4 M=R 1…n(V, L, S,…..) Performs a reaction without any energy supply

5 M=2phM 1…n(V, L, S,…..) Performs mixing of two phases

6 =PC=PS 1…n(V, L, S,…..) Performs separation of two phases

7 =PC=PT 1…n(V, L, S,…..) Performs contact and phase creation

8 =PT=PS 1…n(V, L, S,…..) Performs separation of two phases

9 =PC=PT=PS 1…n(V, L, S,…..) Performs separation of two phases

10 D 1…n(V, L, S,…..) Performs division of stream



Step 8: Generation of phenomena based superstructure

The phenomena based superstructure is generated by combining mathematical combinatorial

superstructure of compounds generated in step 5 and the list of principle PBBs identified in step

6. The algorithm to generate the phenomena based superstructure is given in section A3.3.

Step 9: Reduction of alternatives and generation of basic structures

This step of the framework consists of two parts i.e. reduction of the phenomena based

superstructure and then translation of principle PBBs to basic structures from the set of feasible

SPBs generated in step 7. These are as follows:

• S9.1. Reduction of alternatives

The phenomena based superstructure generated in step 8 consists of all feasible and

infeasible alternatives. This superstructure is thus reduced to remove alternatives that

Input information

List of identified

phenomena building blocks

(PBBs)

Methods/Tools used

Combination rules for

PBBs to SPBs

Output information

Operating window for all

PBB s, list of feasible

SPBs


46

are infeasible and illogical using logical and feasibility rules. Follow algorithm A3.4 to

perform this action.

o Feasibility rules: The feasibility rules are based on task performed and the principle

PBBs identified in previous steps. The task based rules are developed using heuristics

(Douglas, 1985) i.e. separation considerations based on phases present in the system.

This action primarily assists in reduction of the superstructure size by removing sub

superstructures. Further, using physical property insights, infeasible set of principle

PBBs for every binary pair present in the system are removed.

o Logical rules: The logical rules are based on inlet and outlet conditions of PBBs

involved in the selected binary pair that may or may not be an inlet to the adjacent

task. The feed conditions are checked both at ambient and original conditions.

• S9.2. Generation of basic structures

The next action in step 9 is to transform the principle PBBs into basic structures. The

SPBs generated in step 7 are used to identify feasible set of basic structures representing

principle PBBs. These generated basic structures are one’s that can potentially complete

required task. Use algorithm A3.5 to complete this action of step 9. The superstructure

consisting of basic structures is level 1 phenomena-based superstructure.



Step 10: Combination of basic structures to generate flowsheet alternatives

The objective of step 10 is to generate level 2 and level 3 phenomena based superstructures. This

is done by considering the combination of basic structures across adjacent tasks to generate new

basic structures performing integrated tasks i.e. multiple tasks. The algorithm required to

generate these set of superstructures is presented in A3.6. The level 2 superstructure is generated

by combining basic structures performing adjacent tasks in level 1 superstructure. Further, level

3 superstructure is generated by combining structures generated at level 2 to generate innovative

solutions. At both the levels, the combinations are performed across reaction-separation and

separation-separation tasks.

Input information

Phenomena based

superstructure

Methods/Tools used

Reduction rules

(feasibility and logical),

List of feasible SPBs

Output information

Level 1 phenomena based

superstrucutre

4.2

. S

yste

mat

ic f

ram

ewo

rk

Ta

ble

4.4

: A

dja

cen

cy m

atr

ix f

or

com

ple

te l

ist

of

PB

Bs

No.

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

PBB

M

R

2phM

PC(VL)

PC(LS)

PC(LL)

PC(VS)

PC(SS)

PT(VL)

PT(LL)

PT(LS)

PT(VS)

PT(PVL)

PT(VV)

PT(M

LL)

PS(VL)

PS(VV)

PS(LL)

PS(LS)

PS(VS)

PS(SS)

ES(C)

ES(H)

ES(D)

D

M

-+

+ +

+ +

+ +

+ +

+ +

+ +

+ +

+ +

+ +

+ +

+ +

-

R

-+

+ +

+ +

+ +

+ +

+ +

+ +

+ +

+ +

+ +

+ +

+ -

2phM

-

+ +

+ +

- +

+ +

+ -

- -

+ +

+ +

+ -

+ +

+ -

PC(VL)

-

- -

- -

+ -

- -

+ +

+ +

- -

- -

-+

+ +

-

PC(LS)

-

- -

- -

- -

- -

- -

- -

- -

- -

+ +

+ -

PC(LL)

-

- -

- +

--

- -

+ -

- +

- -

- +

+ +

-

PC(VS)

-

- -

- -

+ -

- -

- -

- -

+ -

+ +

+ -

PC(SS)

-

- -

- -

- -

- -

- -

- -

+ +

+ +

-

PT(VL)

-

- -

- -

- -

+ -

- -

- -

+ +

+ -

PT(LL)

-

- -

- -

- -

- +

--

-+

+ +

-

PT(LS)

-

- -

- -

- -

- +

--

+ +

+ -

PT(VS)

-

- -

- -

- -

- +

-+

+ +

-

PT(M

VL)

-

- -

+ -

- -

- -

- -

- -

PT(M

VV)

- -

- +

--

- -

- -

- -

PT(M

LL)

- -

- +

--

- -

- -

-

PS(VL)

-

- -

- -

- +

+ +

-

PS(VV)

- -

- -

-+

-+

-

PS(LL)

- -

- -

+ +

+ -

PS(LS)

- -

- +

+ +

-

PS(VS)

-

- +

+ +

-

PS(SS)

-+

+ +

-

ES(C)

-+

+ -

ES(H)

-+

-

ES(D)

--

D

-




Step 11: Translation of the basic structures to unit-operation

The objective of step 11 is to generate unit-operation based flowsheet alternatives. These are

generated by translating the basic structure in the phenomena based superstructures at level 1, 2

and 3. These flowsheet alternatives are one’s that perform the required tasks to obtain desired

products. The basic structures are translated and thus flowsheet alternatives at unit-operation

scale are generated using algorithm A3.7 and KB3.2 given in chapter 5.

4.2.4. Stage IV: Ranking, analysis and comparison (step 12-13)

Objective – The objective of stage IV is to rank the alternatives generated in stage III, analyze

and then compare the top ranked or selected alternatives to find the potential solutions. Also, in

case of an existing base case, the generated alternatives are compared in order to verify if set

design targets are achieved.



- Generated flowsheet alternatives

- Enthalpy Index (EI) for all the alternatives

- Performance indicators value

Algorithms needed

- Algorithm A4.1 (section 5.2.4)

Steps/Action

Step 12: Ranking and verification of generated flowsheet alternatives

In this step, the feasible flowsheet alternatives generated in stage III are in order to identify the

top alternatives and are then verified using model analysis or by performing simulations to

retrieve mass and energy balance data.

Input information

Level 1 phenomena based

superstrucutre

Methods/Tools used

Combinatorial rules for

basic structures

Output information

Level 2 and 3 phenomena

based superstrucutre


49

• S12.1. Ranking of unit-operation based flowsheet alternatives

The flowsheet alternatives are ranked using Enthalpy Index (EI). EI is the modular ratio

of lowest enthalpy for a flowsheet alternative to the enthalpy of considered alternative.

Ranking is done in order to quickly identify and screen top ranked alternatives as it is not

logical to perform analysis for all the flowsheet options. These alternatives may include

completely novel and innovative alternatives; thus, specific shortcut models are not

possible to generate apriori. Algorithm A4.1 is developed to generate the ranking.

• S12.2. Verification of selected flowsheet alternatives

The top ranked or selected alternatives are then verified by performing modelling or

simulation. This is performed in order to understand novel intensified unit-operations

that may or may not be involved in the selected flowsheet alternatives. Some of the

models for intensified unit-operations like reactive distillation, reactive flash can be

retrieved from ICAS-MoT for further analysis (Gani et al., 1997; Fedorova et al., 2014). In

case of presence of membrane or adsorptions systems that uses any separating agent,

verification is performed in terms of availability of real data in literature that can be used

to perform detailed analysis. The alternatives for which the real data is not available are

not chosen for further analysis and thus, options further in the ranking are selected.

Finally, for verified alternatives, the mass and energy balance data is retrieved.



Step 13: Analysis and comparison of selected flowsheet alternatives

The objective of this final step is to analyze and compare the selected alternatives in terms of

economics, sustainability and life cycle assessment. Additionally, it is performed for an indirect

synthesis problem to calculate the performance indicator values that are used to compare the

base case with the selected flowsheet alternatives in terms of pre-defined performance criteria.

• S13.1. Analysis of selected alternatives

The mass and energy balance retrieved from step 12 is used to perform economics

analysis, sustainability analysis and life cycle assessment. The analysis can be performed

using the tools used in step S4.1 (ECON for economic analysis, SustainPro for the

Input information

Unit-operation based

flowsheet alternatives

Methods/Tools used

Enthalpy Index (EI),

Model based analysis or

simulation

Output information

Top ranked alternatives,

Mass and energy balance

data


50

sustainability analysis while LCSoft for LCA analysis). The performance indicator values

are calculated for all the selected alternatives based on above analysis.

• S13.2. Comparison of selected alternatives

The comparison is made for the alternatives independent of the problem type i.e. direct

or indirect synthesis-intensification. In case of a direct synthesis-intensification problem,

the comparison is made among the selected alternatives while in case of an indirect

synthesis-intensification problem, for an innovative or novel intensified alternative to be

a non-trade off solution i.e. more sustainable and economic, it must show improvements

(or no change) with respect to all the performance criteria parameters. Also, perform a

check for both the problem types, if the design targets are met.

Thus, the alternatives that match the performance criteria and design targets are potential novel,

innovative and intensified solutions for the considered problem.




The developed framework for phenomena based synthesis-intensification has been presented

step by step to generate novel, innovative and intensified process flowsheet alternatives. The

chapter also presented detailed workflow, information flow and methods needed to perform

every step. The key elements of the developed framework are phenomena-based representation

for a superstructure consisting of all the alternatives and systematic algorithms to carry out

different steps (presented in detail in chapter 5). Further, it has been shown that the framework

is not only capable of performing indirect synthesis to generate better alternatives in terms of

economy, sustainability and LCA but can also perform direct synthesis-intensification.

Input information

Mass and energy balance

data for selected

alterantives

Methods/Tools used

ECON, LCSoft, SustainPro

Output information

Performance indicator

values, Potential solutions


51

Chapter 5 PBS-Intensification: Algorithms, Knowledge bases and Supporting tools

Chapter outline:

5.1. Overview

5.2. Algorithms

5.2.1. Algorithms: Stage I

5.2.2. Algorithms: Stage II

5.2.3. Algorithms: Stage III

5.2.4. Algorithms: Stage IV

5.3. Knowledge bases

5.4. Supporting tools


This journal article is partially based on this chapter:



This chapter presents the detailed algorithms, knowledge bases and associated

tools required for the phenomena-based synthesis-intensification. Algorithms

operates at unit-operation, task and phenomena scale. The objective of Stage I

algorithm is to generate the binary ratio matrix. Stage II algorithms are used to

identify the initial search space of phenomena alongside additional phenomena

mitigating process hotspots. The objective of stage III algorithms is to identify

desirable PBBs combined using combinatorial algorithms to generate feasible

basic structures constituting SPBs, performing desired task that are further

combined to generate new and innovative solutions. At stage IV, algorithm is used

to rank the alternatives in order to identify top flowsheets for further analysis. The

knowledge bases developed and other supporting tools that assists algorithms and

steps to complete their objectives across all the stages are also presented.

PBS-Intensification: Algorithms, Knowledge bases and Supporting tools

52

5.1. Overview

The framework performing direct and indirect phenomena-based synthesis-intensification

consists of 12 algorithms and 4 knowledge bases across 4 stages. These algorithms and knowledge

bases are supported by computer-aided tools. An overview of all algorithms, knowledge bases

and supporting tools is given in Tables 5.1, 5.2 and 5.3 respectively.

Table 5.1: List of algorithms developed in the framework

Sr. No.

Algorithm Stage/Step Objective

1 A1.1 I/2 Transform the base case flowsheet to a task-based flowsheet

2 A2.1 II/3 Identify tasks in the base case flowsheet and transform the base case flowsheet to a phenomena-based flowsheet

3 A2.2 II/3 Identify PBBs in the base case flowsheet and transform a task-based and base case flowsheet to a phenomena-based flowsheet

4 A2.3 II/4 Identify additional task and phenomena based on identified process hotspots of base case

5 A3.1 III/5 Generate a mathematical combinatorial superstructure of compounds

6 A3.2 III/6 Identify list of principle PBBs for all the binary pairs

7 A3.3 III/7 Generate phenomena based superstructure

8 A3.4 III/8 Reduce alternatives within phenomena based superstructure

9 A3.5 III/9 Transform principle PBBs to basic structures using list of feasible SPBs

10 A3.6 III/10 Generate alternatives by combining basic structures

11 A3.7 III/11 Translate basic structures into unit operations to generate flowsheet alternatives

12 A4.1 IV/12 Ranking of generated flowsheet alternatives

Table 5.2: List of knowledge bases developed in the framework

No. Stage/Step Knowledge base Description Appendix

KB2.1 II/3 Translation of unit-operations to task and phenomena

List of different unit operations translated to tasks and PBBs

C.1

KB2.2 II/4 Translation of process hotspots to principle PBBs

A list of alternative tasks and phenomena building blocks (PBBs) based on process hotspots

C.2

KB3.1 III/6 Identification of principle PBBs

A list of principle PBBs identified based on pure and mixture property analysis

C.3

KB3.2 III/11 Translation of basic structures to unit operations

A database guidance to translate basic structures to unit operations

C.4

5.2. Algorithms

53

Table 5.3: List of supporting tools used across different steps in the framework

Stage/Tool ProCARPS ProPred Azeopro ASPEN/ PRO/II

ECON SustainPro LCSoft MoT

Stage I * * *

Stage II * * * * *

Stage III

Stage IV * * * * *

5.2. Algorithms

5.2.1. Algorithms: Stage I

Algorithm A1.1: Generation of the binary ratio matrix

This algorithm presents a method to generate the binary ratio matrix. A binary ratio matrix

presents the property differences of each of the binary pairs of components present in the

synthesis analysis as their property ratios except properties like dipole moment where gaseous

species possess zero dipole moment, thus the difference of properties is used instead. Following

steps are followed otherwise to generate the binary ratio matrix.

o A1.1.1. Identify the name and total number of components (NC) in the synthesis problem.

o A1.1.2. Identify the total number of binary pairs using the following equation:

NBP =NC ∗ (NC − 1)

2 (5.1)

NBP – Number of binary pairs and

NC – Number of components

o A1.1.3. Compute binary property ratio and generate the matrix as follows:

- Collect the pure component property data for the list of properties from Table 4.1.

Then compute and store the property ratio for every binary pair as follows:

If,

PAj ≥ PBj (5.2)

Then,

Rij =PAj

PBj (5.3)

Else,

Rij =PBj

PAj (5.4)

Where,

|𝑅𝑖𝑗| > 1 (5.5)


54

Rij = Binary ratio

PA = Pure component property of component A,

PB = Pure component property of component B

Example: Consider a conceptual example of a mixture with 3 compounds A, B and C. The

objective is to generate binary ratio matrix using algorithm A1.1. A list of 4 pure component

properties for the components is given in Table 5.4. So, applying the algorithm A1.1:

Table 5.4: Pure component properties for the 3 component system

Boiling

point (K) Melting

point (K) Molar volume

(m3/kmol) Molecular

weight (g/mol)

A 231.11 85.47 0.08 44.10

B 272.65 134.86 0.10 58.12

C 309.22 143.42 0.12 72.15

The name and number of components is known (A1.1.1). The number of binary pairs are

calculated to be 3 using equation 5.1 in step A1.1.2. Then, from step A1.1.3, the binary ratio matrix

is generated using equations 5.2 – 5.5 and Table 5.4. The matrix generated is shown in Table 5.5.

Table 5.5: Binary ratio matrix for the 3 component system

Boiling point

(K) Melting


(m3/kmol) Molecular weight

(g/mol)

A/B 1.18 1.58 1.27 1.32

A/C 1.34 1.68 1.53 1.64

B/C 1.13 1.06 1.20 1.24

5.2.2. Algorithms: Stage II

Algorithm A2.1: Transformation of base case flowsheet to task-based flowsheet

This algorithm presents a method to transform a base case flowsheet (unit-operation scale) to a

task-based flowsheet (task scale). The inlet and outlet in base case flowsheet joining all the unit

operations remains same in task based flowsheet.

o A2.1.1. Classify each unit operation into 3 types of tasks - Mixing, Reaction, Separation

and replace unit operations to generate the task-based flowsheet as follows:

- Reaction task - If in a unit operation, some or all of the inlet components

undergoes the conversion (reaction) to produce new component (s) and has

different inlet and outlet composition, then the unit operation is termed as a

‘reactor’ and is translated as a ‘reaction task’.

5.2. Algorithms

55

- Separation task – If in a unit operation, the inlet and outlet compositions are

different and has more than or equal to two outlet streams, then the unit

operation is termed as a ‘separator’ and is translated as a ‘separation task’.

- Mixing task - If in a unit operation, there is no reaction or separation task and

have more than one inlet streams and one or less than the number of inlet streams

in outlet with changed composition, then the unit-operation is termed as a ‘mixer’

and is translated as a ‘mixing task’.

o A2.1.2. A unit operation performing multiple tasks i.e. any combination of above tasks is

also translated. For example, a reactive distillation unit has reaction and separation task

occurring within a single unit, thus the task is defined as reaction-separation task.

o A2.1.3. For a known or identified set of unit operations, the tasks performed can directly

be identified from the knowledge base KB2.1.

Note: The unit operation affecting just change in temperature (for example a plate type heat

exchanger) and pressure (for example pump) are not considered for the task-based flowsheet.

This is because these type of unit operations are added during flowsheet finalization in rigorous

simulation and here algorithm is moving towards lower scale (Babi, 2014). Also, a mixer used for

simulation purposes in process simulators is not considered as a mixing task.

Example: Consider a conceptual example of an equilibrium, liquid phase exothermic reaction

between A and B to produce C and D, followed by the separation of AB from CD using a flash.

Then, AB and CD are separated in two simple distillation columns. The unit-operation based

process flowsheet is given in Figure 5.1. The objective here is to generate a task based flowsheet.

So, applying the algorithm A2.1, all the equipment are first identified in terms of tasks performed

using step A2.1.1. Also, all equipment in the flowsheet are known, thus using step A2.1.2-A2.1.3,

the task based flowsheet is generated as shown in Figure 5.1. Here, reactor is translated to

reaction task while, flash and two distillation columns are translated to separation task.

Algorithm A2.2: Transformation of base case flowsheet to a phenomena-based flowsheet

This algorithm presents a method to transform a base case flowsheet to phenomena based

flowsheet. Here, similar to the task based flowsheet, the inlet and outlet joining all the unit

operations remains same as in base case flowsheet.

o A2.2.1. Retrieve the unit-operation from the unit operations-based flowsheet and tasks

from the task-based flowsheet that are identified using algorithm A1.1

o A2.2.2. Search in the knowledge base KB2.1 for the unit operation retrieved from the base

case and select the list of PBBs.

o A2.2.3. For any unknown unit operations, identify the list of PBBs based on Table 5.6.

Table 5.6 presents the PBBs that can perform an identified task. Further, identify the

phase and class based on the type of task being performed.


56

o A2.2.4. Replace the tasks in the flowsheet generated in algorithm A1.1 with the PBBs to

generate the phenomena based flowsheet.

Table 5.6: PBBs identification for a task

Task/PBB M 2phM R PC PT PS ES D

Reaction * * * *

Separation * * * * * *

Mixing * * *

Example: Considering conceptual example from algorithm A2.1, the objective is to generate

phenomena based flowsheet. Thus, applying the algorithm A2.2, firstly, the unit operations

retrieved are reactor, flash and 2 distillation column. Here, reactor is performing reaction task

while flash and distillation columns are performing separation task from step A2.2.1. Then in step

A2.2.2, using KB2.1 knowledge base, the list of PBBs are retrieved as follows:

- Reactor (reaction task) ABCD – M, R(L), ES(C)

- Flash (separation task) AC/BD – M,PT(VL), PS(VL)

- Distillation (separation task) A/C – M, 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)

- Distillation (separation task) B/D – M, 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)

In step A2.2.3, all the tasks in task based flowsheet are replaced with identified PBBs to generate

phenomena based flowsheet (Figure 5.1).

Figure 5.1: Translation of base case flowsheet to task and phenomena based flowsheet

AB M, R(L), ES(C)M, PT(VL),

PS(VL)

M, 2phM, R(L),

ES(C), ES(H),

PC(VL), PT(VL),

PS(VL)

M, 2phM, R(L),

ES(C), ES(H),

PC(VL), PT(VL),

PS(VL)

ABCD

AC

BD

A

C

B

D

Phenomena based

flowsheet

B

D

ABABCD

AC

BD

A

C

Unit operation based

flowsheet

AB Reaction

task

Separation

task

Separation

task

Separation

task

ABCD

AC

BD

A

C

B

D

Task based

flowsheet

5.2. Algorithms

57

Algorithm A2.3: Identification of desirable task and phenomena

This algorithm presents a method to identify desirable task and phenomena for an existing

process flowsheet. The primary objective of this algorithm is to identify principle PBBs that can

mitigate the process bottlenecks by expanding the search space. The process hotspots are

translated to the desirable task and phenomena as follows:

o A2.3.1. Using knowledge base KB2.2, select the process hotspot to retrieve corresponding

property binary ratio values and calculate other property values concerning the task.

o A2.3.2. Retrieve additional task and feasible principle PBBs (based on binary ratios using

Appendix C.3) corresponding to the process hotspot and binary pair(s) involved. Also,

screen alternative separation task identified for reaction based on phase feasibility.

o A2.3.3. Add the retrieved principle PBBs to the existing list identified from A2.2 while

making a note that the principle PBBs are not repeated.

Note that, alternative separation task identified for the existing reaction task are for combination

using combinatorial rules (see A3.6) and not as an alternative for the reaction task.

Example: Consider the conceptual example from algorithm A2.1 and 2.2 where one of the

separation task is separation of A and C. Assume that the process hotspot identified here is the

presence of an azeotrope between A and C. The objective here is to identify additional task and

desirable phenomena that could potentially mitigate the process hotspot. Thus, applying the

algorithm A2.3, for the selected process hotspot, the list of property data and binary ratios are

retrieved using step A2.3.1. Assuming, in this case a list of property data to be feasible, the

additional task and corresponding principle PBBs are identified from step A2.3.2 as shown in

Table 5.7. These are then added to an initial list of phenomena using step A2.3.3.

Table 5.7: Additional task and PBBs identified for the process hotspot

Process hotspot

Main task Property/Binary ratio Alternative

task MSA Principle PBBs

Azeotrope Separation

Vapor pressure, solubility parameter

Separation Y 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)

Solubility parameter Separation Y PC(LL), PT(LL), PS(LL)

Vapor pressure, heat of vaporization, boiling point, solubility parameter

Separation Y 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H), PC(LL), PS(LL)

Vapor pressure, heat of vaporization, boiling point

Separation N 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)

Molar volume, solubility parameter

Separation N PT(MVL), PS(VL)

Van der Waals volume, critical temp

Separation N PT(MVV), PS(VV)

Solubility parameter, molar volume, radius of gyration

Separation N PT(MLL), PS(LL)


58

5.2.3. Algorithms: Stage III

Algorithm A3.1: Generation of mathematical combinatorial superstructure of compounds

This algorithm presents a method for generation of a mathematical combinatorial superstructure

of compounds present in the synthesis problem.

o A3.1.1. Identify the reaction task and number of compounds coming out of the reaction

task.

o A3.1.2. Identify the minimum number of separation operations required to separate NC

number of components using equation below:

NST = NC -1 (5.1)

o A3.1.3. Annotate each compound as A, B, C etc.

o A3.1.4. Starting with reaction task, identify sequentially all possible separations of each

compound coming out of the reaction system considering all the possible binary pairs.

Continue this mathematical enumeration for the subsequent remaining separation tasks

i.e. NC-1 tasks for C components to generate the combinatorial superstructure.

Example: Consider a conceptual example of a system that consists of 3 components at the

reactor outlet (A3.1.1). Thus, following step A3.1.2, maximum number of separation tasks required

are 2. From step A3.1.3, the compounds are annotated as A, B and C. The enumeration is done

using step A3.1.4. A mixture of A, B and C can be separated in 6 ways for task 1 separation. The

possibilities for separation task 1 are A/BC, A/CB, B/AC, B/CA, C/AB and C/BA. Further binary

mixture coming out of separation task 1 needs to be separated so the options for A/BC and A/CB

is B/C, for B/AC and B/CA is C/A and for C/AB and C/BA is A/B. The graphical representation of

the superstructure is shown in Figure 5.2.

Figure 5.2: Mathematical combinatorial superstructure for 3 component system

----ABC---- A/BC

A/CB

C/AB

C/BA

B/C

B/AC

B/CA

A/C

A/B

Reaction

task

Separation

task 1

Separation

task 2

5.2. Algorithms

59

Note: Equation 5.1 calculates the minimum number of separation tasks required for recovery of

all the compounds present in a system. However, scenarios may arise based on the performance

criteria and objectives of the synthesis problem, where all compounds are not required to be

recovered separately (Babi and Gani, 2014).

Algorithm A3.2: Identification of principle PBBs

This algorithm presents the method to identify feasible principle PBBs for all the binary pairs and

tasks using a knowledge base developed using physical property and thermodynamic insights.

The step at which this algorithm is used consists of only reaction and separation task. Thus,

principle PBBs are identified as follows:

o A3.2.1. Identify principle PBBs for reaction task as follows:

- ‘R’ PBB is always selected for reaction task and thus identify the phase of the

reaction in which reaction is taking place i.e. vapor (V), liquid (L), vapor-liquid

(VL) etc. After identification of phase complete the ‘R’ PBB for example R(V) for

a vapor phase reaction. For multiple phase reaction add ‘2phM’ PBB.

- Identify the type of reaction i.e. exothermic or endothermic to add the energy

supply (ES) PBB completing the list of principle PBBs for a reaction task. It is

identified as follows:

▪ For an exothermic reaction add ‘ES(C)’ PBB and for an endothermic

reaction add ‘ES(H)’ PBB.

▪ For a reaction task taking place in presence of a special energy supply (i.e.

microwave, ultrasound etc.), add ‘ES(D)’ PBB instead of ES(C) or ES(H).

o A3.2.2. Identify principle PBBs for separation task as follows:

- Retrieve the number of binary pairs and all the corresponding pure and mixture

property data from step 1 of the framework in stage I.

- Using the knowledge base KB3.1, select a binary pair to compare the possible

phase condition (mixture or ambient) and binary ratio values of corresponding

component properties. Retrieve and store the principle PBBs that satisfies the

following condition. Alongside note down the separating agent (SA) required.

Rij ≥ Threshold value

- In case of azeotropic (homogeneous and heterogeneous) binary pairs (liquid-

liquid or vapor-liquid) that are identified in step 1 and 2, retrieve and store all the

corresponding principle PBBs. Also, if the mixture analysis shows the binary pair

being pressure sensitive or having a eutectic point, retrieve and store the

corresponding principle PBBs. Alongside note down the separating agent (SA)

required if any.


60

o A3.2.3. Add and store identified principle PBBs from A2.3 (in case of availability of base

case) to the ones identified in this algorithm and avoid any repetition.

Add ‘*’ sign for a set of principle PBBs requiring any MSA

Example: Consider a conceptual example of a liquid phase exothermic reaction that converts A

to B and C in presence of a heterogeneous catalyst. The reaction is an equilibrium reaction; thus,

outlet of the reactor consists of product B, byproduct C and unreacted A. The objective here is

to identify list of principle PBBs for the reaction and separation tasks. Thus, applying algorithm

A3.2, in step A3.2.1, the phase of the reaction is known alongside the reaction being exothermic

in nature. Thus, for the reaction task the principles PBBs identified are R(L), ES(C). Following

step A3.2.2, number of binary pairs identified are 3 as number of components in the system are

3. Further assuming, a set of binary ratio of pure component properties is shown in Table 5.8.

Table 5.8: Binary ratio matrix for 3 component system

Boiling

point (K) Melting


(m3/kmol) Vapor

pressure (Pa) Solubility Parameter

(√(kJ/m3))

A/B 1.18 1.58 1.27 1.32 1.08

A/C 1.34 1.68 1.53 1.49 1.12

B/C 1.13 1.06 1.20 1.13 1.04

The binary pair is in liquid phase at both reaction and ambient conditions and does not form any

azeotrope. The binary pair also does not exhibit any miscibility gap and eutectic points. Thus,

using knowledge base KB3.1 and looking at possible feed conditions, the principle PBBs identified

are shown in Table 5.9.

Table 5.9: Identified principle PBBs for different tasks

Task Reaction (A → B)

Separation (A/B) Separation (A/C) Separation (B/C)

Principle

PBBs R(L), ES(C)

PT(MVL), PS(VL) PT(MVL), PS(VL) PT(MVL), PS(VL)

2phM, PC(VL), PT(VL),

PS(VL), ES(C), ES(H)





PT(LS), PS(LS), ES(C)/ES(H) PT(LS), PS(LS), ES(C)/ES(H)

Algorithm A3.3: Generation of phenomena based superstructure

This algorithm presents the method to generate phenomena based superstructure performing

different tasks for the synthesis-intensification problem. The algorithm is as follows:

o A3.3.1. Retrieve mathematical combinatorial based superstructure from step 5 in stage

III. If synthesis problem consists of compounds that are non-condensable, any biomass

in case of bio reactions or solids, then using knowledge based insights fix the task to

separate specific compound and choose relevant sub superstructure.

5.2. Algorithms

61

o A3.3.2. Retrieve identified principle PBBs from step 6 in stage III.

o A3.3.3. Place the corresponding principle PBBs against the reaction task and separation

tasks for key binary pair to generate phenomena based superstructure.

o A3.3.4. Add ‘*’ sign for a set of principle PBBs requiring any MSA.

o A3.3.5. Determine the outlet phase for every set of principle PBBs using KB3.1. If multiple

phases are possible then phase from the preceding task is considered as the inlet phase

to the current principle PBB.

o A3.3.6. Remove all the common principle PBBs that are in mathematical alternatives

separating same key compound from the mixture.

Note: This algorithm only generates an initial stage of level 1 phenomena based superstructure.

Level 2 and level 3 phenomena based superstructures are generated using algorithm A3.6.

Example: Consider the conceptual example from algorithm A3.1 and 3.2. Here, the objective is

to generate phenomena based superstructure. Thus, applying the algorithm, firstly, the

mathematical combinatorial superstructure and list of identified principle PBBs are retrieved as

mentioned in steps A3.3.1 and A3.3.2. Then, corresponding principles PBBs are placed for

respective tasks considering key binary pairs (A3.3.3) as shown in Figure 5.3.

Figure 5.3: Phenomena based superstructure generated for example problem

A B + C-----ABC

R(L), ES(C)

A/BC

PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)

PT(LS), PS(LS), ES(C/H)

A/CB

B/AC

B/CA

C/AB

C/BA

B/C

A/C

A/B














Reaction task Separation task 1 Separation task 2


62

In Figure 5.3, repetitive PBBs are colored for separation of same compound from the considered

mixture. As no set of principle PBB requires any MSA as identified in algorithm A3.2, thus step

A3.3.4 is skipped. Further, as mentioned in step A3.3.5, the possible outlet phase for all the set of

principle PBBs is identified using KB3.1 and repetitive PBBs are removed as mentioned in step

A3.3.6. An updated phenomena based superstructure is then shown in Figure 5.4.

Figure 5.4: Updated phenomena based superstructure generated for example problem

Algorithm A3.4: Reduction of alternatives

This algorithm presents the method for reduction of phenomena based superstructure generated

in step 8. This algorithm is divided into two sections i.e. reduction using feasibility rules and

logical rules. The algorithm is presented as follows:

• Feasibility Rules

Level 1 - Task based feasibility rules

o A3.4.1. Retrieve outlet phase of the reaction from the mixture analysis in step 1.

o A3.4.2. If the reaction mixture consists of solids in the system the first separation task

after reaction should be removal of solids and thus remove all other alternatives from

the first task after the reaction.

o A3.4.3. If the reaction mixture consists of vapor-liquid, the phases need to be

separated first after removing the solids and thus, other subsequent alternatives are

removed.

A B + C-----ABC

R(L), ES(C)

A/BC



B/AC

C/AB

B/C

A/C

A/B











L V-LV-L

L-S

V-LV-L

L-S

V-LV-L

L-S

5.2. Algorithms

63

o A3.4.4. If the mixture consists of non-condensable gases, then non-condensable

needed to be removed first thus, removing all other subsequent alternatives.

Level 2 - Phenomena based feasibility rules

o A3.4.5. If there is no azeotrope present for a binary pair and identified set of principle

PBBs include PT(VL) with no added separating agent, then the alternatives separation

not in order of boiling point of compounds are eliminated.

o A3.4.6. Eliminate the set of identified principle PBBs with PT(LS) and no added

separating agent, if the separation task is not in order of melting point of compounds.

• Logical Rules

Level 3 – Conditional rules

o A3.4.7. Retrieve the phenomena based superstructure from step 9 and identify

feasible inlet feed conditions for all the principle PBBs.

o A3.4.8. Remove principle PBBs consisting of phenomena mentioned in Table 5.10

that are not falling within the temperature range and phases of ambient mixture

conditions or feed conditions. Also, in case of presence of azeotrope, eutectic mixture

or difficult separating mixture for the considered binary pair, add required energy

supply PBBs from Table 5.10.

Table 5.10: Logical set of conditions for different transition PBBs

PBB Feed

conditions

Additional

Phenomena*

Operating

temperature

PT(MVV) V - -

PT(MVV) L, VL ES(H)/ES(D) -

PT(MLL) L - -

PT(MLL) V, VL ES(C) >0 ˚C

PT(MVL) L - -

PT(MVL) V, VL ES(C) -

PT(LS) L ES(D) >0 ˚C

PT(VL) V, L, VL ES(D) -

PT(LL) L - -

PT(VS) V, S, VS ES(C)/ES(H)/ES(D) -

o A3.4.9. After all reductions, update phenomena based superstructure from step 9.

Example: Consider phenomena based superstructure generated in conceptual example from

algorithm A3.3 (Figure 5.4). The objective here is to apply reduction rules from algorithm A3.4.

Algorithm is explained with examples at three different levels.


64

• Level - 1

Consider same superstructure in Figure 5.4 with reactor outlet conditions as V-L. Here,

component C is in vapor phase and is non condensable while component A and B are in

liquid phase. Thus, following steps A3.4.1-A3.4.4, the first task is removal of solids i.e.

removal of C from A and B. Thus, in same superstructure, except C/AB or C/BA all other

task in separation task 1 are removed. An updated superstructure is shown in Figure 5.5.

Figure 5.5: Phenomena based superstructure generated after level 1 reduction

• Level - 2

Consider Figure 5.4 with order of boiling and melting point for components as A>B>C

and no azeotrope. Thus, following step A3.4.5-A3.4.6, separation of B from A and C using

PT(VL) and PT(LS) is infeasible. So, alternatives in separation task 1 with PBB ‘PT(VL)’

and ‘PT(LS)’ are removed that contains separation of B/AC. An updated superstructure is

shown in Figure 5.6.


A B + C-----ABC

R(L), ES(C)

C/AB A/B






V-L V-LV-L

L-S

A B + C-----ABC

R(L), ES(C)

A/BC



B/AC

C/AB

B/C

A/C

A/B

PT(MVL), PS(VL)









L V-LV-L

L-S

V-L

V-LV-L

L-S

5.2. Algorithms

65

• Level - 3

Consider Figure 5.5, where the outlet of the reaction task is V-L with presence of a non-

condensable. Thus, applying step A3.4.7, the phenomena based superstructure is

retrieved along with feed conditions. These are then checked (A3.4.8) upon with Table

5.10, where in absence of any azeotropic or eutectic mixture, it is identified that the

phases allowed for principle PBB with phenomena ‘PT(MVL)’ and ‘PT(LS)’ is L, while for

‘PT(VL)’ is V, L or VL. Thus, according to reaction task outlet phase which VL, only

principle PBB with phenomena ‘PT(VL)’ is logical. The updated superstructure (A3.4.9)

after this reduction is shown in Figure 5.7.


Algorithm A3.5: Transformation of principle PBBs to basic structures

This algorithm presents the method for translating principle PBBs to basic structures by selecting

SPBs from step 7 that can perform desired task.

o A3.5.1. Identify the task activity for set of principle PBBs i.e. reaction, separation.

• Reaction

o A3.5.2. For reaction task, look for reaction PBBs within the set of principle PBBs that

need to be translated to basic structure.

o A3.5.3. Select SPBs from feasible list of SPBs generated in step 7 consisting of reaction

PBB without any mass transfer PBB.

o A3.5.4. Screen those selected set of SPBs based on the mixing and energy supply PBBs

present in principle PBBs. In case of presence of multiple energy supply PBBs, identify

additional SPB consisting of only special energy supply PBB.

o A3.5.5. Combine screened SPBs if multiple SPBs are available for basic structure.

• Separation

o A3.5.6. For separation task, look for the mass transfer PBBs within the set of principle

PBBs that need to be translated to basic structure. Then, perform steps A3.5.7-A3.5.9

for same phase PBBs in a single SPB.

A B + C-----ABC

R(L), ES(C)

C/AB A/B

2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)




V-LV-L


66

o A3.5.7. Select SPBs from feasible list of SPBs generated in step 7 consisting of all mass

transfer SPBs from the considered set of principle PBBs without reaction PBBs.

o A3.5.8. Screen those selected set of SPBs based on the energy supply SPBs present in

principle PBBs and possible inlet feed conditions.

o A3.5.9. Combine screened SPBs if multiple SPBs are available to form a basic structure

in a way that energy supply PBBs are always separated by a non-energy transfer SPB

except those with direct energy transfer PBBs if present.

o A3.5.10. Replace principle PBBs with identified basic structures in phenomena based

superstructure from step 8.

o A3.5.11. In presence of MSA and its separation, select SPBs consisting of principle

PBBs – “PT(MLL), PS(LL)”, “PT(MVL), PS(VL)”, “PT(MVV), PS(VV)” and “PC(VL),

PT(VL), PS(L), ES(C), ES(H)” to generate basic structures by following A3.5.7-A3.5.9.

Example: Consider a list of feasible SPBs shown in Table 5.11, generated from list of PBBs. The

objective here is to generate basic structures for principle PBBs from superstructure in Figure

5.7. Thus, applying the algorithm first for reaction task. The reaction PBB within principle PBBs

is R(L), thus SPB 3, 6, 7, 8, 11 and 12. These SPBs are screened in step A3.5.3, as the principle PBBs

consists of ES(C) PBB without any 2 phase mixing taking place. Thus, only SPB left after screening

is SPB no. 7. For separation task, there are 3 sets of principle PBBs. The translation is performed

individually for all. The first set of principle PBBs is 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H).

So, from step A3.5.7, SPB number 23, 24 and 25 are selected. Then screening selected SPBs based

on A3.5.8, SPB 24 and 25 are considered for combination in A3.5.9. As, SPB 24 and 25 consist of

energy supply PBBs, they need to be separated with non-energy supply SPB with same set of mass

transfer PBBs. Required SPB is identified to be SPB 23, which is then placed in between SPB 24

and 25 to generate the required basic structure. Similarly, for second and third set of principle

PBBs, SPB 29 and SPB 31 are identified individually to become required basic structures. Here,

SPB 31 is selected instead of SPB 32, because of incoming feed which is liquid, thus transition will

take place by cooling instead of heating as both A and B are liquid at ambient conditions.

Figure 5.8: Phenomena based superstructure with basic structures (Level 1 superstructure)

A B + C-----ABC C/AB A/B


V-LV-L




M=PT(MVL)=PS(VL)

M=PT(LS)=PS(LS)

M=ES(C)

M=R(L)=ES(C)




5.2. Algorithms

67

Table 5.11: Example list of feasible SPBs to generate basic structures in algorithm A3.5

SPB Connected PBB Task they may perform

SPB.1 M Mixing

SPB.2 M=2phM Mixing

SPB.3 M=R(V) Mixing+Reaction

SPB.4 M=ES(H) Mixing+Heating

SPB.5 M=ES(C) Mixing+Cooling

SPB.6 M=R(V)=ES(H) Mixing+Reaction+Heating

SPB.7 M=R(V)=ES(C) Mixing+Reaction+Cooling

SPB.8 M=2phM=R(V) Mixing+Reaction

SPB.9 M=2phM=ES(C) Mixing+Cooling

SPB.10 M=2phM=ES(H) Mixing+Heating

SPB.11 M=2phM=R(V)=ES(C) Mixing+Reaction+Cooling

SPB.12 M=2phM=R(V)=ES(H) Mixing+Reaction+Heating

SPB.13 M=2phM=PC(VL)=PT(VL) Mixing+Phase creation

SPB.14 M=2phM=R(V)=PC(VL)=PT(VL) Mixing+Reaction+ Phase creation

SPB.15 M= 2phM= ES(C)=PC(VL)=PT(VL) Mixing+Cooling+ Phase creation

SPB.16 M= 2phM= ES(H)=PC(VL)=PT(VL) Mixing+Heating+ Phase creation

SPB.17 M=2phM =R(V)=ES(C) =PC(VL)=PT(VL) Mixing+Reaction+Cooling+Phase creation

SPB.18 M=2phM=R(V)=ES(H)=PC(VL)=PT(VL) Mixing+Reaction+Heating+Phase creation

SPB.19 M=PT(VL)=PS(VL) Mixing+Separation

SPB.20 M=ES(C)=PT(VL)=PS(VL) Mixing+Cooling+Separation

SPB.21 M=ES(H)=PT(VL)=PS(VL) Mixing+Heating+Separation

SPB.22 M=R(V)=ES(H)=PT(VL)=PS(VL) Mixing+Reaction+Heating+Separation

SPB.23 M=2phM=PC(VL)=PT(VL)=PS(VL) Mixing+Separation

SPB.24 M=2phM=ES(H)= PC(VL)=PT(VL)=PS(VL) Mixing+Heating+Separation

SPB.25 M=2phM=ES(C) =PC(VL)=PT(VL)=PS(VL) Mixing+Cooling+Separation

SPB.26 M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Separation

SPB.27 M=2phM =R(V)=ES(H) =PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Heating+Separation

SPB.28 M=2phM=R(V)=ES(C)=PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Cooling+Separation

SPB.29 M=PT(MVL)=PS(VL) Mixing+Heating+Separation

SPB.30 M=PT(LS)=PS(LS) Mixing+Separation

SPB.31 M=ES(C)=PT(LS)=PS(LS) Mixing+Cooling+Separation

SPB.32 M=ES(H)=PT(LS)=PS(LS) Mixing+Heating+Separation

SPB.33 D Stream division


68

Among identified basic structures, SPB 7 and SPB 31 can also be represented as combination of

SPB 3 and 5 for reaction task and SPB 5 and 30 for separation task respectively. The updated

superstructure with all identified basic structures is shown in Figure 5.8.

Algorithm A3.6: Generation of alternatives by combining basic structures

This algorithm presents the method for combining the basic structures that can perform multiple

tasks. Here, two level (2 and 3) of phenomena based superstructures are generated. At level 2

two adjacent task are combined from level 1, while at level 3 two adjacent task are combined form

level 2. The basic structures can be combined using following rules:

o A3.6.1. Adjacent reaction and separation task can be combined to generate a basic

structure with reaction-separation task occurring in one structure with following rule.

- The phase of the key binary pair coming out of the reactor should be same as the

phase of inlet of the adjacent separation task.

- The reaction-separation task in a single basic structure can have a maximum of 4

outlets (an example being Kaibel column by Lopez-Saucedo et al. (2018)).

o A3.6.2. Adjacent separation tasks sharing the same basic structure with ‘PT(VL)’,

‘PT(VS/LS)*’ as one of the principle PBB can be combined to generate a structure

performing multiple tasks.

- The combined basic structure with ‘PT(VL)’ PBB can have a maximum of 4 outlets

(an example being Kaibel column by Lopez-Saucedo et al. (2018)).

o A3.6.3. If, a basic structure of one of an adjacent task consist one of the following

phenomena:

PT(MVL), PT(MVV), PT(MLL)

Then the following combinations rules are applied:

- The basic structure that consists of ‘R’ PBB and same phase for the key binary pair,

can be combined to generate a new basic structure.

- The combined basic structure with ‘R’ PBB should not remove any of the reactant.

- Above phenomena cannot be combined with each other in adjacent tasks.

o A3.6.4. The principle PBBs that use MSA may or may not (fixed MSA) require additional

separation task and thus any additional task required can only be combined with the

adjacent reaction task.

o A3.6.5. Adjacent basic structures with SPB having ES(C) phenomena along with PT(LS)

cannot be combined with structure having SPB with ES(H) and/or PT(MVV).

o A3.6.6. The last separation task of a binary pair with basic structure having principle SPB

PT(VL) can only be combined with similar SPB consisting of vapor-liquid phenomena.

o A3.6.7. A basic structure with principle PBBs ‘PT(VL), PS(VL)’ can only be combined with

adjacent following basic structure but not preceding one along with phase feasibility.

5.2. Algorithms

69

Example: Consider, the level 1 superstructure shown in Figure 5.8. The objective here is to

combine basic structures to generate level 2 and level 3 phenomena based superstructures. Thus,

first applying the algorithm to generate level 2 superstructure. According to step A3.6.1, adjacent

reaction-separation task can be combined. So, following combination rules, the adjacent tasks

are combined to generate a new basic structure performing reaction and separation task

together. Similarly, adjacent separation tasks are combined using step A3.6.2-A3.6.7. The basic

structure at separation task 1 can be combined with all the basic structures in separation task 2

except one with principle PBBs of ‘PT(LS), ES(C)’ according to step A3.6.5. Thus the new basic

structures generated at level 2 is shown in Figure 5.9.

Figure 5.9: Level 2 (a, b) and level 3 phenomena based superstructure

A B + C

--ABC--C/AB--A/B

Reaction-Separation task 1 Separation task 2

V-L

M=PT(MVL)=PS(VL)

M=PT(LS)=PS(LS)

M=ES(C)





M=2phM=R(L)=PC(VL)=PT(VL)=PS(VL)


C/AB - A/B

Separation - Separation

task (1 and 2)

A B + C-----ABC

Reaction task

V-LM=R(L)=ES(C)M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)

M=PT(MVL)=PS(VL)







Level 2a

Level 2b

A B + C

--ABC--C/AB—A/B

Reaction-Separation-

Separation task


M=PT(MVL)=PS(VL)








Level 3


70

Level 3 superstructure is generated by using level 2a and 2b superstructures. Thus, again using

combinatorial algorithm steps, the combined basic structures at level 3 is shown in Figure 5.9.

Algorithm A3.7: Translation of basic structures to unit-ops

This algorithm presents the method to translate basic structures to unit-operations generating

process flowsheet alternatives at unit-operation level.

o A3.7.1. Identify the SPBs building block including reaction or mass transfer PBBs within

the key basic structure that consist one or more than one SPBs.

o A3.7.2. Using the knowledgebase KB3.2, select the SPBs and identify the associated unit

operation.

o A3.7.3. If a basic structure does not match any of the listed equipment then potentially a

novel equipment is generated.

o A3.7.4. Replace every basic structure with the identified unit operation and generate

flowsheet alternatives while screening them using feed phase, use of mass or energy

separating agent and number of possible outlets.

Note: The basic structures, involving membrane operations as a first unit operation involving

separations are not translated to flowsheet alternatives except binary pair with azeotropes or

difficult separations.

Example: Consider the superstructures shown in Figure 5.8 and 5.9, where the objective is to

translate the basic structures to unit-operations generating process flowsheet alternatives at

unit-operation level. Applying algorithm A3.7, a reaction, separation and reaction-separation

basic structure is translated as follows:

- Conceptual example for reaction basic structure: The SPB for reaction task in level 1

superstructure (A3.7.1) with building block SPB is M=R=. Further, looking into knowledge

base, the unit operation identified (A3.7.2) based on SPB are shown in Table 5.12.

Table 5.12: Unit-operations based on basic structure for reaction

SPB building

block Task Unit-operation

Screening 1 Feed/Reaction

Phase

Screening 2 MSA Y/N

Screening 3 Azeotrope

Screening 4 Min no. of

outlets

M=R= Reaction Batch reactor S, V and/or L Y/N - 1

M=R= Reaction Semi-batch reactor S, V and/or L Y/N - 1

M=R= Reaction CSTR L Y/N - 1

M=R= Reaction Tubular Reactor

(PFR) V N - 1

M=R= Reaction Pack-bed reactor S and/or V N - 1

Further, the alternatives identified are screened based on reaction phase (A3.7.3) where

most suitable operation identified is a CSTR (continuous stir tank reactor).

5.2. Algorithms

71

- Conceptual example for separation basic structure: The SPB identified for separation

task 1 (A3.7.1) in level 1 with building block SPB is =2phM=PC(VL)=PT(VL)=PS(VL).

Further, looking into knowledge base, the unit operation identified (A3.7.2) based on SPB

are shown in Table 5.13.

Table 5.13: Unit-operations based on basic structure for separation

SPB building block Task Unit-

operation

Screening 1

Feed phase

Screening 2

MSA Y/N

Screening 3

Azeotrope

Screening 4

Min no. of outlets

=2phM=PC(VL)=PT(VL)=PS(VL) Separation Distillation V and/or L N Y/N 2

=2phM=PC(VL)=PT(VL)=PS(VL) Separation Kaibel

Column V and/or L Y/N Y/N 4

=2phM=PC(VL)=PT(VL)=PS(VL) Separation Dividing Wall

Column V and/or L N N 3

Further, screening based on number of outlets distillation alternative is identified as the

potential unit operation.

- Conceptual example for reaction-separation basic structure: The SPBs identified for

one of the reaction-separation task (A3.7.1) in level 3 consists of two key SPB building

blocks. These are ‘=2phM=R=PC(VL)=PT(VL)=PS(VL)’ and ‘=PT(MVL)=PS(VL)’. Further,

looking into knowledge base, the unit operation identified (A3.7.2) based on SPBs is

shown in Table 5.14.

Table 5.14: Unit-operations based on basic structure for reaction-separation

SPB building block Task Unit-operation

Screening 1

Feed phase

Screening 2

MSA Y/N

Screening 3

Azeotrope

Screening 4

Number of outlets

=2phM=R=PC(VL)=PT(VL)=PS(VL), =PT(MVL)=PS(VL)

Reaction - Separation

Membrane reactive

distillation column

V and/or L N Y/N 3

Similarly, for all other basic structures, unit-operation are identified to generate unit-operation

based flowsheet alternatives (A3.7.3-A3.7.4). An example of flowsheet alternatives generated at

each level is shown in Table 5.15.

Table 5.15: Unit-operation based flowsheet alternatives

Level Flowsheet alternative

3 Reactive divided wall distillation

2 Reactive distillation → VP membrane

1 Reaction →Distillation → Distillation


72

5.2.4. Algorithm: Stage IV

Algorithm A4.1: Ranking of feasible flowsheet alternatives

This algorithm presents the method to rank the flowsheet alternatives generated in stage III. The

objective of this algorithm is to calculate the Enthalpy Index (EI) for all the feasible flowsheet

alternatives in order to rank them to identify potential alternatives for detailed analysis.

o A4.1.1. Calculate enthalpy for individual unit-operations in all the feasible flowsheet

alternatives as follows:

- For a reactor, retrieve the enthalpy of the reaction from step 2.

- For other unit operation, perform mass balance across unit-operations using simple

mass balance models like mixer, splitter and separator (Appendix D.1) by identifying

the recovery factors (Appendix D.2-indicative list) (Tula, 2016).

- Identify inlet-outlet conditions across the unit-operation using process information

(Appendix D.2-indicative list) (Tula, 2016).

- Retrieve heat capacity data for inlet and outlet process streams.

- Calculate enthalpy change (outlet subtracted from inlet streams) for all the unit

operation using mass balance, temperature and heat capacity data across the streams.

o A4.1.2. Calculate overall enthalpy of a process alternative by adding individual enthalpies

of unit operations involved.

o A4.1.3. Calculate the Enthalpy Index (EI) for all the alternatives using following equation:

EI𝑘 =|∆H|lowest

|∆H|𝑘

(5.2)

o A4.1.4. Rank the alternatives at different levels with highest Enthalpy Index (EI) being

the top ranked alternative.

Example: Consider the flowsheet alternatives generated at the different levels (Table 5.15) in

conceptual example from A3.6. The objective here is to rank the flowsheet alternatives by

calculating enthalpy index (EI). Thus, applying algorithm A4.1 to flowsheet alternative generated

at level 1 in Table 5.14. In step A4.1.1, assume enthalpy of the reaction is -35 kJ/mol and for a

distillation column the mass balance is performed by taking recovery of the components lighter

than the light key is equal to 100% in the overhead product and the recovery of the components

heavier than the heavy key is equal to 100% in the bottom product. The recovery of the key

components is greater than or equal to 99.5%. The distillate temperature is set at bubble point

or, in case of non-condensable, dew point. The bottoms stream of the distillation process-group

is always set at bubble point. Thus, retrieving the specific heat capacity data, the enthalpy change

is calculated. Assume, enthalpy calculated for two distillation column in considered flowsheet

alternative is -28 kJ/mol and -11 kJ/mol. Thus, overall enthalpy is calculated by adding enthalpy


73

of 3 unit operations which comes out to be -74 kJ/mol. Similarly, consider the overall enthalpy

of other flowsheet alternative at level 2 and level 3 in Table 5.14 to be -39 kJ/mol and -59 kJ/mol

respectively. The EI is calculated for 3 alternatives using equation 5.2 and are ranked as shown

in Table 5.16.

Table 5.16: Ranking of flowsheet alternatives for a conceptual example using A4.1

Level Flowsheet alternative Enthalpy Index (EI) Rank

2 Reactive distillation → VP membrane 1.00 1

3 Reactive divided wall distillation 0.66 2

1 Reaction →Distillation → Distillation 0.53 3


There are 4 knowledge bases that are developed fir phenomena-based synthesis intensification

framework. An overview of all the knowledge bases is given in Table 5.2.

• Knowledge base KB2.1: Translation of unit-operation to task and phenomena This knowledge base is developed (Appendix C.1) to translate existing process flowsheet

to lower scale i.e. task and phenomena scale, thus generating task and phenomena based

flowsheet. This knowledge base assists to access an initial search space in which existing

process flowsheet is built. It mainly consists of known unit-operations found in literature

that can perform the reaction, separation, reaction-separation, and separation-separation

task. The knowledge base along with task and phenomena associated with the unit-

operation provides information about the possible feed/reaction phase, any separating

agent required, type of separating agent and any phase being added or created within the

unit operation. The knowledge is primarily used in step 3 in stage II of the framework.

• Knowledge base KB2.2: Translation of process hotspots to principle PBBs This knowledge base is developed (Appendix C.2) to translate the process hotspots

identified in the base case to additional task and desirable phenomena that may assist in

mitigating them. This knowledge base assists to expand the initial search space for an

existing process flowsheet, thus providing opportunities to generate novel solutions. The

knowledge base consists of different process hotpots, the task process hotspot associated

to, an alternative task that may be performed to mitigate the hotspot, possible list of

property analysis required to verify alternative task, use of mass separating agent and list

of phenomena associated with the alternative task. The process hotspot database is based

on detailed analysis in terms of economics, sustainability and life cycle assessment. The

knowledge base is primarily used in step 4 in stage II of the framework.


74

• Knowledge base KB3.1: Identification of principle PBBs This knowledge base is developed (Appendix C.3) to identify the list of principle PBBs for

every binary pair present in the synthesis-intensification problem. This knowledge base

is the fundamental pillar of the framework as it provides the complete search space in

terms of phenomena that may assist in achieving the desired task while generating novel

and innovative solutions. It is developed based on physical property and thermodynamic

insights from Jaksland et al. (1995). The properties and thermodynamic insights provide

information about potential driving force behind the task. For example, a significant

difference in melting point of a binary pair drives separation task by transition of one of

the components from liquid to solid phase. For an exothermic reaction task, the task can

be driven by continuously removing heat, thus exploiting the energy supply phenomena.

The knowledge base consists of physical and thermodynamic properties, its threshold

values above which a set of principle PBBs are selected for a feasible phase, potential

outlet phase and any MSA that may be required along with the set of principle PBBs. The

knowledge base thus developed is used in step 6 of stage II.

• Knowledge base KB3.2: Translation of basic structure to unit-operations This knowledge base is developed (Appendix C.4) to translate the basic structures of

phenomena to unit-operations, thus generating unit-operation based process flowsheet

alternatives. The knowledge base consists of SPB building block to be identified based on

the basic structure, task performed by the basic structure and unit-operation. Further,

there are different screening criteria based on feasible phase, mass separating agent,

presence of azeotrope and possible number of outlets from the task. The knowledge base

is used in step 11 of stage III.

5.4. Supporting tools

Over the course of four stages, there are different tools that are used being shared by all or some

of the stages. An overview of usage of different supporting tools at different stages is given in

Table 5.3. These are described in different sections as follows:

• Modelling and simulation tools Modelling and simulation tools are used in stage II and stage IV of the framework.

Modeling tool ICAS-MoT (Fedorova et al., 2014) is used which is also a part of ICAS (Gani,

2002). There are other similar tools like GAMS (GAMS Development Corporation, 2012),

gPROMS (Barton et al., 1993) that can also be used to perform modelling. While for

simulation primarily PRO/IITM/Aspen PlusTM is used, whereas tools like CHEMCADTM

can also be used for the same purpose. These simulation tools contain detailed property

models, model equations and calculation tools for standard unit-operations that can be

directly used while in modelling tools, these can be generated to fulfil the purpose of a


75

specific unit-operation. The primary objective of these tools is to generate detailed mass

and energy balance along with design data.

• Analysis tools Analysis tools are used in stage II and stage IV to analyze the process flowsheets in terms

of economics, sustainability and life cycle assessment. ECON (Saengwirun, 2011) tool is

used to perform economic analysis. In this tool, similar to some other economic analysis

tools, the economic parameters are calculated via the Guthrie Method (Seider et al.,

2008). These economic parameters include operating costs (OPEX) including utility

costs, capital costs, return on investment and production costs. SustainPro (Carvalho et

al., 2013) tool is used to perform sustainability analysis where factors such as energy and

waste cost (EWC), material value added (MVA) and total value added (TVA) are

calculated to determine the process hotspots specifically in stage II. LCSoft (Kalakul et

al., 2014) is a tool used in stage II and IV to perform life cycle analysis and thus obtain

sustainability indicators in terms of global warming potential (GWP), carbon footprint,

human toxicity (HTPI, HTPE) to name a few.

• Other tools There are some other tools for example ProCARPS (Cignitti, 2014), ProPred, Azeopro that

may be used to carry out specific tasks. In case of missing properties for certain

compounds, ProPred can be used to calculate them. ProPred and Azeopro are also part

of ICAS software (Gani et al. 1997; Gani 2002). ProCARPS can be used to identify possible

reaction paths producing desired products from certain raw materials. Azeopro is used

to identify potential azeotropes in the synthesis analysis which is also a part of ICAS

software. ICAS database (Gani et al. 1997; Gani 2002) is also used at different steps of

framework to retrieve property data.


The algorithms that are used while performing phenomena-based synthesis intensification along

with knowledge bases and associated tools were presented. Algorithms operates at phenomena,

task and unit operation level that creates an entirely new search space generating novel solutions.

The knowledge base assists phenomena based synthesis method to operate at all possible phases

covering VLE, SLE and LLE; thus, allowing to generate multiple solutions for a single synthesis

problem. Finally, an overview of supporting tools was also given.


76


77

PART - III

The third part of thesis presents the application of the developed

phenomena-based synthesis-intensification framework. The 4-

stage framework is applied to the three different case studies

including chemical and biochemical production processes. The

case studies includes direct and indirect synthesis application of

the framework. The first case study is the production of a

chemical considered as a green energy source, Dimethyl Ether

(DME) as a direct synthesis problem. The second case study is the

Hydrodealkylation (HDA) of toluene to produce benzene as a

primary product. In this case, indirect synthesis is used to

generate more innovative, sustainable and economic solutions

than an existing process flowsheet. The third case study is a bio

process where biological production of the succinic acid is

considered. In this case, first an optimal base case is synthesized

using superstructure-based optimization approach. The base

case is then designed and analysed in detail to identify potential

improvements. Then, PBS-intensification framework is applied

by selecting the optimal base case to solve an indirect synthesis-

intensification problem.


78


79

Chapter 6 Case Studies

In this chapter, three example case studies are presented, highlighting each step of

the phenomena-based synthesis-intensification framework. These case studies

are: Production of Dimethyl Ether (DME), Hydrodealkylation (HDA) of toluene,

Production of bio-succinic acid. In case study 1 and 2, the developed framework

for phenomena-based synthesis-intensification is applied which is followed by the

discussion about the results obtained. In third case study, the base case is first

synthesised by identifying an optimal processing route. The optimal process is

then designed, analysed for the process hotspots and intensified using indirect

phenomena-based synthesis-intensification method. The results generated are

then discussed and compared to the base case.

Chapter outline:

6.1. Production of Dimethyl Ether (DME)

6.1.1. Framework application

6.1.2. Discussion

6.2. Hydrodealkylation (HDA) of Toluene


6.2.2. Discussion

6.3. Production of Bio-Succinic Acid

6.3.1. Synthesis and design using superstructure based optimization

6.3.2. Application of extended phenomena-based synthesis method


6.3.4. Discussion







126, 499-519.

Case Studies

80

6.1. Case study 1: Production of Dimethyl Ether (DME)

DME is categorized as a green energy source and the demand for DME continues to increase as

it is expected to reach 11.72 billion USD by 2023 (report by Crystal Market research, 2017). It is

also a non-toxic, well-known propellant, coolant and a clean burning fuel for diesel engines. DME

as a fuel also provides high performance and low emission of greenhouse gases like CO, NOx and

particulates in its combustion as compared to other energy sources. This makes DME a preferable

source of energy over many of the others (Figure 6.1). The major producers of DME are Korea

Gas corporation, Guangdong JOVO Group CO ltd., Royal Dutch Shell, Toyota Tsusho, Mitsubishi

Corporation to name a few (Egypt Business Directory, 2018).

Figure 6.1: Importance of DME (with permission-Volvo Sustainability report, 2013)

Objective of the case study: To identify novel, innovative and intensified flowsheet alternatives

for the production of DME from methanol as a raw material with a purity of at least 99.8 mol %

(fuel grade).


Stage I: Synthesis analysis

• Step 1: Problem definition

The synthesis problem definition is to produce DME from methanol with a purity of at

least 99.8 mol % (fuel grade) which is a design constraint and performance criteria for

this problem. A joint venture has been established by 9 different companies in Japan to

produce 80 kt/y of DME (http://japan-dme.or.jp/english/dme/production.html) with

the potential expansion to 100kt/y, thus for this case the target annual production of

DME has been set to 100 kt/y.

- S1.1. Problem type

The problem type identified is direct synthesis as no prior information about process

flowsheet is selected to produce DME of required specifications from methanol.

http://japan-dme.or.jp/english/dme/production.html


81

- S1.2. Information collection

DME in industry is generally produced from two kinds of processes: Indirect method

via dehydration of methanol (MeOH) and direct method where DME is synthesized

from synthesis gas. Most of the industrial DME is currently produced by indirect

method (Japan DME Association). The reaction pathway identified by performing

literature search is shown below.

2CH3OH ⇌ CH3OCH3 + H2O

The methanol dehydrates in the presence of Al2O3 catalyst to produce DME and water

(Zhang et al., 2011). The reaction is an equilibrium reaction and operates at 593.15 K

and 0.1 MPa pressure. Being an equilibrium reaction, the outlet of the reactor consists

of DME, water and unreacted methanol.

• Step 2: Problem analysis

In this step all the necessary reaction, physical property and thermodynamic analysis is

performed which is required for rest of the stages. This is carried out in terms of reaction

analysis and mixture analysis.

- S2.1. Reaction analysis

The reaction in step 1 confirms the possibility to produce DME from methanol. The

reaction takes place at high temperature in vapor phase. The equilibrium conversion

of the reaction is 84.38% (Zhang et al., 2011). The catalyst used is a heterogeneous

catalyst. The reaction is reversible and thus, kinetic data for the reaction is retrieved

from Zhang et al. (2011). The heat of reaction is -23.5 kJ/mol, which makes reaction

to be exothermic as it is less than zero.

- S2.2. Mixture analysis

The outlet of the reactor consists of DME, water and unreacted methanol. In this part

of step 2, the pure and mixture component analysis is performed to set up the basis

for stage III.

Pure component analysis

The list of pure component properties is retrieved from ICAS database (Gani et

al. 1997; Gani 2002) and literature search. The retrieved list is shown in Table 6.1.

Then, by following the steps A1.1.1-A1.1.2 of algorithm A1.1, the number of binary

pairs are calculated to be 3 as the number of compounds in the problem are

identified to be 3 (Methanol (MeOH), DME and Water). These components are

annotated as A, B and C respectively. Then, the binary ratio matrix of pure

component properties for binary pairs is calculated using step A1.1.3 of algorithm

A1.1. The binary ratio matrix for a selected set of pure component properties is

shown in Table 6.2.

Case Studies

82

Table 6.1: Pure component properties data for the compounds involved in the problem

Property UOM MeOH (A) DME (B) Water (C)

MW (g/mol) 32.04 46.07 18.02

ω - 0.56 0.20 0.34

Tc (K) 512.64 400.10 647.13

Pc (bar) 79.91 53.00 217.67

Zc - 0.22 0.27 0.23

Vc (m3/kmol) 0.12 0.17 0.06

Tb (K) 337.85 248.31 373.15

dm (Debye) 1.70 1.30 1.85

rg (Å) 1.55 2.15 0.62

Tm (K) 175.47 131.66 273.15

Ttp (K) 175.47 131.65 273.16

Ptp (Pa) 0.11 3.01 603.73

MV (m3/kmol) 0.01 0.07 0.02

Hf (kJ/kmol) -200940 -184100 -241810

Gf (kJ/kmol) -162320 -112800 -228590

SIG (kJ/kmol·K) 239.88 266.70 188.72

Hfus (kJ/kmol) 3215.00 4937.00 6001.70

Hcomb (kJ/kmol) -638200 -1328400 0.00

δ (√(kJ/m3) 29.59 15.12 47.81

Vvw (m3/kmol) 0.02 0.03 0.01

Avw (m2/kmol) 3.58E+08 4.84E+08 2.26E+08

Pvap (Pa) 16832.70 637841.0 3170.00

log Kow - -0.77 0.10 -1.38

Hvap (kJ/mol) 35.20 21.50 40.70

d (pm) 376 465 296


83

Table 6.2: Binary ratio matrix for the selected set of properties

Property MeOH/DME

(A/B) MeOH/Water

(A/C) DME/Water

(B/C)

MW 1.44 1.78 2.56

ω 2.82 1.64 1.72

Tc 1.28 1.26 1.62

Pc 1.51 2.72 4.11

Zc 1.23 1.02 1.20

Vc 1.44 2.11 3.04

Tb 1.36 1.10 1.50

rg 1.39 2.52 3.50

Tm 1.33 1.56 2.07

Ttp 1.33 1.56 2.07

Ptp 27.36 5488.45 200.59

MV 6.64 1.71 3.89

SIG 1.11 1.27 1.41

δ 1.96 1.62 3.16

Vvw 1.43 1.76 2.51

Avw 1.35 1.58 2.14

Pvap 37.89 5.31 201.21

log Kow -7.70 6.31 -13.80

Hvap 1.64 7.31 1.89

d 1.27 7.31 1.57

Mixture property analysis

Following analysis is performed for the mixture from the reactor outlet:

▪ The mixture state or phase (after reaction) – Vapor

▪ State of pure components at mixture conditions and ambient conditions

- Mixture conditions – MeOH, Water, DME - Vapor

- Ambient conditions – MeOH – Liquid, Water – Liquid, DME - Vapor

▪ Azeotropes and pressure sensitivity - None

▪ Liquid-liquid phase splits or eutectic points – None

Case Studies

84

Stage II: Base case analysis

As the problem type identified is direct synthesis to generate novel and intensified alternatives,

no base case has been selected, thus stage 2 including step 3 and step 4 is bypassed.

Stage III: Generation of feasible flowsheet alternatives

• Step 5: Generation of mathematical combinatorial superstructure of compounds

The mathematical combinatorial superstructure of compounds is generated by following

algorithm A3.1. The number of compounds is 3 and are annotated as A (MeOH), B (DME)

and C (Water). Minimum number of separation tasks required are 2 to obtain all pure

compounds. This is because any unreacted methanol has to be recycled while the DME

purity should be at least 99.8 mol %. Thus, the superstructure is generated based on all

possible mathematical combinations and is shown in Figure 6.2. The number of possible

flowsheet alternatives at this step are 6.

Figure 6.2: Mathematical combinatorial superstructure of compounds

• Step 6: Identification of principle PBBs

The binary ratio matrix is retrieved from step 2 and thus following the algorithm A3.2,

principle PBBs for all the binary pairs are identified using knowledge base KB3.1 and are

listed in Table 6.3. The PBBs that are not feasible as per mixture phase at ambient or

reaction conditions are removed.

*The separation is using an external solid mass separating agent. Also, note that list in

Table 6.3 is based on a constraint that principle PBBs requiring an external mass

separating agent that further requires an additional separation task are not selected. The

‘M’ PBB is selected by default for all SPBs.

2A B + C-----ABC A/BC

A/CB

C/AB

C/BA

B/C

B/AC

B/CA

A/C

A/B

Reaction taskSeparation

task 1

Separation

task 2


85

Table 6.3: Identified list of principle PBBs

Binary

pair

2MeOH → DME + Water

(A → B + C)---ABC--- MeOH/DME (A/B) MeOH/Water (A/C) DME/Water (B/C)

Principle

PBBs

R(V), ES(C) PT(VL), PS(VL) PT(LS), PS(LS), ES(C) PT(VL), PS(VL)

PT(MVV), PS(VV) PT(MVV), PS(VV) PT(MVV), PS(VV)

PT(MLL), PS(LL) PT(MLL), PS(LL) PT(MLL), PS(LL)








PC(LS/VS), PS(LS/VS)* PC(LS/VS), PS(LS/VS)* PC(LS/VS), PS(LS/VS)*

• Step 7: Generation of list of feasible SPBs

In this step, a list of feasible SPBs is generated using the PBBs identified in previous steps.

The total number of PBBs identified are M, 2phM, R(V), PC(VL), PT(VL), PS(VL),

PT(MVV), PS(VV), PT(MLL), PS(LL), PT(LS), PS(LS), PT(MVL), PC(LS), PC(VS), PS(VS),

ES(C), ES(H), D - 19.

- S7.1. Operating window for identified PBBs

The operating window of each phenomena is shown in Table 6.4.

Table 6.4: Operating window for all identified PBBs (Pressure – 0.1 MPa)

Phenomena (PBB) Operating Window

M Tlow=131.66 K (lowest melter)

Thigh=373.15 K (highest boiler)

2phM Tlow=131.66 K (lowest melter)


R(V) Tlow=373.15 K (highest boiler)

Thigh=593.15 K (T for reaction from literature)

PC(VL) V-L present

PC(LS) L-S present (solid separating agent)

PC(VS) V-S present (solid separating agent)

PT(VL) Tlow=248.31 K (lowest boiler)


PT(LS) Tlow=131.66 K (lowest melter)

Thigh=273.15 K (highest melter)

PT(MVL) Component affinity

PT(MVV) Component affinity

PT(MLL) Component affinity

PS(LL) L-L present

Case Studies

86

PS(VL) V-L present

PS(VV) V-V present (all compounds in vapor phase)

PS(LS) L-S present (can be solid separating agent)

PS(VS) V-S present (solid separating agent)

ES(H) -

ES(C) -

D -

- S7.2. Feasible SPBs

The maximum number of SPBs including both feasible and infeasible are calculated

to be 63003 (from equation 4.2). The list of feasible SPBs generated from identified

PBBs using adjacency matrix and SPB building blocks is shown in Table 6.5. As the

solid phase in’ PC(LS/VS)* and PS(LS/VS)*’ PBBs from Table 6.3 is fixed, the rules are

applied on these PBBs together and are considered different from PT(LS) and PS(LS).

Table 6.5: Generated list of feasible SPBs


SPB.1 M Mixing

SPB.2 M=2phM Mixing











SPB.13 M=2phM=PC(VL)=PT(VL) Mixing+ Phase creation

SPB.14 M=2phM=R(V)=PC(VL)=PT(VL) Mixing+Reaction+Phase creation

SPB.15 M= 2phM=ES(C)=PC(VL)=PT(VL) Mixing+Cooling+ Phase creation

SPB.16 M= 2phM=ES(H)=PC(VL)=PT(VL) Mixing+Heating+ Phase creation

SPB.17 M=2phM=R(V)=ES(C) =PC(VL)=PT(VL) Mixing+Reaction+Cooling+ Phase creation

SPB.18 M=2phM=R(V)=ES(H)=PC(VL)=PT(VL) Mixing+Reaction+Heating+ Phase creation


SPB.20 M=R(V)=PT(VL)=PS(VL) Mixing+Reaction+Separation



87





SPB.26 M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL) Mixing+Heating+Separation

SPB.27 M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL) Mixing+Cooling+Separation





SPB.32 M= PT(MVV)=PS(VV) Mixing+Cooling+Separation

SPB.33 M=R(V) =PT(MVV)=PS(VV) Mixing+Reaction+Separation

SPB.34 M=PT(MLL)=PS(LL) Mixing+Cooling+Separation

SPB.35 M=PC(VS)=PS(VS)* Mixing+Separation

SPB.36 M=R(V)=PC(VS)=PS(VS)* Mixing+Reaction+Separation

SPB.37 M=R(V)=ES(C)=PC(VS)=PS(VS)* Mixing+Reaction+Cooling+Separation

SPB.38 M=R(V)=ES(H)=PC(VS)=PS(VS)* Mixing+Reaction+Heating+Separation

SPB.39 M=PC(LS)=PS(LS)* Mixing+Separation

SPB.40 M=ES(H)=PC(LS)=PS(LS)* Mixing+Heating+Separation

SPB.41 M=ES(C)=PC(VS)=PS(VS)* Mixing+Cooling+Separation

SPB.42 M=ES(H)=PC(VS)=PS(VS)* Mixing+Heating+Separation

SPB.43 M=ES(C)=PC(LS)=PS(LS)* Mixing+Cooling+Separation





• Step 8: Generation of phenomena based superstructure

The phenomena based superstructure is generated by using the algorithm A3.3. The

mathematical combinatorial superstructure (Figure 6.2) is combined with principle PBBs

in Table 6.3 to generate phenomena based superstructure. The possible outlet phase is

also identified and marked. Thus, the superstructure generated is shown in Figure 6.3.

Further, the repetitive principle PBBs for same separation with different binary pairs are

removed (for example A/BC and A/CB). These principle PBBs for same binary pairs are

marked with green color (Figure 6.3). The reduced superstructure is shown in Figure 6.4.

• Step 9: Reduction of alternatives and generation of basic structures

- S9.1. Reduction of alternatives

The reduction of alternatives is performed at 3 different levels under feasibility rules

and logical rules.

Case Studies

88

Figure 6.3: Generated phenomena based superstructure

2A B + C-----ABC

R(V), ES(C)

A/BC

PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)


PC(LS/VS), PS(LS/VS)*

A/CB

PT(LS), PS(LS), ES(C)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)



B/AC




B/CA




C/AB




C/BA




B/C




A/C




A/B




V-LV-VL-LV-LV-L

V/L

V-LV-VL-LV-LV-L

V/L

L-SV-VL-LV-LV-L

V/L

V-LV-VL-LV-LV-L

V/L

V-LV-VL-LV-LV-L

V/L

L-SV-VL-LV-LV-L

V/L

V

Reaction task Separation task - 1 Separation task - 2


89

Figure 6.4: Phenomena based superstructure after removing repetitive principle PBBs

Figure 6.5: Phenomena based superstructure after applying feasibility rules

2A B + C-----ABC

R(V), ES(C)

A/BC




A/CB


B/AC




C/AB

PT(LS), PS(LS), ES(C/H)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)



C/BA

PT(VL), PS(VL)

B/C




A/C




A/B




V-LV-VL-LV-LV-L

V/L

V-LV-VL-LV-LV-L

V/L

L-S

V-L

L-SV-VL-LV-LV-L

V/L

V


2A B + C-----ABC

R(V), ES(C)

A/BC

PT(MVV), PS(VV)PT(MLL), PS(LL), ES(C)PT(MVL), PS(VL), ES(C)PC(LS/VS), PS(LS/VS)*

B/AC

PT(VL), PS(VL)PT(MVV), PS(VV)

PT(MLL), PS(LL), ES(C)PT(MVL), PS(VL), ES(C) 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)


C/AB

PT(MVV), PS(VV)PT(MLL), PS(LL), ES(C)PT(MVL), PS(VL), ES(C)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)


C/BA

PT(VL), PS(VL)

B/C




A/C




A/B




V-VL-LV-LV/L

V-LV-VL-LV-LV-L

V/L

V-L

V-VL-LV-LV-L

V/L

V


Case Studies

90

Feasibility rules

Firstly, the phenomena based superstructure is reduced by applying feasibility

rules at 2 different levels as mentioned in algorithm A3.4. After applying these

rules, the superstructure is reduced as shown in Figure 6.5. Following the

algorithm, the outlet of the reactor is in vapor phase and has no solids present.

Also, there are no non-condensable gases present at outlet. Thus, superstructure

maintains it originality at level 1 reduction rules. Further, looking at phenomena

based feasibility rules at level 2, phenomena with PBB ‘PT(VL)’ under binary pair

A/B and ‘PT(LS)’ under binary pair A/C in ternary mixture of A, B and C is not

feasible according to boiling point and melting point order.

Logical rules

At level 3 reduction (logical rules), the phase of inlet and outlet conditions are

checked and thus, PBBs that does not satisfy the logical rules in algorithm A3.4

are removed. For example, A/BC has outlet in ‘V’ phase, and thus, options with

principle PBBs that only allows ‘L’ feed like ‘PT(MLL), PT(MVL), PC(LS)*’ are

removed in B/C. The updated superstructure is shown in Figure 6.6.

Figure 6.6: Phenomena based superstructure after applying logical rules

2A B + C-----ABC

R(V), ES(C)

A/BC

PT(MVV), PS(VV)PC(VS), PS(VS)*

B/AC



PC(VS), PS(VS)*

C/AB

PT(MVV), PS(VV)PT(MLL), PS(LL), ES(C)PT(MVL), PS(VL), ES(C)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)

PC(VS), PS(VS)*

C/BA

PT(VL), PS(VL)

B/C



PC(VS), PS(VS)*

A/C




A/B




V-VV-V

V-LV-VV-L

V-V

V-L

V-VL-LV-LV-L

V-V

V



91

- S9.2. Generation of basic structures

The principle PBBs in phenomena-based superstructure (Figure 6.6) are translated to

basic structures using the algorithm A3.5. These basic structures in the form of

superstructure (level 1) is shown in Figure 6.7.

Figure 6.7: Level 1 superstructure with translated principle PBBs to basic structures

• Step 10: Combination of basic structure to generate flowsheet alternatives

The basic structures within the superstructure at level 1 are combined at two different

levels i.e. level 2 and 3 as follows:

Level 2: At level 2, adjacent basic structures within level 1 (Figure 6.7) are considered for

combination following all the generic rules defined in algorithm A3.6. Further in level 2,

two different combinations are performed at level 2a and level 2b. At level 2a, adjacent

A/BC

M=PT(MVV)=PS(VV)

M=PC(VS)=PS(VS)*

2A B + C-----ABC

M=R(V)=ES(C)

B/AC

M=PT(MVV)=PS(VV)

M=PC(VS)=PS(VS)*

M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)M=2phM=PC(VL)=PT(VL)=PS(VL)


M=PT(VL)=PS(VL)

B/C



M=PT(VL)=PS(VL)

M=PT(MVV)=PS(VV)

M=PC(VS)=PS(VS)*

A/C



M=PT(LS)=PS(LS)M=ES(C)

M=PT(MVV)=PS(VV)

M=PT(MLL)=PS(LL)

M=PT(MVL)=PS(VL)

M=PC(VS)=PS(VS)*

M=PC(LS)=PS(LS)*

A/B



M=PT(VL)=PS(VL)

M=PT(MVV)=PS(VV)

C/BA

M=PT(VL)=PS(VL)

C/AB

M=PT(MVV)=PS(VV)

M=PC(VS)=PS(VS)*



V-V

V-V

V-L

V-V

V-L

V-V

V-V

V-L

V-V

V-L


M=PC(VS)=PS(VS)*

M=PC(LS)=PS(LS)*

V

Cas

e S

tud

ies

92

Fig

ure

6.8

: C

om

bin

ati

on

of

ba

sic

stru

ctu

res

at

lev

el

2a

an

d l

ev

el

2b

2A

B

+ C

----

-AB

C

M=

R(V

)=E

S(C

)V

C/A

B--

-A/B

M=

PT

(VL)=

PS

(VL)

M=2p

hM=E

S(C

)=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

2p

hM=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

2p

hM=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PC

(VS

)=P

S(V

S)*

M=P

C(M

VV

)=P

S(V

V)

M=

PT

(VL)=

PS

(VL)

M=P

C(V

S)=

PS

(VS

)*M

=P

T(V

L)=

PS

(VL)

M=

PT

(MV

V)=

PS

(VV

)M

=2p

hM=E

S(C

)=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

2p

hM=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=2p

hM=E

S(H

)=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

2p

hM=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=2p

hM=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=2p

hM=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

2p

hM=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=2p

hM=E

S(C

)=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

2p

hM=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=P

C(V

S)=

PS

(VS

)*M

=2p

hM=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

2p

hM=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

B/A

C--

-A/C

M=P

T(V

L)=

PS

(VL)

M=

ES

(C)

M=P

T(L

S)=

PS

(LS

)

M=P

T(V

L)=

PS

(VL)

M=

2p

hM=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=2p

hM=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=2p

hM=E

S(H

)=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

PT

(VL)=

PS

(VL)

M=P

C(M

LL)=

PS

(LL)

M=P

T(V

L)=

PS

(VL)

M=

PC

(LS

)=P

S(L

S)*

M=

PT

(MV

V)=

PS

(VV

)M

=P

C(V

S)=

PS

(VS

)*

M=P

T(M

VV

)=P

S(V

V)

M=

2p

hM=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=2p

hM=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

2p

hM=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=2p

hM=E

S(C

)=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

2p

hM=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=2p

hM=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=P

T(M

VL)=

PS

(VL

)

M=

2p

hM=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=2p

hM=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

2p

hM=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=P

T(M

LL)=

PS

(LL)

M=

2p

hM=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=2p

hM=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

2p

hM=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=2p

hM=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

2p

hM=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=2p

hM=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

PC

(LS

)=P

S(L

S)*

M=2p

hM=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

2p

hM=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PC

(LS

/VS

)=P

S(L

S/V

S)*

M=E

S(C

)M

=P

T(L

S)=

PS

(LS

)

A/B

C--

-B/C

M=P

C(V

S)=

PS

(VS

)*M

=P

T(M

VV

)=P

S(V

V)

M=2p

hM=E

S(C

)=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=2p

hM=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=P

C(V

S)=

PS

(VS

)*M

=2p

hM=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=2p

hM=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=P

C(V

S)=

PS

(VS

)*

M=

PT

(MV

V)=

PS

(VV

)M

=2p

hM=E

S(C

)=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=2p

hM=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=2p

hM=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PC

(VS

)=P

S(V

S)*

M=P

T(M

VV

)=P

S(V

V)

M=

PC

(VS

)=P

S(V

S)*

Reac

tio

n t

ask

Sep

ara

tio

n t

as

kS

ep

ara

tio

n t

as

kS

ep

ara

tio

n t

as

k

Le

vel

2a

Le

vel

2b

2A

B

+ C

---A

BC

---B

/AC

M=

2p

hM=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=2p

hM=

R(V

)=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

2p

hM=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

R(V

)=E

S(C

)M

=P

T(M

VV

)=P

S(V

V)

M=

R(V

)=E

S(C

)M

=P

C(V

S)=

PS

(VS

)*

2A

B

+ C

---A

BC

---C

/AB

M=2p

hM=E

S(C

)=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

2p

hM=

R(V

)=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

2p

hM=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

R(V

)=E

S(C

)M

=P

T(M

VV

)=P

S(V

V)

M=

R(V

)=E

S(C

)M

=P

C(V

S)=

PS

(VS

)*

2A

B

+ C

---A

BC

---A

/BC

M=R

(V)=

ES

(C)

M=

PT

(MV

V)=

PS

(VV

)

M=

R(V

)=E

S(C

)M

=P

C(V

S)=

PS

(VS

)*

B/C

M=2p

hM=E

S(C

)=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

2p

hM=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=2p

hM=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=P

T(V

L)=

PS

(VL)

M=

PT

(MV

V)=

PS

(VV

)

M=

PC

(VS

)=P

S(V

S)*

A/C

M=

2p

hM=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=2p

hM=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=

2p

hM=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=P

T(L

S)=

PS

(LS

)M

=E

S(C

)

M=P

T(M

VV

)=P

S(V

V)

M=P

T(M

LL)

=P

S(L

L)

M=P

T(M

VL

)=P

S(V

L)

M=P

C(V

S)=

PS

(VS

)*

M=

PC

(LS

)=P

S(L

S)*

A/B

M=

2p

hM=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)M

=2p

hM=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=2p

hM=E

S(H

)=P

C(V

L)=

PT

(VL

)=P

S(V

L)

M=P

T(V

L)=

PS

(VL)

M=P

T(M

VV

)=P

S(V

V)

M=P

C(V

S)=

PS

(VS

)*

Sep

ara

tio

n t

as

k -

1R

eactio

n -

Sep

aratio

n t

ask


93

reaction and separation task are combined to identify feasible combinations while at level

2b, adjacent separation tasks are combined. The feasible combinations at both the levels

are shown in Figure 6.8.

Level 3: At level 3, the superstructures generated at level 2a and 2b are considered for

combination and the combinatorial structures should have same phase or feasible to be

combined with adjacent structures. Thus, using combination rules in algorithm A3.6, the

superstructure performing multiple tasks is shown in Figure 6.9. Also, as the reaction is

an equilibrium reaction, thus the combination of reaction and separation basic structures

removing products may lead to an increased conversion of the reactant making it feasible

to get pure products. For that matter, the combination of reaction and separation task-2

is also considered at level 3.

Figure 6.9: Combination of basic structures at level 3

• Step 11: Translation of the basic structures to unit-operation

The basic structures that perform different identified tasks are then translated to unit

operations using algorithm A3.7 generating process flowsheet alternatives. Table 6.6

gives selected alternatives for the given problem at different levels while Figure 6.10

2A B + C--ABC--A/B/C

M=2phM=ES(C)=PC(V L)=PT(V L)=PS(V L)

M=2phM=R(V)=P C(VL)=P T(VL)=P S(VL)

M=PT(MVV)=PS(VV)

M=2phM=ES(H)=PC(V L)=PT(V L)=PS(V L)

M=PT(MVV)=PS(VV)

M=R(V)=ES(C)

M=PC(VS)=PS(VS)*

M=2phM=ES(C)=PC(V L)=PT(V L)=PS(V L)


M=R=PC(LS/VS)=P S(LS/VS)*

M=2phM=P C(VL)=P T(VL)=P S(VL)


M=PC(V S)=PS(VS)*

M=R(V)=ES(C)

M=PC(V S)=PS(VS)*


M=2phM=P C(VL)=P T(VL)=P S(VL)

M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL)


M=2phM=ES(H)=PC(VL)=PT(V L)=PS(V L)

Reaction - Separation -

Separation task

Level 3

Reaction - Separation task

2A B + C----B/C


M=2phM=R(V)=PC(V L)=PT(V L)=PS(V L)


M=R(V)=E S(C)

M=PT(MVV)=PS(VV)

M=R=PC(VS)=PS(VS)*

Case Studies

94

shows some of the basic structures that are translated to unit-operation at level 3. The

complete list of flowsheet alternatives (88 process alternatives) is given in Appendix E.1.

Figure 6.10: Combination of basic structures-(A)-Reactive membrane distillation column, (B)-Reactive membrane adsorption column, (C)-Reactive multistage

adsorption, (D)-Membrane reactor, (E)-Reactive distillation column

DME

Water

MeOH

MeOH

DME

Water

MeOH

Water

DME

MeOH

DME

MeOH

Water

MeOH

DME

Water

MeOH

MeOH



M=PT(MVV)=PS(VV)


M=PT(MVV)=PS(VV)

M=PC(VS)=PS(VS)*

M=R(V)=ES(C)

M=PC(VS)=PS(VS)*

M=R(V)=ES(C)

M=PC(VS)=PS(VS)*

M=PT(MVV)=PS(VV)

M=R(V)=ES(C)




Basic strucutre Unit-operation

(A)

(B)

(C)

(D)

(E)


95

Many of the alternatives generated can be found in literature. For example, alternative 14

(Reaction followed by two distillation columns) is the traditional process to produce

DME from methanol (Muller and Hubsch, 2005; Azizi et al., 2014). Alternative 67

(Reactive distillation followed by distillation) and alternative 85 (Reactive divided wall

distillation) are proposed by Kiss and Suszwalak, (2012) while alternative 87 (reactive

distillation) is proposed by Bildea et al. (2017). Some of the alternatives generated are

completely new and have novel unit-operations. Alternative 81 with single unit-operation

i.e. reactive membrane (vapor–permeation) distillation column and alternative 84 with

reactive multi-stage adsorption column are some of the novel solutions generated by the

framework.

An overview of screening of the generated process flowsheet alternatives is given in Figure 6.11.

The total number of mathematical combinations possible are 6. At the phenomena level, it began

with 63003 possible SPB combinations based on selected PBBs. Using principle PBBs, 216

possible flowsheet combinations are identified, which are then screened based on logical and

feasibility rules and further combined based on feasible list of SPBs to generate 88 feasible

flowsheet alternatives for ranking and analysis.

Figure 6.11: Generation and screening of alternatives at different steps

Stage IV: Ranking, analysis and comparison

• Step 12: Ranking and verification of generated flowsheet alternatives

- S12.1. Ranking of unit-operation based flowsheet alternatives

In this step, the generated flowsheet alternatives are ranked in order to identify the

promising one’s that can be further analyzed. The alternatives are ranked based on

the Enthalpy Index (EI) values calculated as described in algorithm A4.1. Table 6.6

shows the top 3 alternatives based on EI values at different levels.

06

63003

216

88

Mathematical

alternatives

All possible

combination of SPB’s

Total number of

alternatives

(feasible + infeasible)

Total number of alternatives

(feasible including novel

and intensified solutions)

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96

Table 6.6: Top ranked flowsheet alternatives at different levels

Level Alternative

No. Flowsheet alternative EI

3

82 Reactive membrane (vapor) adsorption (water removal) 0.863

84 Reactive multi-stage adsorption 0.860

81 Reactive membrane (vapor) distillation (water removal) 0.462

2

72 Membrane (vapor) reactor (water removal) → VP membrane 1.000

74 Membrane (vapor) reactor (water removal) → Adsorption (MSA(S)) 0.961

61 Membrane (vapor) reactor (DME removal) → VP membrane 0.908

1

26 Reaction → Adsorption (Water-MSA(S)) → VP membrane 0.913

24 Reaction → Adsorption (Water-MSA(S)) → Adsorption (MSA(S)) 0.875

18 Reaction → Adsorption (MeOH-MSA(S)) → VP membrane 0.834

- S12.2. Verification of selected flowsheet alternatives

The top alternatives at different levels are then verified by performing simulations in

PRO/IITM. This is also done to resolve the mass and energy balance of the alternatives,

to verify the key parameters and conduct the post analysis in step 13. Due to lack of

data in literature regarding adsorption and membrane separation for MeOH and

DME removal at the desired process conditions, some of the top alternatives are not

considered for simulation. Thus, simulation is performed for the alternative next in

the ranking while at level 1, traditional alternative of reaction followed by two

distillation columns is selected for further analysis.

o Process alternative 81: This is a novel alternative for the DME production

from methanol with a novel equipment which is yet to be realized in

practicality (Figure 6.12). However, a few similar configurations (without

reactive section) named as distillation-pervaporation in a single unit (DPSU)

are available in literature for this novel equipment being proposed by

Fontalvo and Keurentjes, (2015) and Leon and Fontalvo, (2018). In another

article (Haelssig et al., 2012), a distillation-pervaporation system with internal

membrane was studied and called as membrane dephlegmation process

(MDP). Here in this alternative, unwanted by-product water is removed using

vapor-permeation membrane module within a distillation column and DME

is recovered as distillate while recovered methanol from the bottom is

recycled. The vapor permeation membrane data obtained from Lee et al.

(2004) is used for simulation purposes.

o Process alternative 74: In this process flowsheet (Figure 6.13), water is

removed in the membrane reactor using same vapor permeation membrane

used in process alternative 81. The outlet of membrane reactor containing the


97

Figure 6.12: Schematic of process alternative 81 - Reactive DVPSU column

Figure 6.13: Schematic of process alternative 74


DME

Water

MeOH

MeOH

MeOH

Water

DME

MeOH

MeOH

Water

MeOH

DME

Case Studies

98

DME and unreacted MeOH is then sent to an adsorption column where

MeOH is adsorbed to obtain DME of required purity. The adsorption data for

MeOH is obtained from Rao et al. (2007).

o Process alternative 14: This alternative is the traditional alternative to

produce DME from methanol (EI value-0.33). Here, the reactor is followed by

a sequence of distillation columns to recover DME and send recovered MeOH

back to the reactor (Figure 6.14).

• Step 13: Analysis and comparison of selected flowsheet alternatives

- S13.1. Analysis of selected alternatives

The selected process alternatives are analyzed in terms of economics, sustainability

and life cycle assessment. In-house tools that are part of ICAS (Gani et al. 1997; Gani

2002) is used to perform sustainability (SustainPro) and life cycle analysis (LCSoft).

Selected set of indicators calculated are shown in Table 6.7.

Table 6.7: Analysis of results for selected process flowsheet alternatives

Parameter Alternative 81 Alternative 74 Alternative 14

General results DME Production (kt/y) ∼100 ∼100 ∼100

DME purity (mol %) >99.8 >99.8 >99.8

RM Consumption (kt/y) 142.74 143.04 139.12

RM Cost (M$/y) 61.38 61.51 59.82

RM (MeOH) loss (kt/y) 3.51 3.50 0.05

Energy usage (MJ/hr) 27851.3 23040.0 38878.7

Number of tasks performed 03 03 03

Number of unit operations 01 02 03

Performance metrics DME (kg/kg main RM) 0.701 0.700 0.719

Energy usage (MJ/kg DME) 2.01 1.66 2.80

RM Cost ($/kg DME) 0.614 0.615 0.598

LCA results Carbon footprint (kg CO2/kg DME) 7.04E-03 7.02E-03 1.59E-02

HTPI (1/LD50) 0.103 0.095 0.174

PCOP 0.197 0.182 0.334

HTC (kg benzene eq.) 0.239 0.221 0.405

- S13.2. Comparison of selected alternatives

The comparison of analysis for three selected feasible alternative is given in Table 6.7.

Alternative 81 has the least number of equipment’s as compared to alternative 74 and

the traditional process alternative 14. Flowsheet alternative 74 shows better values of


99

the performance parameters in terms of energy, carbon footprint and sustainability

indicators among three. Though, traditional process alternative 14 incur less loss of

MeOH as compared to alternative 81 and 74 owing to membrane separation. A better

membrane in terms of selectivity can further improve performance of novel

intensified equipment and flowsheet alternatives. The membrane area calculated

along with other data is given in Appendix E.2 and E.3. For each of the alternatives

the required product purity is achieved while maintaining the production target.

The results claim the objective set in the beginning of the case study which is the required purity

of DME is achieved with target production. Also, novel, innovative and intensified process

flowsheet alternatives are generated.

6.1.2. Discussion

This case study showcases the capability of developed framework to perform direct process

synthesis-intensification (generation of novel, innovative and intensified solutions without any

prior information and pre-postulation) generating novel, innovative and intensified flowsheet

alternatives. The case study has no prior information and postulation about the kind of

alternatives that can be generated for a target product from a selected raw material. Thus, PBS-

Intensification framework provides a systematic approach to synthesize potentially feasible novel

process options along with innovative solutions.

Since, the primary objective of the framework is to systematically generate potentially feasible

novel unit-operations; for a direct synthesis problem, this case study generates number of

completely novel unit-operation based flowsheets along with existing solutions present in

literature for the production of DME. Table 6.10 presents 3 such novel equipment translated from

phenomena basic structures. Some similar configurations are also available in literature where

for example, adsorption section or membrane module are within the reactor or a distillation

column are replaceable and thus justify the feasibility of such equipment that still needed to be

validated using detailed modelling or by performing experiments.

Case Studies

100

6.2. Case study 2: Hydrodealkylation (HDA) of Toluene

Toluene being less useful chemical than benzene, most of it is converted to benzene either by

hydrodealkylation or disproportionation reaction. The Hydrodealkylation (HDA) of toluene is a

well-known petrochemical process to produce benzene, where toluene is reacted with hydrogen

to produce benzene along with by products (mainly methane) due to side reactions depending

on the reaction conditions. This method of production for benzene is also called ‘on-purpose’

method as compared to the conventional Benzene-Toluene-Xylene (BTX) extraction processes.

Benzene is one of the most produced and used chemical around the petrochemical industry,

being mainly used to produce cyclohexane that is a nylon precursor.

Objective of the case study: To identify more sustainable, innovative and intensified flowsheet

alternatives for the production of benzene from an existing process flowsheet (Tula, 2016) using

hydrodealkylation of toluene.




The synthesis problem definition is to produce benzene from hydrodealkylation of

toluene with a purity of at least 99 mol % being one of the design constraint and

performance criteria for this problem. The target annual production of benzene has been

set to 80 kt/y. These parameters are set to be same as existing process flowsheet.


The problem type identified is indirect synthesis as an existing process flowsheet is

selected as a base case (Tula, 2016) for HDA of toluene to produce benzene.


The same reaction pathway used in the existing process (Tula, 2016) is used in this

problem given as below:

C7H8 + H2 → C6H6 + CH4

2C6H6 ⇌ C12H10 + H2

The hydrodealkylation of toluene can be carried out in different ways i.e. in presence

of the catalyst or homogeneously (Meidanshahi et al., 2011). So, high temperature

reactions can be used instead of using catalysts. The dealkylation reaction for toluene

is exothermic with typical high operating conditions ranging from 500oC to 650oC

around 40 bar. The main reaction at these high operating conditions produces water

and benzene on hydrodealkylation of toluene. There is also a side reaction where


101

product benzene reacts with another molecule of benzene to form biphenyl and

hydrogen.


In this step all the necessary reaction, physical property and thermodynamic analysis is

performed which is required for rest of the stages. This is carried in terms of reaction

analysis and mixture analysis.


The reaction in step 1 confirms the possibility to produce benzene from hydro-

dealkylation of toluene. The reaction takes place at high temperature and high

pressure in vapor phase. The conversion of the main reaction is 75% (Tula, 2016).

The reaction kinetics can be retrieved from Douglas, (1988). The heat of the reaction

for HDA of toluene reaction is -50.3 kJ/mol, which means the reaction is exothermic

as it is less than zero.


The outlet of the reactor consists of 5 components i.e. benzene, biphenyl, methane,

hydrogen and toluene. In this part of step 2, the pure and mixture component analysis

is performed to set up the basis for stage III.


The list of pure component properties is retrieved from ICAS database (Gani et

al. 1997; Gani 2002) and literature search. The retrieved list is shown in Table 6.8.

Then, by following the steps A1.1.1-A1.1.2 of algorithm A1.1, the number of binary

pairs are calculated to be 10 as the number of compounds in the problem are

identified to be 5 (Hydrogen, Methane, Toluene, Benzene and Biphenyl). These

components are annotated as A, B, C, D and E respectively. Then, the binary ratio

matrix of pure component properties for binary pairs is calculated using step

A1.1.3 of algorithm A1.1. The binary ratio matrix for selected set of pure component

properties is shown in Table 6.9.


Following analysis is performed for the mixture from the reactor outlet:

▪ The mixture state or phase (after reaction) – Vapor

▪ State of pure components at mixture conditions and ambient conditions

- Mixture conditions

Hydrogen, Methane, Toluene, Benzene and Biphenyl - Vapor

- Ambient conditions

Hydrogen, Methane – Vapor, Toluene, Benzene – Liquid, Biphenyl -

Solid

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102

▪ Azeotropes and pressure sensitivity - None


Table 6.8: Pure component properties data for the compounds involved in the problem

Property UOM Hydrogen

(A) Methane

(B) Toluene

(C) Benzene

(D) Biphenyl

(E)

MW (g/mol) 2.02 16.00 92.00 78.00 154.00

ω - -0.22 0.01 0.26 0.21 0.37

Tc (K) 33.19 191.00 592.00 562.00 789.00

Pc (bar) 12.96 45.00 41.00 48.00 38.00

Zc - 0.31 0.29 0.26 0.27 0.30

Vc (m3/kmol) 0.06 0.10 0.32 0.26 0.50

Tb (K) 20.39 112.00 384.00 353.00 528.00

dm (Debye) 0.00 0.00 0.36 0.00 0.00

rg (Å) 0.37 1.12 3.47 3.00 4.83

Tm (K) 13.95 90.69 178.18 278.68 342.20

Ttp (K) 13.95 90.69 178.18 278.68 342.20

Ptp (atm) 0.07 0.12 4.18E-07 0.05 9.25E-04

MV (m3/kmol) 0.03 0.04 0.11 0.09 0.16

Hf (kJ/kmol) 0.00 -74520 50170 82880 182420

Gf (kJ/kmol) 0.00 -50490 122200 129600 280230

SIG (kJ/kmol·K) 131.00 186.00 321.00 269.00 394.00

Hfus (kJ/kmol) 117.00 941.00 6636.00 9866.00 18580.00

Hcomb (kJ/kmol) -241820 -802620 -3734000 -3136000 -6031700

δ (√kJ/m3) 6.65 12.00 18.32 18.73 19.26

Vvw (m3/kmol) 0.01 0.02 0.06 0.05 0.09

Avw (m2/kmol) 1.43E+08 2.88E+08 7.42E+08 6.00E+08 1.07E+09

Pvap (Pa) 1.65E+08 6.18 E+07 3.8E+03 1.26E+04 1.19

log Kow - 0.45 1.09 2.69 2.13 4.01

d (pm) 289.0 380.0 585.0 585.0 -


103


Binary pair/Property MW Tb Tm Mv δ Vvw Pvap

Hydrogen (A)

Methane (B)

7.94 5.49 6.52 1.31 1.81 2.70 2.67

Toluene (C)

45.93 18.83 12.77 3.79 2.76 9.52 43505.26

Benzene (D)

38.69 17.31 20.00 3.07 2.82 7.62 13120.63

Biphenyl (E)

76.39 25.9 24.52 5.52 2.90 14.6 1.39E+08

Methane (B)

Toluene (C)

5.75 3.43 1.96 2.89 1.53 3.53 16263.76

Benzene (D)

4.88 3.15 3.07 2.34 1.56 2.82 4904.94

Biphenyl (E)

9.63 4.71 3.76 4.21 1.61 5.41 5.19E+07

Toluene (C)

Benzene (D)

1.18 1.09 1.57 1.24 1.02 1.25 3.32

Biphenyl (E)

1.67 1.38 1.92 1.45 1.05 1.53 3191.81

Benzene (D)

Biphenyl (E)

1.97 1.50 1.23 1.80 1.03 1.92 10583.37


The objective of stage II is to analyze the selected base case (Tula, 2016). The base case flowsheet

for HDA of toluene shown in Figure 6.15. In this flowsheet, hydrogen (with 3 mol% of methane

as impurity) and toluene is fed into the reactor operating at high pressure and temperature,

where mentioned reactions takes place. The outlet of the reactor is then flashed after cooling to

recover hydrogen which is recycled to the reactor along with a small purge. The bottom from the

flash then goes through a sequence of distillation columns to recover benzene.

Figure 6.15: Base case flowsheet for HDA of toluene (Tula, 2016)

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104

The distillate from first distillation column are the gases that were not recovered from flash. The

bottom of second distillation column is then crystallized to obtain crystalline biphenyl while

toluene is sent back to the reactor. A purge ratio of 0.8 is used in base case flowsheet (Tula, 2016).

• Step 3: Generation of task and phenomena based flowsheet

- S3.1. Task based flowsheet

The base case flowsheet shown in Figure 6.15 is translated to task based flowsheet by

identifying unit-operations involved in the process. The unit-operations identified

are reactor, flash column, distillation column and crystallizer. Further, unit-operation

based flowsheet is translated to task based flowsheet using algorithm A2.1. The task

based flowsheet is shown in Figure 6.16.

Figure 6.16: Task based flowsheet for the base case

- S3.2. Phenomena based flowsheet

The phenomena are identified for the unit-operations involved in the base case using

algorithm A2.2. All the unit-operations are known and are present in knowledge base

KB2.1. The phenomena based flowsheet is shown in Figure 6.17. The initial search

space of phenomena identified is M, 2phM, R(V), E(C), ES(H), PC(VL), PT(VL),

PT(LS), PS(VL), PS(LS).

Figure 6.17: Phenomena based flowsheet for the base case

Reaction task

Hydrogen +

Methane

Toluene

Biphenyl

BenzeneFlue gas

PurgeHydrogen + Methane

Separation task Separation task Separation task Separation task

Reaction task

M, R(V), ES(C)

Hydrogen +

Methane

Toluene

Biphenyl

BenzeneFlue gas

PurgeHydrogen + Methane

Separation task

M, 2phM, PC(VL), PS(VL)

Separation task

M, 2phM, PC(VL), PT(VL),


Separation task

M, 2phM, PC(VL), PT(VL),


Separation task

M, PT(LS), PS(LS), ES(C)


105

• Step 4: Identification of additional task and phenomena

- S4.1. Process hotspots and design targets

The process hotspots are identified based on economic, sustainability and life cycle

analysis. These are the raw material loss from the purge stream and is based on high

negative value of material value added for hydrogen and methane. Other process

hotspot is high energy consumption and/or demand based on high utility cost and

CO2 equivalent value from heat exchangers (temperature rise for feed and recycle)

and reboilers of both the distillation column. An overview of sustainability, economic

and life cycle analysis is given in Appendix F. The life cycle analysis is performed using

LCSoft. Further using the Appendix B, following design targets are set based on these

process hotspots:

▪ Reduce raw material loss

▪ Reduce energy consumption

▪ Improvement in LCA/sustainability indicators

▪ Product purity (par on performance criteria)

▪ Production target (par on performance criteria)

- S4.2. Additional task and phenomena

A list of additional task and phenomena are identified based on the process hotspots

using algorithm A2.3 and knowledge base KB2.2. These are shown in Table 6.10.

Table 6.10: Additional task and phenomena to overcome identified process hotspots

Process Hotspot

Main task Binary

pair Phase

Alternative Task

MSA Principle PBBs

Raw material loss

Reaction - V Separation N 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)

Reaction - V Separation N PT(MVL), PS(VL)

Reaction - V Separation N PT(MVV), PS(VV)

High energy consumption/demand

Separation C/D L Separation Y PC(LL), PT(LL), PS(LL)

Separation C/D L Separation Y PC(LS), PS(LS)

Separation C/D L Separation Y 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)

Separation C/D L Separation N 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)

Separation C/D L Separation N PT(MVL), PS(VL)

Separation A/B V Separation N PT(MVV), PS(VV)

Separation A/B V Separation Y PC(VS/VL), PS(VS/VL)

These additional list of phenomena in Table 6.10 are added to initial list identified in

step 3 without repetition. Thus, list of phenomena at the end of stage II is as follows:

M, 2phM, R(V), ES(C), ES(H), PC(VL), PC(LL), PC(LS), PT(VL), PT(LS), PT(MVL),

PT(MVV), PT(MLL), PT(LL), PS(VV), PS(LL), PS(VL), PS(LS).

Case Studies

106




algorithm A3.1. As, the number of compounds are 5 and are annotated as A, B, C, D and

E. Minimum number of separation tasks required are 4 to obtain all pure compounds.

Thus, the superstructure generated based on all possible mathematical combinations is

shown in Figure 6.18. The number of possible alternatives at this step are 39636.







Binary

pair

C + A → D + B, 2D → E + A

(---ABCDE---)

Hydrogen/Methane

(A/B)

Hydrogen/Toluene

(A/C)

Hydrogen/Benzene

(A/D)

Principle

PBBs

R(V), ES(C) PT(MVV), PS(VV) PT(VL), PS(VL) PT(VL), PS(VL)

PC(VS), PS(VS)* PT(MVV), PS(VV) PT(MVV), PS(VV)

PT(MLL), PS(LL) PT(MLL), PS(LL)

PT(MVL), PS(VL) PT(MVL), PS(VL)





PC(LS/VS), PS(LS/VS)* PC(LS/VS), PS(LS/VS)*

Binary

pair

Hydrogen/Biphenyl

(A/E)

Methane/Toluene

(B/C)

Methane/Benzene

(B/D)

Methane/Biphenyl

B/E

Principle

PBBs

PT(VL), PS(VL) PT(VL), PS(VL) PT(VL), PS(VL) PT(VL), PS(VL)

PT(MVV), PS(VV) PT(MVV), PS(VV) PT(MVV), PS(VV) PT(MVV), PS(VV)

PT(MLL), PS(LL) PT(MLL), PS(LL) PT(MLL), PS(LL) PT(MLL), PS(LL)

PT(MVL), PS(VL) PT(MVL), PS(VL) PT(MVL), PS(VL) PT(MVL), PS(VL)









PC(LS/VS), PS(LS/VS)* PC(LS/VS), PS(LS/VS)* PC(LS/VS), PS(LS/VS)* PC(LS/VS), PS(LS/VS)*

Binary

pair

Toluene/Benzene

C/D

Toluene/Biphenyl

C/E

Benzene/Biphenyl

D/E

Principle

PBBs

PT(LS), PS(LS), ES(C/H) PT(LS), PS(LS), ES(C/H) PT(LS), PS(LS), ES(C/H)

PT(MVL), PS(VL) PT(VL), PS(VL) PT(VL), PS(VL)


PS(VL), ES(C), ES(H) PT(MVV), PS(VV)

PT(MVV), PS(VV)

PC(LS), PS(LS)

PC(LS), PS(LS)* PT(MVL), PS(VL) PT(MVL), PS(VL)





PC(LS), PS(LS)* PC(LS), PS(LS)*


107


A + C B + D

2D A + E

--ABCDE--

A/BCDE

B/ACDE

E/ABCD

AB/CDE

C/ABDE

D/ABCE

AC/BDE

AD/BCE

BD/ACE

BE/ACD

AE/BCD

BC/ADE

CD/ABE

CE/ABD

DE/ABC

ABCD A/BCD

A/CBD

AB/DC

BA/CD

A/DBC

AB/CD

BA/DC

AC/BD

CA/DB

AD/BC

AC/DB

CA/BD

AD/CB

DA/BC

DA/CB

B/ACD

B/CDA

B/DAC

C/ABD

C/BDA

C/DBA

D/ABC

D/BCA

D/CAB

CDE

B/CD

B/DC

C/BD

C/DB

D/BC

D/CB

A/CD

A/DC

C/AD

C/DA

D/AC

D/CA

A/BD

A/DB

B/AD

B/DA

D/AB

D/BA

A/BD

A/DB

B/AD

B/DA

D/AB

D/BA

C/D

B/D

B/C

A/D

A/C

A/B

C/D

B/D

A/D

A/B

B/D

A/D

A/B

C/D

A/C

B/D

A/D

C/B

C/ED

CD/E

C/DE

DC/E

D/CE

D/EC

D/E

C/D

C/E

10*6

5*4

A/B

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108

*The separation is using an external mass separating agent. Also, note that list in Table 6.11 is

based on a constraint that principle PBBs requiring an external mass separating agent that

further requires an additional separation task are not selected.


In this step, a list of feasible SPBs is generated using the PBBs identified in previous

steps. The total number of PBBs identified are M, 2phM, R(V), ES(C), ES(H), PC(VL),

PC(LS), PC(VS), PT(VL), PT(LS), PT(MVL), PT(MVV), PT(MLL), PS(VV), PS(LL),

PS(VL), PS(LS), PS(VS), D - 19.



Table 6.12: Operating window for all identified PBBs


M Tlow=13.95 K (lowest melter)

Thigh=850.00 K (highest reaction temperature from literature)

2phM Tlow=13.95 K (lowest melter)


R(V)

P= 40 bar (reaction pressure from literature)



PC(VL) V-L present (also liquid separating agent)

PC(LS) L-S present (solid separating agent)

PC(VS) V-S present (solid separating agent)

PT(VL) Tlow=20.39 K (lowest boiler)


PT(LS) Tlow=13.95 K (lowest melter)

Thigh=342.00 K (highest melter)


PT(MVV) Component affinity


PS(VL) V-L present

PS(VV) V-V present (all compounds in vapor phase)


PS(LL) L-L present (liquid separating agent)

PS(VS) V-S present (solid separating agent)


109

ES(H) -

ES(C) -

D -




PBBs using adjacency matrix and SPB building blocks is shown in Table 6.13. The

combination rules are applied together for principle PBBs with MSA’s.



SPB.1 M Mixing

SPB.2 M=2phM Mixing












SPB.14 M=2phM=R(V)=PC(VL)=PT(VL) Mixing+Reaction+ Phase creation



SPB.17 M=2phM=R(V)=ES(C)=PC(VL)=PT(VL) Mixing+Reaction+Cooling+ Phase creation

SPB.18 M=2phM=R(V)=ES(H)=PC(VL)=PT(VL) Mixing+Reaction+Heating+ Phase creation






SPB.24 M=R(V)=ES(C)=PT(VL)=PS(VL) Mixing+Reaction+Cooling+Separation







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110


SPB.32 M= PT(MVV)=PS(VV) Mixing+Cooling+Separation

SPB.33 M=R(V) =PT(MVV)=PS(VV) Mixing+Reaction+Separation


SPB.35 M=PC(VS)=PS(VS)* Mixing+Separation

SPB.36 M=R(V)=PC(VS)=PS(VS)* Mixing+Reaction+Separation

SPB.37 M=R(V)=ES(C)=PC(VS)=PS(VS)* Mixing+Reaction+Cooling+Separation

SPB.38 M=R(V)=ES(H)=PC(VS)=PS(VS)* Mixing+Reaction+Heating+Separation



SPB.41 M=ES(C)=PC(VS)=PS(VS)* Mixing+Cooling+Separation

SPB.42 M=ES(H)=PC(VS)=PS(VS)* Mixing+Heating+Separation








mathematical combinatorial superstructure (Figure 6.18) is combined with principle

PBBs from Table 6.11 to generate phenomena based superstructure. The possible outlet

phase is also identified and marked. As, hydrogen (A) and methane (B) gases are non-

condensable, the first task is selected as removal of these non-condensable gases and thus

choosing relevant sub superstructure from Figure 6.18, phenomena based superstructure

is generated as shown in Figure 6.19.

Further, the repetitive principle PBBs for same separation with different binary pairs are

removed (for example AB/CDE, AB/DCE, AB/ECD, BA/CDE, BA/DCE and BA/ECD).

These principle PBBs for same binary pairs are marked with green color (Figure 6.19). The

reduced superstructure is shown in Figure 6.20.


- S9.1. Reduction of alternatives The reduction of alternatives is performed at 3 different levels under feasibility rules

and logical rules.

Feasibility rules


rules at 2 different levels using algorithm A3.4. Following algorithm, the outlet of

the reactor is in vapor phase and has no solids present. Thus, the superstructure

maintains it originality at level 1 reduction rules. Further, looking at phenomena


111

based feasibility rules at level 2, phenomena with PBB ‘PT(VL)’ under binary pairs

C/E, C/D and ‘PT(LS)’ under binary pair D/E in ternary mixture of C, D and E are

not feasible according to boiling point and melting point order.


L-SV-LV-VV-LV-L

V-L

L-SV-LV-VL-SV-LV-L

V-L

L-SV-LV-VV-LV-L

V-L

L-SV-LV-VL-SV-LV-L

V-L

L-SV-LV-L

V-L

L-SV-LV-L

V-L

C/DE

PT(LS), PS(LS), ES(C)PT(MVL), PS(VL)



C/ED

PT(LS), PS(LS), ES(C)PT(VL), PS(VL)

PT(MVV), PS(VV)PT(MVL), PS(VL)



CD/E


PT(MVV), PS(VV)PC(LS), PS(LS)



DC/E





D/CE




D/EC





D/E

PT(LS), PS(LS), ES(C/H)PT(VL), PS(VL)




C/D

PT(LS), PS(LS), ES(C/H)PT(MVL), PS(VL)



C/E





R(V), ES(C)

AB/CDE




AB/DEC




AB/ECD




BA/CDE




BA/DEC

PT(VL), PS(VLPT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)



BA/ECD




A + C B + D

2D A + E

--ABCDE-- V-LV-VL-LV-LV-L

V-L

V-LV-VL-LV-LV-L

V-L

V-LV-VL-LV-LV-L

V-L

V-LV-VL-LV-LV-L

V-L

V-LV-VL-LV-LV-L

V-L

V-LV-VL-LV-LV-L

V-L

V

Reaction task Separation task - 1 Separation task - 2 Separation task - 3

A/B


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112

Figure 6.20: Phenomena based superstructure after removing repetitive principle PBBs

Logical rules



are removed. For example, outlet mixture from reactor is in ‘V’ phase, and thus,

options with principle PBBs that only allows ‘L’ feed like ‘PT(MLL), PT(MVL),

PC(LS)*’ are removed in first separation task.

The updated superstructure after all reductions is shown in Figure 6.21.

- S9.2. Generation of basic structures The principle PBBs in phenomena-based superstructure (Figure 6.21) are translated

to basic structures using the algorithm A3.5. These basic structures in the form of


V-LV-V

L-SV-LV-VL-SV-LV-L

V-L

L-SV-LV-VL-SV-LV-L

L-SV-LV-L

V-L

V-L

C/DE




C/ED


CD/E





D/CE


D/EC




D/E





C/D




C/E





R(V), ES(C)

AB/CDE




A + C B + D

2D A + E

--ABCDE-- V-LV-VL-LV-LV-L

V-L

V


A/B



113

Figure 6.21: Phenomena based superstructure after applying reduction rules



levels i.e. level 2 and 3 as follows:

Level 2: At level 2, adjacent basic structures within level 1 (Figure 6.7) are considered for

combination following all the generic rules defined in algorithm A3.6. Further in level 2,

three different combinations are performed at level 2a, 2b and 2c. At level 2a, adjacent

reaction and separation task are combined to identify feasible combinations while at level

2b, adjacent separation task are combined. The feasible combinations in the form of

superstructure are shown in Appendix F.2.

Level 3: At level 3, the superstructures generated at level 2a, 2b and 2c are considered for

combination and the combinatorial structures should have same phase or feasible to be

combined with adjacent structures. Thus, using combination rules in algorithm A3.6, the

superstructure performing multiple tasks is shown in Appendix F.3.

V-V

L-SV-LV-VL-SV-LV-L

V-L

V-LV-VL-SV-LV-L

L-SV-LV-L

V-L

C/DE



C/ED

PT(MVV), PS(VV)

CD/E





D/CE


D/EC

PT(VL), PS(VL)PT(MVV), PS(VV)PC(LS), PS(LS)


D/E





C/D




C/E





R(V), ES(C)

AB/CDE




A + C B + D

2D A + E

--ABCDE--V-LV-VV-L

V-L

V


A/B


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114

Figure 6.22: Level 1 superstructure with translated principle PBBs to basic structures

• Step 11: Translation of the basic structures to unit-operation

The basic structures that perform different identified tasks are then translated to unit

operations using algorithm A3.7 generating process flowsheet alternatives. Table 6.14

gives selected alternatives for the given problem at different levels while Figure 6.23

shows some of the basic structures that are translated to unit-operation. The complete

list of flowsheet alternatives generated is given in Appendix F.4.

Many of the alternatives generated are available in literature. For example, alternative 118

(Reaction followed by flash and multiple distillation column to separate benzene and the

A + C B + D

2D A + E

--ABCDE--

M=R(V)=ES(C)

C/DEAB/CDE

C/ED

D/E

C/D

M=PT(VL)=PS(VL)

M=PT(MVV)=PS(VV)



M=PC(VS)=PS(VS)*

M=PT(MVV)=PS(VV)

M=PT(MVL)=PS(VL)

M=PC(VS/LS)=PS(VS/LS)*

M=PT(LS)=PS(LS)M=ES(C/H)

M=PT(MVL)=PS(VL)





D/EC

M=PT(VL)=PS(VL)

M=PT(MVV)=PS(VV)

M=PC(LS)=PS(LS)

M=PT(MVL)=PS(VL)




CD/E

M=PT(VL)=PS(VL)

M=PT(MVV)=PS(VV)

M=PC(LS)=PS(LS)

M=PT(MVL)=PS(VL)






M=PT(VL)=PS(VL)

M=PT(MVV)=PS(VV)

M=PC(LS)=PS(LS)

M=PT(MVL)=PS(VL)






C/E

M=PT(VL)=PS(VL)

M=PT(MVV)=PS(VV)

M=PT(MVL)=PS(VL)






V-L

V-L

V-L

V-L

V-V

V

L-S

V-V

V-L

V-L

D/CE


L-S

M=PC(VS/LS)=PS(VS/LS)* V-L

V-V

V-L

L-S

V-L

V-L

V-L

L-S

V-V

V-L

V-L


A/B

M=PT(MVV)=PS(VV)

M=PC(VS)=PS(VS)*


115

Figure 6.23: Combination of basic structures-(A)-Cooling crystallizer, (B)-Distillation column, (C)-Membrane distillation column (DPVSU), (D)-Reactive divided wall column




M=PT(LS)=PS(LS)

M=ES(C)







(A)

(B)

(C)

(D)Toluene + Biphenyl

Toluene + H2

Methane + H2

Benzene

Toluene + Biphenyl

Toluene

Biphenyl

Benzene

Methane + H2

Toluene, H2,

Methane, Benzene, Biphenyl,

Toluene + Biphenyl


M=PT(MVL)=PS(VL)



Toluene

Biphenyl

Toluene+ Biphenyl

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116

toluene) is proposed by Douglas, (1985). Alternative 118 including membrane to separate

purged non condensable and recycling them to reactor is proposed by Bouton and

Luyben, (2008). While, Konda et al. (2006), proposed a similar alternative to Bouton and

Luyben, (2008) where membrane is used to recover hydrogen directly from flash outlet

in place of purged stream. Some of the generated alternatives (493-514, 530-549, 593-

616) including reactive distillation are also studied in literature (Shah et al., 2012).

An overview of screening of the generated process flowsheet alternatives is given in Figure 6.24.

The total number of mathematical combinations possible are 39636. At the phenomena level, it

began with 63003 possible SPB combinations based on selected PBBs. Using principle PBBs

20304 possible flowsheet combinations were identified which were then screened based on

redcutuon and feasibility rules and further combined based on feasible list of SPBs to generate

726 feasible flowsheet alternatives for ranking and analysis.




- S12.1. Ranking of unit-operation based flowsheet alternatives The flowsheet alternatives generated in stage 3 of the framework are ranked based on

calculated Enthalpy Index (EI) values. The top alternatives at different levels are

highlighted in Table 6.14.

- S12.2. Verification of selected flowsheet alternatives

The selected alternatives are verified by performing simulations in PRO/IITM and

Aspen PlusTM. Due to unavailability of data regarding separation using membrane and

adsorption at required conditions for benzene, toluene and biphenyl, the alternatives

further having lower Enthalpy Index (EI) value are selected. The alternatives selected

at different levels are further analyzed.

39636

63003

13536

726

Mathematical

alternatives

All possible


Total number of

alternatives






117

Table 6.14: Top ranked flowsheet alternatives at different levels

Level Alternative


3 718 Reaction→Multistage membrane (vapor) adsorption (gases removal) 0.981

726 Reaction→Multistage adsorptive (gases removal) membrane 0.971

2 582 Membrane reactor (gases removal) → VP membrane → Adsorption (MSA(S)) 0.968

579 Membrane reactor (gases removal) → VP membrane → VP membrane 0.982

1 33 Reaction → Adsorption (MSA(S)) → VP membrane → Adsorption (MSA(S)) 1.000

37 Reaction → Adsorption (MSA(S)) → Adsorption (MSA(S)) → Adsorption-MSA(S) 0.999

o Alternative 118 (hydrogen/methane separation using gas membrane):

The selected alternative resembles the base case flowsheet except the mixture

of unreacted hydrogen and methane (unwanted by product) are recycled to

the reactor. Here, this mixture which is also the cause of highest energy

consumption and utility cost among all the heat exchangers in base case is

separated using membrane at the purge stream. The membrane data is

adapted from the process alternatives suggested by Konda et al. (2006) and

Fischer and Iribarren, (2011). An extra stabilizer column is required as non-

condensable are not completely removed from the flash. The schematic of this

alternative is shown in Figure 6.25.


o Alternative 272: In this alternative, the benzene, toluene and biphenyl are

separated using divided wall column (DWC). The DWC is simulated using

petlyuk column in Aspen PlusTM. The schematic of the alternatives is shown

in Figure 6.26. The separation of the non-condensable hydrogen and methane

using membrane is also considered as in alternative 118.

Hydrogen +

Methane

Toluene

Toluene

Biphenyl

BenzeneFlue gas

Methane

Hydrogen + Methane

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118


Besides, these alternatives, other process flowsheets at level 3 incorporating reactive distillation

with high EI value followed by distillation or crystallization can also be analyzed. In this case

study, the analysis is performed limiting to level 1 and level 2 alternatives.



The selected process alternatives are analyzed in terms of economics, sustainability

and life cycle assessment using in-house tools. An indicative analysis for the selected

alternatives along with the base case is shown in Table 6.15.


The comparison of analysis for selected feasible alternatives is given in Table 6.15.

Both alternatives are novel process flowsheets to produce benzene from

hydrodealkylation of toluene. These alternatives are more sustainable and economic

than the base case and also shows improvement in LCA indicators.

In selected alternatives, an additional task as compared to the base case is added in terms of

membrane to separate methane from recycle stream. This is to reduce the amount of purge and

thus reduction of hydrogen loss. Addition of this gas membrane reduces the annual hydrogen

loss by around 97 %. Overall benzene production also increases owing to better recovery of

hydrogen. The energy consumption reduces in both the alternatives. The value of LCA indicators

has better values than base case (performed using LCSoft for all the alternatives including base

case). The membrane area calculated along with other data is given in Appendix F.5. A better

membrane in terms of flux or permeability can further improve performance of novel and

intensified flowsheet alternatives. For each of the alternatives, product purity is above required

while approximately achieving annual production target. A graphical comparison of three

selected alternatives is shown in Figure 6.27. Due to considerably large reduction in hydrogen

loss, a factor of 20 is taken for Figure 6.27.

Hydrogen +

Methane

Toluene

Toluene

Flue gas

Biphenyl

Benzene

Methane

Hydrogen + Methane


119

Table 6.15: Analysis of results for selected process flowsheet alternatives

Parameter Base case Alternative 118 Alternative 272

General results Benzene production (kt/y) ∼80 ∼80 ∼80

Benzene purity (mol %) >99 >99 >99

RM Consumption (Mt/y) 106.02 102.98 103.00

RM Cost (M$/y) 21.22 18.06 18.06

RM (H2) loss (kt/y) 2538.24 82.78 82.78

Total heating energy (M KJ/hr) 34.57 34.22 33.42

Total cooling energy (M KJ/hr) 43.67 36.17 33.65

Number of tasks performed 4 4 4

Number of unit operations 5 6 5

Performance

metrics

Benzene (kg/kg RM) 0.75 0.77 0.78

Energy usage (MJ/kg Benzene) 7.91 7.10 6.70

RM Cost ($/kg Benzene) 0.27 0.23 0.23

LCA results Carbon footprint (CO2 equivalent) 0.94 0.90 0.87

HTPI (1/LD50) 51.05 16.72 16.72

HTPE 47.78 15.30 15.30

ATP 59.20 57.54 57.54

GWP 7.90 7.82 7.82

Further, recalling the design targets set in step 4, which are required to be met in order to achieve

more sustainable, economic and innovative solutions. These are as follows:

- Reduce raw material loss – Yes (96 % reduction annually)

- Reduce energy consumption – Yes (10-15 % reduction per kg of product)

- Improvement in LCA/sustainability indicators – Yes (1-67 % reduction)

- Product purity (par on performance criteria) – Yes (achieved as required)

- Production target (par on performance criteria) – Yes (achieved as required)

6.2.2. Discussion

This case study showcases the capability of developed framework to perform indirect process

synthesis-intensification (generation of the more economic, sustainable, novel and intensified

process alternatives for an existing process). The base case is selected from literature which is

analysed in stage 2 to generate better alternatives. The alternatives generated are novel and has

Case Studies

120

better sustainability and economics than the base case. Thus, PBS-Intensification framework

provides a systematic approach to synthesize potentially feasible novel and innovative process

options that are better than the existing process or the base case.

As, primary objective of the framework is to systematically generate potentially feasible novel

unit-operations; for an indirect synthesis problem, this case study generates number of novel

unit-operation based flowsheets along with existing solutions present in literature for the

hydrodealkylation of toluene. Alternatives including reactive distillation column at level 3 can

be further analysed with other adjacent unit-operations. A study by Shah et al. (2012) shows that

using reactive distillation column for HDA of toluene at high pressure balances out the effect of

flowsheet simplification with less unit operations by carrying out separations at high pressure

within the RD column. Still, RD column possess the potential for significant reduction and

simplification for HDA reactions that can be carried out at lower pressures.

Figure 6.27: Comparison of performance criteria for alternatives relative to base case

60%

70%

80%

90%

100%

Benzene(kg/Kg main RM)^-1

RM Consumption (Mt/y)

Total cooling energy (M KJ/hr)

Total heating energy (M KJ/hr)RM Cost (M$/kg product)

Carbon footprint (CO2equivalent)

RM (H2) loss (kt/y)

Base Case Alternative 137 Alternative 324

6.3. Case study 3: Production of Bio-Succinic Acid

121


Succinic acid, a four-carbon dicarboxylic acid is one of the most widely used platform chemical

and is a precursor to produce different chemicals with application in food, pharma and various

other chemical sectors (Song et al., 2006). Its demand is rising exponentially and is projected to

reach 247.9 thousand ton (t) by 2021 (Technavio, 2018). Moreover, increasing interest in

sustainability along with dynamic situation of petrochemical industry has created attraction

towards production of bio-chemicals such as succinic acid. Alongside this, the production of bio-

succinic acid is favorable for reduction of carbon footprint since it uses CO2 as an additional

carbon source. It also possesses great potential to replace chemicals like phthalic anhydride and

adipic acid used in plasticizers and polyurethanes – both very big scale bulk chemicals.

Objectives of the case study:

• To identify novel, innovative and intensified process alternatives for the production of

bio-succinic acid utilizing CO2.

In this case study, the base case flowsheet has been synthesized and designed to generate data

required for intensification. The base case is first synthesized in order to cover the wide range of

possibilities in fermentation technique involving different bacterial and yeast strains. Also,

several downstream technologies have been published in literature to obtain pure succinic acid

and thus superstructure based mathematical optimization is performed to identify an optimal

processing route for intensification.

6.3.1. Synthesis and design using superstructure based optimization

The objective of this section to identify an optimal process flowsheet (base case) for the

production of bio-succinic acid using superstructure based optimization approach. The optimal

process flowsheet is then designed and analyzed to identify possible targets of improvement to

be achieved using intensification.

General problem definition

The general synthesis problem for this case study is to find an optimal processing route among

numerous alternatives for production of bio-succinic acid with a purity of at least 99 wt. %

(pharmaceutical grade). Additionally, basic information about succinic acid (product), its raw

material(s), target production, reaction information for example conversion is also collected.

Some of the major producers of bio-succinic acid are Bio Amber Inc (joint venture of DNP Green

Technology and ARD), Reverdia (joint venture of DSM and Roquette), Myriant Corporation and

Succinity (joint venture of BASF and Corbion Purac) (Choi et al., 2015). The production plant

owned by Bio Amber in Sarnia (Canada) has the highest capacity of 30 kilo ton per year (kt/y)

Case Studies

122

(Cavani et al., 2016). Thus, the production target for this case study is set to produce 30 kt/y of

succinic acid. Over the last 30 years, the production of bio-succinic acid has been the subject of

interest to many researchers and industries (Mckinlay et al., 2007; Bechthold et al., 2008). Thus,

there are diverse options proposed in literature in building a process for bio-succinic acid

production. Traditionally, biochemical processes are designed around the best choice of host

organism. But a process is called successful if it can be applied commercially with optimized

capital and operating costs. This includes host micro-organism, biochemical pathway,

fermentation conditions and downstream process. Two distinctive solutions based on the pH of

the fermentation broth have been identified as most common across various research and

patented articles (Table 6.16). Fermentation using bacterial strains are conducted at neutral pH

and are often capable of producing high yield. Though bacterial fermentation for succinic acid

tend to have complex downstream process as it requires splitting of succinate salt to form

succinic acid and inorganic salt coproduct. Another solution focuses on acidophilic yeast

fermentations that operate below the lower pKa value of succinic acid (4.2), that increases the

ratio of succinic acid to succinate salts simplifying the downstream process but do not generally

give substantial yield and productivity. Thus, both type of processes is considered.

Bio-based succinic acid has an attractive theoretical yield of 1.124 g/g of glucose and 1.283 g/g of

glycerol (greater than 1 because of CO2 as extra carbon source), which is the highest among bio-

based chemicals. This leads to an efficient use of feedstocks, less volatility and lower raw material

costs. Thus, based on the attractive theoretical yield, along with Glucose and Glycerol, four

different raw materials (Glucose, Glycerol, Maltose and Sucrose) are considered. As defined in

objective, only those fermentations are considered that uses CO2 as the raw material. This is due

to the following two reasons; it acts as an additional carbon source and secondly a sustainable

solution to reduce carbon footprint. An example of abstract sustainable scheme for production

of bio-succinic acid in presence of bacteria or yeast is shown in Figure 6.28.

Figure 6.28: An example of abstract reaction scheme for bio-succinic acid

The production of bio-succinic acid can be carried out using different feedstocks and several

micro-organisms. A lot of research has been done to identify the best strains giving optimal yield,

high concentration and high productivity. Some of the example of different micro-organisms

used are Actinobacillus succinogenes (Guettler et al., 1999), Saccharomyces cerevisiae (Raab et

al., 2010), Mannheimia succiniciproducens (Lee et al., 2002), Corynebacterium glutamicum

(Okino et al., 2005; Litsanov et al., 2012), Yarrowia lipolytica (Yuzbashev et al., 2010),

Anaerobiospirillum succiniciproducens (Lee et al., 2003), Bacteroides fragilis (Isar et al., 2007),

C6H12O6 + CO2 C4H6O4 + CH3COOH + HCOOH

Formic acid (By product)

Glucose (main raw mateiral)

Carbon dioxide (Additional carbon source)

Succinic acid (main product)

Bacteria or Yeast

Acetic acid (By product)


123

Prevotella ruminicola and Ruminobacter amylophilus (Geuttler, Jain and Soni, 1998), Fibrobacter

succinogenes (Li et al., 2010), Basfia succinoproducens (Scholten et al., 2009) and Escherichia

coli (Donnelly et al., 1998; Sanchez et al., 2005, Jantama et al., 2008). A list of fermentation and

related data based on the type of host micro-organism, raw material, yield, productivity and

broth concentration is collected (Table 6.16). The data mentioned in table is either directly taken

from the mentioned references or is calculated based on the information given. Note that the

list includes only those fermentations that utilizes CO2 as an additional carbon source.

Table 6.16: Fermentation data to produce bio succinic acid using different strains

(FERM-1: Datta, Glassner, Jain and Roy, (1992); FERM-2: Glassner and Datta, (1992); FERM-3:

Rush and Fosmer, (2014); FERM-4: Van De Graaf, Vallianpoer, Fiey, Delattre and Schulten,

(2012); FERM-5: Vemuri et al., 2002; FERM-6: Guettler, Jain and Rumler, (1996); FERM-7: Lee et

al., 2008; FERM-8: & FERM-9: Schroder, Haefner, Abendroth, Hollmann, Raddatz, Ernst and

Gurski, (2014); FERM-10: S. Y. lee, J. W. Lee, Choi and Yi, (2014))

Organism Strain name Ferm Type Carbon

source

Titer

(g/l)

Yield

(g/g)

Productivity

(g/l/h)

Broth

pH

FERM-1 Bacteria A. succinoproducens

ATCC 53488 Batch Glucose 43.5 0.87 1.93 6.10

FERM-2 Bacteria A. succinoproducens

ATCC 53488 Batch Glucose 30.8 0.90 1.10 6.20

FERM-3 Yeast I. orientalis,

13723 Batch Glucose 48.2 0.45 0.97 3.00

FERM-4 Yeast S. cerevisiae,

SUC-297 Fed-batch Glucose 43.0 0.31 0.45 3.00

FERM-5 Bacteria E. coli,

AFP111/pTrc99A- pyc Fed-batch Glucose 99.2 1.10 1.30 6.80

FERM-6 Bacteria A. succinogen, FZ53 Batch Glucose 105.8 0.83 1.36 6.08

FERM-7 Bacteria M. succiniciproducens

LPK7 Fed-batch Glucose 52.4 0.76 1.80 6.50

FERM-8 Bacteria B. succiniciproducens

DD1 Batch Glycerol 36.2 1.26 1.51 6.50

FERM-9 Bacteria B. succiniciproducens

LU 15224 Batch

Glycerol +

Maltose 69.8 1.11 2.91 6.50

FERM-10 Bacteria M. succiniciproducens

PALFK Fed-batch

Sucrose +

Glycerol 78.4 1.07 6.03 6.50

Case Studies

124

Generation of base case flowsheet

There are numerous approaches that can be applied to identify the optimal processing route for

example, literature search, mathematical optimization based approach or ProCAFD (Tula et al.,

2017). Here, the superstructure based mathematical optimization approach has been applied.

Superstructure based process synthesis is an effective way to determine the optimal pathway

from a network of alternatives. This is because using a mathematical optimization approach for

a superstructure, a large number of processing routes as possible alternatives in terms of

processing steps and processing intervals can be generated. It is based on an integrated

framework for synthesis and design of processing networks (Quaglia et al., 2013). The processing

steps are defined as number of steps required to achieve the final result while processing intervals

are defined as alternatives within the processing step. This kind of superstructure representation

has been termed as “Processing Step-Interval Network (PSIN)” (Bertran et al., 2017).

To generate a superstructure, the basic fermentation data is collected as shown in Table 6.16.

Further, there are different purification techniques or technologies available in literature to

obtain succinic acid of a given purity. In principle, the minimum number of separation steps

required to separate N components is N - 1. This is the minimum to separate all the compounds

individually. But, in this case study the main objective is to produce pure succinic acid. Thus, the

logical rules are also followed, for example after fermentation step, the biomass is removed first,

and by-products present in low amount are not recovered.

Many of the various processing steps and intervals are thus identified based on available data

and current technologies reported in the scientific literature (Table 6.17). The superstructure is

set up in Super-O which is an interface to formulate and solve superstructure-based optimization

problems (Bertran et al., 2017). The optimization problem is solved by using solvers from an

external software GAMS (GAMS Development Corporation, 2012), where Super-O is a user

interface to enter required data and information. Processing interval information on raw

materials, main products, side products, reactions, chemical added, utilities and economic data

such as product price, raw material cost and chemical cost has been collected from patents,

published articles and scientific reports, available industrial data and databases. Every interval

in the PSIN representation of the superstructure is modelled with the same set of generic

equations representing a sequence of processing tasks, namely mixing, reaction, waste removal

and product separation, as well as utility consumption. Multiple inlets to and outlets from the

interval are allowed, including recycle streams from downstream intervals and bypasses.

A representation of the generic model is shown in Figure 6.29. Here, “f” represents the

component flow rates at different positions for different parameters while “g” denotes the flow

rate of added/removed component/utility. Further details regarding setting up the problem,

generic mathematical model and entering the required data in Super-O can be read in detail in

article by Bertran et al. (2017).


125

Table 6.17: Processing steps and processing intervals for superstructure

Processing Interval Reference

I. Raw Material

GLU Glucose -

GLY Glycerol -

MAL Maltose -

SUC Sucrose -

II. Fermentation

FERM 1 Fermentation option 1 using bacterial strain and Glucose Datta et al., 1992

FERM 2 Fermentation option 2 using bacterial strain and Glucose Glassner and Datta, 1992

FERM 3 Fermentation option 3 using yeast strain and Glucose Rush and Fosmer, 2014

FERM 4 Fermentation option 4 using yeast strain and Glucose Van De Graaf et al. 2012

FERM 5 Fermentation option 5 using bacterial strain and Glucose Vemuri et al., 2002

FERM 6 Fermentation option 6 using bacterial strain and Glucose Guettler et al., 1996

FERM 7 Fermentation option 7 using bacterial strain and Glucose Lee et al., 2008

FERM 8 Fermentation option 8 using bacterial strain and Glycerol Schroder et al., 2014

FERM 9 Fermentation option 9 using bacterial strain and Glycerol + Maltose Schroder et al., 2014

FERM 10 Fermentation option 10 using bacterial strain and Sucrose + Glycerol Lee et al., 2014

III. Biomass Removal

BIOR-MFLT Biomass removal using microfiltration Vogel and Todaro, 1996; Hong et al., 2009; Soper et al., 2013

BIOR-ULFT Biomass removal using ultrafiltration

BIOR-CENT Biomass removal using centrifugation

IV. Concentration Pre-Isolation

CPRI-DSTL Concentrating the broth using distillation Bernier et al., 2013

CPRI-EVAP Concentrating the broth using evaporation Gerberding et al., 2012

CPRI-EXTR Concentrating the broth using extraction King and Poole, 1995

CPRI-PVAP Concentrating the broth using pervaporation Van Baelen et al., 2005

BYPASS Concentration pre-isolation step is bypassed -

V. Isolation

SEP-CSSP Isolation of succinic acid from succinate salt containing calcium Datta et al., 1992

SEP-IEXC Isolation of succinic acid from succinate salt using ion-exchange Gerberding et al., 2012

SEP-SUSP Isolation of succinic acid from succinate salt using methanol Yedur et al., 2001

SEP-REXT Isolation of succinic acid from succinate salt using reactive extraction Vaswani, 2010

SEP-EDLS Isolation of succinic acid from succinate salt using Electrodialysis Glassner and Datta, 1992

BYPASS Isolation step is bypassed -

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126

VI. Impurities Removal

IMPR-IEXC Removal of soluble impurities using Ion exchange Schroder et al., 2014

IMPR-CTRT Removal of soluble impurities using carbon treatment Choi et al., 2016

IMPR-NFLT Removal of soluble impurities using Nano-filtration Gerberding et al., 2012

BYPASS Impurities removal is bypassed -

VII. Concentration Post-Isolation

CPSI-DSTL Concentrating the broth using distillation Bernier et al., 2013

CPSI-EVAP Concentrating the broth using evaporation Gerberding et al., 2012

CPSI-EXTR Concentrating the broth using extraction King and Poole, 1995

CPSI-PVAP Concentrating the broth using pervaporation Van Baelen et al., 2005

BYPASS Concentration post-isolation step is bypassed -

VIII: Purification

PUR-ECRY Purification of succinic acid using evaporative crystallization Graaf et al., 2011

PUR-SCRY Purification of succinic acid using solvent crystallization Yedur et al., 2001

PUR-CCRY Purification of succinic acid using cooling crystallization Choi et al., 2016

IX. Drying

DRYING Purification of succinic acid by removing remaining impurities -

X. Product

SUC ACD Pharmaceutical grade succinic acid (>99 wt. %) -

Figure 6.29: Generic processing interval scheme (Bertran et al., 2017)

The economic data for product price, raw material costs, chemical costs and utility costs (Tan et

al., 2017; Biorefinery database (Bertran et al., 2017); ICIS price reports, (2016); Ycharts, (2014);


127

Costs of doing business in Thailand, (2014); Intratec utility pricing, (2016); Industrial Price

Comparison - Rocky Mountain Power, (2018); Harrison, Todd P, Todd PW, Rudge, Petrides,

(2015)) is given in Appendix G.1.

The superstructure optimization is performed for 3 different scenarios based on location and

objective function. Overall objective remains same for all the scenarios which is to maximize the

profit. The 3 different scenarios are explained as follows:

• Scenario 1: The plant location is set to USA and the objective function is based upon

sales of product

• Scenario 2: The plant location is same as scenario 1 i.e. USA, but an additional effect of

operating cost is added to the objective function

• Scenario 3: Same as scenario 2 except the plant location has been changed to Thailand

The superstructure describing the network of configurations for different processing routes has

8 processing steps and 33 processing intervals excluding raw material and product steps. The

PSIN representation of alternatives containing the processing intervals, raw materials and

products is shown in Figure 6.30.

An optimization problem is solved for each scenario using the same generic model. The statistics

of the optimization problem for bio succinic acid is shown in Table 6.18.

Table 6.18: Statistics for the optimization problem for bio succinic acid production

Superstructure

No. of feed (NF) 4

No. of product (NP) 1

No. of processing steps (NS) 8

No. of intervals NI (excluding NF and NP) 33

Model and Solver

No. of equations (NEQ) 989,003

No. of variables (NV) 973,451

No. of discrete variables (NDV) 164

Problem type MILP

Solver CPLEX

The results in terms of objective function for 3 different scenarios is shown in Table 6.19 and

optimal topology is shown in Figure 6.30 denoted with different colors. It is observed that, the

optimal topology for scenario 1 and 2 is coming out to be the same, while in scenario 3, the raw

material and the fermentation has changed owing to one of the major reasons being lower prices

of Glycerol as compared to the Glucose. The objective function depends on the product sales

(SPROD), raw material (CRAW), chemical (CC) and utility (CU) costs (scenario 2 and 3).

Cas

e S

tud

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12

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Fig

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129

The sensitivity analysis on the variation of prices is also performed. From this analysis, ±10%

fluctuation in the product price brings ±14.3 to ±18.3% change in the objective function for all

the scenarios. Similarly, a ±10% fluctuation in the raw material and utility prices brings ±1.3 to

±3.2% and ±0.7 to ±1.2% changes respectively, in the objective function for all the scenarios. In

all the above cases, the optimal processing route (flowsheet) remains unchanged. The optimal

processing route identified for different scenarios is as follows:

• Scenario 1: GLU → FERM 5 → BIOR-CENT → CPRI-DSTL → BYPASS → IMPR-CTRT →

BYPASS → PUR-CCRY → DRYING → SUC ACD

• Scenario 2: GLU → FERM 5 → BIOR-CENT → CPRI-DSTL → BYPASS → IMPR-CTRT →

BYPASS → PUR-CCRY → DRYING → SUC ACD

• Scenario 3: GLY+MAL → FERM 9 → BIOR-CENT → CPRI-DSTL → BYPASS → IMPR-

CTRT → BYPASS → PUR-CCRY → DRYING → SUC ACD

Table 6.19: Results of the superstructure based mathematical optimization

Scenario 1 Scenario 2 Scenario 3

Location USA USA Thailand

Objective function SPROD - CRAW - CC SPROD - CRAW - CC - CU SPROD - CRAW - CC - CU

Total product sale (M$/y) 70.02 70.02 70.02

Raw material cost (M$/y) 12.19 12.19 6.44

Chemicals cost (M$/y) 15.27 15.27 12.66

Utilities cost (M$/y) - 4.33 2.31

Execution time (seconds) 2.50 2.52 2.56

Objective function (M$/y) 42.56 38.23 48.61

The optimal processing routes identified for all 3 different scenarios are novel processing routes.

Also, as shown in Figure 6.30, along with optimal processing routes, 5 other existing routes in

literature are also identified. These existing routes are denoted with different colors in the PSIN

representation.

• Existing alternative 1 (Datta, Glassner, Jain and Roy, 1992): GLU → FERM 1 → BIOR-

MFLT→ BYPASS → SEP-CSSP → BYPASS → CPSI-EVAP→ PUR-ECRY → DRYING →

SUC ACD

• Existing alternative 2 (Glassner and Datta, 1992): GLU → FERM 2 → BIOR-MFLT→

BYPASS → SEP-EDLS→ BYPASS → BYPASS→ PUR-CCRY → DRYING → SUC ACD

• Existing alternative 3 (Van De Graaf, Vallianpoer, Fiey, Delattre and Schulten,

2012): GLU → FERM 4 → BIOR-MFLT→ BYPASS → SEP-IEXC → BYPASS → CPSI-

EVAP→ PUR-ECRY → DRYING → SUC ACD

Case Studies

130

• Existing alternative 4 (Vaswani, 2010): GLU → FERM 7 → BIOR-UFLT→ BYPASS →

SEP-REXT → BYPASS → CPSI-DSTL→ PUR-CCRY → DRYING → SUC ACD

• Existing alternative 5 (Schroder, Haefner, Abendroth, Hollmann, Raddatz, Ernst

and Gurski, 2014): GLY+MAL → FERM 9 → BIOR-MFLT→ BYPASS → SEP-IEXC→

BYPASS → CPSI-EVAP→ PUR-CCRY → DRYING → SUC ACD

The optimal processing route from scenario 1 and 2 is considered for further analysis in stage 2

and 3. The process flowsheet for the selected alternative (base case flowsheet) is shown in Figure

6.31. The first step is fermentation where non-condensable gases are removed from the top of

fermenter followed by microfiltration to separate the biomass from the culture broth. Then the

cell free broth is distilled in order to concentrate the solution and facilitate crystallization. The

color of the culture broth caused by certain impurities is removed by activated carbon treatment.

Then the feed is sent to crystallizer where cooling crystallization is performed by lowering the

pH followed by drying of the pure succinic acid crystals to remove any remaining water or

impurities.

Figure 6.31: Process flowsheet of selected alternative for bio-succinic acid

Base case design and analysis

The base case is rigorously simulated using PRO/IITM and the UNIQUAC model is used for the

liquid activity coefficients. Optimized UNIQUAC parameters for the calculation of water-acetic

acid VLE system is retrieved from Pirola et al. (2014). The solubility of succinic acid in water is

shown in solubility curve in Figure 6.32 (Sundaram, 2015). The recovery of succinic acid at a

particular temperature is determined using this curve. Then, the detailed mass and energy

balance data along with number of streams, unit operations data is extracted to carry out analysis

in the next step. An overview of the key simulation results is given in Table 6.20.

FERMENTATIONBIOMASS

REMOVALRECOVERY AND PURIFICATION

OP 06

OP 22

Fermentation

Biomass

Water, Acetic acid, EthanolNon cond gases

Glucose, Water,

Sol. solids

Carbon dioxide Water

Succinic Acid crystals

Waste waterCentrifugation

DistillationActivated carbon

treatment

Act. carbon

Crystallization

Drying

Spent carbon,

Sol. solids


131

Figure 6.32: Solubility curve for succinic acid in water (Sundaram, 2015)

Table 6.20: Key results from rigorous simulation of Base case

Parameter Value

Succinic acid product (kg/h) 3750.40

Succinic acid purity (wt. %) > 99

Total energy supplied (MJ/h) 73240.53

Total energy withdrawn (MJ/h) 68875.03

Further, the detailed analysis in terms of process economics, sustainability and life cycle

assessment is performed. In house tools ECON, SustainPro and LCSoft are used to carry out the

respective analysis. The main results from sustainability analysis performed using SustainPro are

shown in Table 6.21. In Figure 6.31, the most critical open paths (OP) identified for potential

improvements are highlighted.

Table 6.21: List of critical paths with highest potential for improvement (MVA-Material vale added, EWC-Energy and waste cost, TVA-Total value added)

Path Compound Flowrate MVA EWC TVA

kg/hr 103 $/yr 103 $/yr 103 $/yr

OP 06 Water 19508.4 - 449.4 -

OP 22 Succinic acid 662.4 -1493.1 611.0 -2104.0

In OP 06, which follows the compound water is present in excess in the system has a high energy

waste cost (EWC). The unit operation mainly belonging to this path is distillation column. This

translates to loss of energy in the open path and thus potential to recover or reduce energy

consumption during distillation operation whose objective is to remove unwanted byproducts

0

100

200

300

400

500

600

700

800

900

1000

1100

0 10 20 30 40 50 60 70 80 90 100 110 120 130

So

lub

ilit

y (

g/l

of

wa

ter)

Temperature (OC)

Case Studies

132

(ethanol and acetic acid) and concentrate the broth. OP 22 follows the main product succinic

acid path ending at crystallizer outlet and has high negative value of MVA and positive value of

TVA. This translates to loss of product and potential for improvement in recovery of product.

As can be seen in Figure 6.33 a), LCA analysis (using LCSoft) shows that the carbon footprint is

highest for the reboiler of the distillation column and as expected, economic analysis performed

using ECON (Figure 6.33 b)) shows that the utility cost is highest for the same reboiler.

Figure 6.33: a) LCA analysis (carbon footprint); b) Utility cost distribution

6.3.2. Application of extended phenomena based synthesis method

This section present results for the application of extended phenomena-based synthesis method

on bio-succinic acid. This extended method is developed by Garg et al. (2019) which is based on

the previous work from Babi et al. (2015) and Lutze et al. (2013). A brief introduction of these

methodologies and extensions are given in chapter 1.

The extended framework (Garg et al., 2019) consists of 3 steps, where in first step, existing process

flowsheet is translated to task and phenomena based flowsheet followed by generation of

intensified flowsheet alternatives. The generated alternatives are then analyzed and screened

according to the pre-defined performance criteria. Application of these steps on the optimal

process flowsheet identified for bio-succinic acid generates 3 intensified flowsheet alternatives.

The task based superstructure showing the base case and alternatives is shown in Figure 6.34.

Three intensified flowsheet alternatives are explained as follows:

• Flowsheet alternative 1: The merging of reaction and separation tasks is considered to

perform these two tasks simultaneously. Thus, in this alternative, starting with the first

task of reaction, the second task, cell removal or clarification of broth are combined. The

task based flowsheet for alternative 1 is highlighted with blue color in Figure 6.34. The

task based flowsheet is translated to unit operation based flowsheet where, the combined

reaction and separation task are translated to membrane reactor (bio). In this unit

0

1

2

3

4

Car

bo

n f

oo

tpri

nt,

CO

2e

q.

EquipmentUnit Operation

Comp. HEX (Hot Utl.) HEX (Cold Utl.) T1-cond T1-reb

0

15

30

45

60

75

Uu

tilit

y co

st, %

EquipmentUnit Operation

Comp. HEX (Hot Utl.) HEX (Cold Utl.) T1-cond T1-reb


133

operation, the fermentation broth is clarified i.e. the reaction product is removed

continuously and the cell culture remains in the membrane bioreactor leading to

increased cell concentration and product yield, which is also observed by Wang et al.

(2014). According to Wang et al. (2014), using membrane based fermentation and

separation system the problem of succinic acid inhibition is alleviated by removing acids

and thus yielding better results. The unit operation based flowsheet for alternative 1 is

shown in Figure 6.35.

(A – Oxygen, B – Carbon dioxide, C – Ammonia, D – Ethanol, E – Water, F – Acetic acid, G –

Succinic acid, H- Glucose, I – Soluble solids, J – Biomass)

Figure 6.34: Task based superstructure for the production of bio-succinic acid

• Flowsheet alternative 2: In this alternative again, the merging of tasks is considered for

the last two separation tasks and is found to be feasible as both the separation tasks share

the similar set of phenomena with liquid-solid phase. Therefore, merging of S-Task 4 and

S-Task 5 (Figure 6.36) is done to generate a new feasible combination. Here, performance

R-Task 1 S-Task 1 S-Task 2 S-Task 3 S-Task 4 S-Task 5 S-Task 6

React. Sep.. J(DEFGHI) Sep.. D(EFGHI) Sep. E(FGHI) Sep. F(GHI) Sep. G(HI) Sep. H(I)

Sep.. E(DFGHI) Sep. D(FGHI) Sep. D(EHI) Sep. E(HI) Sep. E(I)

React.+Sep.

J(DEFGH)ISep.. F(DEGHI) Sep. G(DEHI) Sep. G(HI) Sep. H(GI) Sep. G(I)

React.+Sep.

J(DEFG)HISep. G(DEFHI) Sep. F(DEHI) Sep. E(HI) Sep. H(EI) Sep. …………….

React.+Sep.

J(DEF)GHISep. DE(FGHI) Sep. ……………. Sep. …………… Sep. GH(I)

React.+Sep.

J(DE)FGHISep. DEF(GHI) Sep. EF(GHI) Sep. EH(I)

React.+Sep.

J(DE)FGHISep. DEFG(HI) Sep. DF(GHI) Sep. FGH(I) Sep. …………….

React.+Sep.

J(D)EFGHISep. DEFGH(I) Sep. GD(EHI) Sep. …………….

React.+Sep.

…………….Sep. EF(DGHI) Sep. FD(EHI) Sep. H(I) Sep. …………….

Sep. …………… Sep. ……………. Sep. …………….

Base case Sep. DF(EGHI) Sep. EFG(HI)

Alternative 1 Sep. ……………. Sep. DFG(HI) Sep.. F(G)

Alternative 2 Sep.. D(EFGH) Sep. ……………. Sep. …………….

Alternative 3 Sep.. D(EFG) Sep.. E(FGH)

Sep. ……………. Sep.. E(FG)

Sep. …………….

React.

React.+Sep. (J)DEFGHI

Sep.. J(DEFGHI)

Sep. DF(EGHI)

Sep. I(EGH)

Sep.. G(EH)

Sep.. EG(EH)

Sep.. G(E)

Case Studies

134

of the task is enhanced by PS(LL) PBB from the list of phenomena. The task based

flowsheet for alternative 2 is highlighted purple color in Figure 6.34. The combination of

separation tasks is then translated to membrane crystallizer using a reverse osmosis

membrane (Kuhn et al., 2009). Kuhn et al. (2009) showed that the crystallization

performance of organic acids can be significantly improved using RO membranes. The

corresponding unit operation based flowsheet for this alternative is shown in Figure 6.36.

• Flowsheet alternative 3: This alternative is combination of alternative 1 and 2, where

combination of reaction and adjacent separation task, two last separation task is

considered to generate new feasible alternatives. The task based flowsheet is highlighted

with red color in Figure 6.34 and corresponding unit-operation based flowsheet is shown

in Figure 6.37.

Figure 6.35: Alternative 1 generated using extended phenomena based synthesis


Fermentation


Glucose, Water,

Sol. solids

Carbon dioxide Water

Succinic Acid crystals

Waste water


treatment

Act. carbon

Crystallization

Drying

Spent carbon,

Sol. solids

Membrane

bio-reactor

Fermentation

Biomass


Glucose, Water,

Sol. solids

Carbon dioxide

Succinic Acid

crystals

Waste water

Centrifugation


treatment

Act. carbon

Membrane

Crystallization

Spent carbon,

Sol. solids


135





The synthesis problem definition is to produce bio-succinic acid from glucose and carbon

dioxide with a purity of at least 99 wt. %. The target annual production of bio-succinic

acid is set to be same as section 6.3.1 i.e. 30 kt/y.


The problem type identified is indirect synthesis as the flowsheet synthesized in

section 6.3.1 is considered as the base case for this application.


The optimal processing route from section 6.3.1 consists of fermentation pathway

from Vemuri et al. (2002). The fermentation operates at 37 OC and normal pressure.

The fermentation feed (similar to the base case) consists of glucose and CO2 along

with other necessary components and nutrients. The fermentation reaction in

presence of E. coli, AFP111/pTrc99A- pyc strain does not go to full completion i.e. all

main raw material does not get consumed; therefore, the fermenter outlet contains a

mixture of raw materials, products and byproducts.



The fermentation reaction takes place at moderate conditions where the yield of main

product, succinic acid is 1.1 g/g of glucose (main raw material). The concentration of

the product at the outlet is 99.2 g/l with a productivity of 1.3 g/l/h. The strain used

for fermentation is E. coli, AFP111/pTrc99A- pyc. The fermentation releases energy

thus, is slightly exothermic in nature.

Fermentation


Glucose, Water,

Sol. solids

Carbon dioxide

Succinic Acid

crystals

Waste water


treatment

Act. carbon

Membrane

Crystallization

Spent carbon,

Sol. solids

Membrane

bio-reactor

Case Studies

136


The outlet of the fermenter consists of several components that are categorized

further for the simplification of the problem. The outlet of fermenter includes

product succinic acid, biomass, impurities in form of soluble solids, water, unreacted

raw material i.e. glucose, by products ethanol and acetic acid. The key components

considered for the mixture analysis are succinic acid, water, acetic acid and ethanol.

The components present in the system are annotated as: A – Oxygen, B – Carbon

dioxide, C – Ammonia, D – Ethanol, E – Water, F – Acetic acid, G – Succinic acid, H-

Glucose, I – Soluble solids, J – Biomass.


The list of pure component properties for selected components is retrieved from

ICAS database (Gani et al. 1997; Gani 2002) and literature search. The retrieved

list is shown in Table 6.22. The binary ratio matrix generated for selected set of

pure component properties is shown in Table 6.23.

Table 6.22: Pure component properties data for compounds involved in the problem

Property UOM Oxygen

(A) Carbon

dioxide (B) Ammonia

(C) Ethanol

(D) Water

(E) Acetic

acid (F) Succinic acid (G)

MW (g/mol) 31.99 44.01 17.031 46.069 18.02 60.05 118.09

ω - 0.02 0.22 0.25 0.65 0.3449 0.47 0.99

Tc (K) 154.58 304.21 405.65 513.92 647.13 591.95 806.00

Pc (atm) 49.77 72.86 111.33 60.68 217.67 57.10 46.48

Zc - 0.29 0.27 0.24 0.24 0.229 0.211 0.22

Vc (m3/kmol) 0.07 0.09 0.07 0.2 0.1 0.17 0.32

Tb (K) 90.19 194.7 239.72 351.44 373.15 391.05 591.00

dm (Debye) 0.00 0.00 1.47 1.69 1.84 1.74 2.20

rg (Å) 0.68 1.04 0.85 2.26 0.62 2.61 4.16

Tm (K) 54.36 216.58 195.41 159.05 273.15 289.81 460.65

Ttp (K) 54.36 216.58 195.41 159.05 273.16 289.81 460.65

Ptp (atm) 1.5E-03 5.12 0.06 4.8E-09 6.03E-03 1.2E-02 8.7E-03

Hf (kJ/kmol) 0.00 -3.93E+05 -4.5E+04 2.3E+05 -2.4E+05 -4.3E+05 -8.2E+05

Gf (kJ/kmol) 0.00 -3.94E+05 -1.6E+04 1.6E+05 -2.2E+05 -3.8E+05 -6.9E-05

SIG (kJ/kmol·K) 205.04 213.68 192.66 281 1.8E+02 2.8E+02 403.4

Hfus (kJ/kmol) 4.4E+02 9.01E+03 5657 4930 6.0E+03 1.1E+04 5.3E+04

Hcomb (kJ/kmol) 0.00 0.00 -3.1E+05 -1.2E+06 0.00 -8.2E+05 -1.3E+06

δ (√kJ/m3) 8.18 14.56 29.23 26.13 47.81 19.01 29.34

Vvw (m3/kmol) 0.013 0.02 0.014 0.03 0.012 0.03 0.06

Avw (m2/kmol) 2.3E+08 3.2E+08 2.4E+08 4.9E+08 2.2E+08 5.1E+08 8.8E+08

Pvap (Pa) 4.3E+07 5.7E+06 8.6E+05 7.9E+03 3.1E+03 2.0E+03 1.5E-05


137


Binary pair/Property Tb Tm δ Vvw rg MW

Oxygen (A)

Carbon dioxide (B)

2.16 3.98 1.78 1.52 1.53 1.38

Ammonia (C)

2.66 3.59 3.57 1.06 1.25 1.88

Water (E)

4.14 5.02 5.84 1.05 1.11 1.78

Ethanol (D)

3.90 2.93 3.19 2.45 3.32 1.44

Acetic Acid (F)

4.34 5.33 2.32 2.56 3.84 1.88

Succinic Acid (G)

6.55 8.47 3.59 4.58 6.12 3.69

Carbon dioxide (B)

Ammonia (C)

1.23 1.11 2.01 1.43 1.22 2.58

Water (E)

1.92 1.26 3.28 1.59 1.69 2.44

Ethanol (D)

1.81 1.36 1.79 1.62 2.17 1.05

Acetic Acid (F)

2.01 1.34 1.31 1.69 2.51 1.36

Succinic Acid (G)

3.04 2.13 2.01 3.02 4.00 2.68

Ammonia (C)

Water (E)

1.56 1.40 1.64 1.12 1.39 1.06

Ethanol (D)

1.47 1.23 1.12 2.31 2.65 2.71

Acetic Acid (F)

1.63 1.48 1.54 2.41 3.06 3.53

Succinic Acid (G)

2.47 2.36 1.00 4.31 4.88 6.93

Water (E)

Ethanol (D)

1.06 1.72 1.83 2.58 3.67 2.56

Acetic Acid (F)

1.05 1.06 2.52 2.69 4.24 3.33

Succinic Acid (G)

1.58 1.69 1.63 4.81 6.76 6.56

Ethanol (D)

Acetic Acid (F)

1.11 1.82 1.37 1.04 1.16 1.30

Succinic Acid (G)

1.68 2.90 1.12 1.87 1.84 2.56

Acetic Acid (F)

Succinic Acid (G)

1.51 1.59 1.54 1.79 1.59 1.97


Non condensable gases as in the base case are considered to be removed from

fermenter itself. Further, insoluble solids like biomass are removed immediately

after the fermenter. Further, following analysis is performed for the mixture from

the reactor outlet:

▪ The mixture state or phase (after fermentation) – Liquid

Case Studies

138

▪ State of pure components (fermentation outlet) at the mixture conditions

and ambient conditions.

- Mixture conditions: Ethanol, Water, Acetic acid, Succinic acid - Liquid

- Ambient conditions

Ethanol, Water, Acetic acid – Liquid, Succinic acid - Solid

▪ Azeotrope – Water and ethanol


Additionally, it has also been identified that acetic acid and water system does

not make an azeotrope at normal conditions but shows a tangent pinch at water

side (Pirola et al., 2014) as shown in the Appendix G.2. Thus, the separation of

this mixture using simple distillation technique to recover pure components is

not technically feasible. Also, succinic acid is highly soluble in water as shown in

Figure 6.32 and solubility increases with increase in temperature.


The objective of stage II is to analyze the selected base case synthesized in section 6.3.1. The base

case flowsheet for production of bio succinic acid shown in Figure 6.31.

• Step 3: Generation of task and phenomena based flowsheet

- S3.1. Task based flowsheet

The base case flowsheet shown in Figure 6.31 is translated to task based flowsheet by

identifying unit-operations involved in the process. The unit-operations involved are

fermenter, filtration, distillation column, adsorption column, crystallizer and dryer.

The task based flowsheet is shown in Figure 6.38.

Figure 6.38: Task based flowsheet for the base case

- S3.2. Phenomena based flowsheet

The phenomena based flowsheet is shown in Figure 6.39. An initial list of phenomena

obtained from the phenomena-based flowsheet consists of following PBBs: M, 2phM,

R(L), ES(C), ES(H), PC(VL), PC(LS), PT(VL), PT(LS), PS(VL), PS(LS).

Reaction task

Glucose + Water

CO2

Spent C + Soluble solids

EtOH+Water+AcA

Biomass

Separation task Separation task

Separation task

Non-Condensable gases

Glucose+Water+Succinic Acid+

Acetic acid

Separation task

Water

Separation task

Succinic Acid

Act. carbon


139

Figure 6.39: Phenomena based flowsheet for the base case

• Step 4: Identification of additional task and phenomena

- S4.1. Process hotspots and design targets

The process hotspots are identified based on economic, sustainability and life cycle

analysis in section 6.3.1. Further using the Appendix B, following design targets are

desired:

o Reduce energy consumption

o Reduce utility cost

o Improvement in LCA/sustainability indictors

o Unit operation reduction

o Product purity (to be kept at least as base case)

o Production target (to be kept at least as base case)

o Waste minimization

- S4.2. Additional task and phenomena

A list of additional task and phenomena are identified based on the process hotspots

using algorithm A2.3 and knowledge base KB2.2. These are shown in Table 6.24.

Table 6.24: Additional task and phenomena to overcome identified process hotspots

Process Hotspot

Main task Binary

pair

Pair or Reaction

phase

Alternative Task

MSA Principle PBBs

High energy consumption/demand

Separation E/G L Separation Y PC(LL), PT(LL), PS(LL)

Separation E/G L Separation Y PC(LS), PS(LS)

Separation E/G L Separation Y 2phM, PC(VL), PT(VL), PS(VL), ES(C). ES(H)

Separation E/G L Separation N 2phM, PC(VL), PT(VL), PS(VL), ES(C). ES(H)

Separation E/G L Separation N PT(MVL), PS(VL)

Separation E/G L Separation N PT(MLL), PS(LL)

M, 2phM, R(L)

Glucose + Water

CO2

Spent C + Soluble solids

EtOH+Water+AcA

Biomass

M, PC(LS), PS(LS)M, 2phM, ES(C),

ES(H), PC(VL), PT(VL), PS(VL)

M, PC(LS), PS(LS)

Non-Condensable gases

Glucose+Water+Succinic Acid+

Acetic acid

M, ES(C), PC(LS), PT(LS)

Water

M, ES(H), PT(VL), PS(VL)

Succinic Acid

Act. carbon

Case Studies

140




algorithm A3.1. Compounds like oxygen, unreacted carbon dioxide and ammonia are

non-condensable gases that are removed from fermenter only and thus are not

considered for the mathematical combinatorial superstructure. Raw materials must react

in presence of bacteria for a fermentation to take place and produce products, thus the

first task is the reaction task. The first separation task after fermentation is generally

broth clarification in bio processes i.e. biomass removal. So, to avoid any separation

problems, the first separation task is fixed as biomass (J) removal. Also, the impurities as

soluble solids are considered to be removed after mass removal. Glucose is present as a

solution in water and is considered to be removed along with water. Thus, based on these

considerations, the mathematical combinatorial superstructure is generated as shown in

Figure 6.40. The number of possible flowsheet alternatives at this step are 1080.







Binary

pair

C + A → D + B, 2D → E + A

(---ABCDE---)

Ethanol/Water

(D/E)

Ethanol/Acetic acid

(D/F)

Ethanol/Succinic acid

(D/G)

Principle

PBBs

2phM, R(L) PT(MVL), PS(VL) 2phM, PC(VL), PT(VL),

PS(VL), ES(C), ES(H) PT(MVL), PS(VL)

PT(MLL), PS(LL) PT(LS), PS(LS), ES(C/H) PT(MLL), PS(LL)

PT(LS), PS(LS), ES(C/H) PT(VL), PS(VL)




Binary

pair

Water/Acetic acid

(E/F)

Water/Succinic acid

(E/G)

Acetic acid/Succinic

acid (F/G)

Principle

PBBs


PT(MLL), PS(LL) PT(MLL), PS(LL) PT(MLL), PS(LL)





PT(VL), PS(VL) PT(VL), PS(VL)

PT(LS), PS(LS), ES(C/H) PT(LS), PS(LS), ES(C/H)

PC(LL), PT(LL), PS(LL)*


PS(VL)*, ES(C). ES(H)

PC(LS), PS(LS)*


141


Fermentation

--ABC/DEFGIJ--D/EFG

D/FEG

DE/GF

ED/FG

D/GEF

DE/FG

ED/GF

DF/EG

FD/GE

DG/EF

DF/GE

FD/EG

DG/FE

GD/EF

GD/FE

E/DFG

E/FGD

E/GDF

F/DEG

F/EGD

F/GED

G/DEF

G/EFD

G/FDE

E/FG

E/GF

F/EG

F/GE

G/EF

G/FE

D/FG

D/GF

F/DG

F/GD

G/DF

G/FD

D/EG

D/GE

E/DG

E/GD

G/DE

G/ED

D/EG

D/GE

E/DG

E/GD

G/DE

G/ED

F/G

E/G

E/F

D/G

D/F

D/E

F/G

E/G

D/G

D/E

E/G

D/G

D/E

F/G

D/F

E/G

D/G

F/E

DEFGI/J

Case Studies

142

Ethanol and acetic acid are unwanted by products and are not considered for recovery as

pure components. Thus, being difficult separating binary, the phenomena for the same

are not considered. The phenomena for removal of I and J are kept same as the base case.


The list of feasible SPBs is generated using the PBBs identified in previous steps. The

total number of PBBs identified are M, 2phM, R(L), ES(C), ES(H), PC(VL), PC(LL),

PC(LS), PT(VL), PT(LS), PT(MVL), PT(MLL), PT(LL), PS(LL), PS(VL), PS(LS), D - 17.



Table 6.26: Operating window for all identified PBBs


M Tlow=159.05K (lowest melter)

Thigh=591.00K (highest boiler)

2phM Tlow=159.05K (lowest melter)

Thigh=591.00 (highest boiler)

R(L)

P= 40 bar (reaction pressure from literature)

Tlow=273.15K (lowest melter)

Thigh=310.15K (T for fermentation according to base case)

PC(VL) V-L present (also liquid separating agent)

PC(LL) L-L present (liquid separating agent)

PC(LS) L-S present (can be solid separating agent)

PT(VL) Tlow=351.35 K (lowest boiling azeotrope)

Thigh=591.00K (highest boiler)

PT(LS) Tlow=159.05K (lowest melter)

Thigh=460.65K (highest melter)



PS(LL) L-L present

PS(VL) V-L present


PS(LL) L-L present (liquid separating agent)

ES(H) -

ES(C) -

D -


143




PBBs using adjacency matrix and SPB building blocks is shown in Table 6.27. The

combination rules are applied together for principle PBBs with MSA’s.



SPB.1 M Mixing

SPB.2 M=2phM Mixing

SPB.3 M=R(L) Mixing+Reaction



SPB.6 M=R(L)=ES(H) Mixing+Reaction+Heating

SPB.7 M=R(L)=ES(C) Mixing+Reaction+Cooling

SPB.8 M=2phM=R(L) Mixing+Reaction



SPB.11 M=2phM=R(L)=ES(C) Mixing+Reaction+Cooling

SPB.12 M=2phM=R(L)=ES(H) Mixing+Reaction+Heating


SPB.14 M=2phM=R(L)=PC(VL)=PT(VL) Mixing+Reaction+ Phase creation



SPB.17 M=2phM=R(L)=ES(C)=PC(VL)=PT(VL) Mixing+Reaction+Cooling+ Phase creation

SPB.18 M=2phM=R(L)=ES(H)=PC(VL)=PT(VL) Mixing+Reaction+Heating+ Phase creation





SPB.23 M=R(L)=ES(H)=PT(VL)=PS(VL) Mixing+Reaction+Heating+Separation

SPB.24 M=R(L)=ES(C)=PT(VL)=PS(VL) Mixing+Reaction+Cooling+Separation




SPB.28 M=2phM=R(L)=PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Separation

SPB.29 M=2phM =R(L)=ES(H) =PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Heating+Separation

SPB.30 M=2phM=R(L)=ES(C)=PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Cooling+Separation




SPB.34 M=R(L)=PC(LS)=PS(LS)* Mixing+Reaction+Separation

Case Studies

144



SPB.37 M=ES(H)=R(L)=PC(LS)=PS(LS)* Mixing+Heating+Reaction+Separation

SPB.38 M=ES(C)=R(L)=PC(LS)=PS(LS)* Mixing+Cooling+Heating+Separation




SPB.42 M=2phM=PC(VL)=PT(VL)=PS(VL)* Mixing+Separation

SPB.43 M=2phM=ES(H)= PC(VL)=PT(VL)=PS(VL)* Mixing+Heating+Separation

SPB.44 M=2phM=ES(C) =PC(VL)=PT(VL)=PS(VL)* Mixing+Cooling+Separation

SPB.45 M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL)* Mixing+Reaction+Separation

SPB.46 M=2phM =R(V)=ES(H) =PC(VL)=PT(VL)=PS(VL)* Mixing+Reaction+Heating+Separation

SPB.47 M=2phM=R(V)=ES(C)=PC(VL)=PT(VL)=PS(VL)* Mixing+Reaction+Cooling+Separation

SPB.48 M=PC(LL)=PT(LL)=PS(LL)* Mixing+Separation

SPB.49 M=ES(H)= PC(LL)=PT(LL)=PS(LL)* Mixing+Heating+Separation

SPB.50 M=ES(C) =PC(LL)=PT(LL)=PS(LL)* Mixing+Cooling+Separation




mathematical combinatorial superstructure (Figure 6.40) is combined with principle

PBBs from Table 6.25 to generate phenomena based superstructure. The possible outlet

phase is also identified and marked. In this case study, ethanol (D) and acetic acid (F) are

unwanted byproducts and are thus considered to be removed prior to removal of water.

This is also because of the fact that, succinic acid is highly soluble in water and thus other

impurities need to be removed prior to the removal of water in order to recover pure

crystalline succinic acid. It also makes necessary for the last task to contain ‘PT(LS)’

phenomena (indicated with the dash line). The phenomena based superstructure thus

generated is shown in Figure 6.41. The repetitive PBBs are marked in green color.


- S9.1. Reduction of alternatives

The reduction of alternatives is performed at 3 different levels under feasibility rules

and logical rules.

Feasibility rules


rules at two different levels as mentioned in algorithm A3.4. Following the

algorithm, the outlet of the reactor is in solid-liquid phase with biomass which is

the first separation task and s taken into consideration. Non-condensable gases

are considered to be removed from the fermenter itself.


145


F/EG

PT(MLL), PS(LL)PT(MVL), PS(VL)

F/GE

PT(VL), PS(VL)PT(MLL), PS(LL)PT(MVL), PS(VL)



D/EG



D/GE




--DE/G--E/G—EF/G--



PT(LS), PS(LS), ES(C/H)2phM, PC(VL), PT(VL), PS(VL)*, ES(C), ES(H)

PC(LL), PT(LL), PS(LL)*PC(LS), PS(LS)*

E/G





D/EFG



D/FGE



D/GEF




F/DEG



F/EGD


F/GDE




L-LV-LL-S

V-LL-LV-LV-L

L-S

V-LL-LV-LV-L

L-S

L

Separation task - 2 Separation task - 3 Separation task - 4

2phM, R(L)

Fermentation

--DEFGIJ--

Reaction task

PC(LS), PS(LS)

DEFGI/J

Separation task - 1

DF/GE




FD/GE




DF/EG


FD/EG


PS(VL), ES(C), ES(C/H)

V-L

L-S

L-S L

V-L

L-S

L-LV-L

V-LL-LV-LV-L

L-S

V-LL-LV-LV-L

L-S

L-LV-L

L-LV-LL-S

L-LV-L

V-LL-LV-LV-L

L-S

L-LV-LL-S

V-LL-LV-LV-L

L-S

FDE/G





EFD/G




DEF/G




V-LL-LV-LV-L

L-SV-L

L-LL

V-LL-LV-LV-L

L-S

V-LL-LV-LV-L

L-S

Case Studies

146

Further, looking at the phenomena based feasibility rules at level 2, infeasible

phenomena with boiling and meting point are removed.

Logical rules



are removed. The superstructure maintains its originality here at this level.

The updated superstructure after all reductions is shown in Figure 6.42.

- S9.2. Generation of basic structures The principle PBBs in phenomena-based superstructure (Figure 6.42) are translated

to basic structures using the algorithm A3.5. These basic structures in the form of


Further, the separation of E and G includes mass separating agent (MSA) that needs

additional separation task. Thus, the basic structures are also identified to recover the

MSA (Step A3.5.11). A desired MSA should be recovered easily and thus should not

form any azeotrope with the considered compounds in the system. The MSA should

take the compound present in lower amount i.e. succinic acid and must have lower

boiling point than succinic acid as water is a lower boiling component than product.

A potential solvent is identified later based on feasible threshold values for the

properties valid for the phenomena’s ‘PT(VL), ES(C), ES(H), PT(MLL), PT(MVL)’ or

literature search. Thus, the basic structures generated by following step A3.5.11 from

the feasible list of SPBs is shown alongside in Figure 6.43.



levels i.e. level 2 and 3 using algorithm A3.6. The biomass separation is only considered

for combination with fermentation step. Also, the tasks having a dashed line are not

combined as they signify that the last separation task needs ‘PT(LS)’ PBB. The

superstructures generated at level 2 and level 3 are shown in Appendix G.3.

• Step 11: Translation of the basic structure to unit-operation

The basic structures performing different tasks are translated to unit-operations using

algorithm A3.7. A selected list of alternatives generated is given in Appendix G.4. Figure

6.44 gives an overview of some of the basic structures translated to unit operation, some

of them are novel. The alternatives generated includes the base case which is the starting

point for this case study. The framework also generates the 3 intensified flowsheet

alternatives including membrane crystallizer and membrane bio-reactor shown in

section 6.3.2.

6.3

. C

ase

stu

dy

3: P

rod

uct

ion

of

Bio

-Su

ccin

ic A

cid

14

7

Fig

ure

6.4

2:

Ph

en

om

en

a b

ase

d s

up

ers

tru

ctu

re a

fte

r a

pp

lyin

g r

ed

uct

ion

ru

les

F/E

G

PT

(MLL),

PS

(LL)

PT

(MV

L),

PS

(VL)

D/E

G

PT

(MLL),

PS

(LL)

PT

(MV

L),

PS

(VL)

PT

(LS

), P

S(L

S),

ES

(C/H

)

D/G

E

PT

(VL),

PS

(VL)

2phM

, P

C(V

L),

PT

(VL),

P

S(V

L),

ES

(C),

ES

(H)

--E

/G—

(or

FE

/G o

r D

E/G

)--

PT

(VL),

PS

(VL)

PT

(MLL),

PS

(LL)

PT

(MV

L),

PS

(VL)

2phM

, P

C(V

L),

PT

(VL),

P

S(V

L),

ES

(C),

ES

(H)

PT

(LS

), P

S(L

S),

ES

(C/H

)2phM

, P

C(V

L),

PT

(VL),

P

S(V

L)*

, E

S(C

), E

S(H

)P

C(L

L),

PT

(LL),

PS

(LL)*

PC

(LS

), P

S(L

S)*

E/G

PT

(VL),

PS

(VL)

PT

(MLL),

PS

(LL)

PT

(MV

L),

PS

(VL)

2phM

, P

C(V

L),

PT

(VL),

P

S(V

L),

ES

(C),

ES

(H)

PT

(LS

), P

S(L

S),

ES

(C/H

)2phM

, P

C(V

L),

PT

(VL),

P

S(V

L)*

, E

S(C

), E

S(H

)P

C(L

L),

PT

(LL),

PS

(LL)*

PC

(LS

), P

S(L

S)*

D/E

FG

PT

(MLL),

PS

(LL)

PT

(MV

L),

PS

(VL)

PT

(LS

), P

S(L

S),

ES

(C/H

)

D/F

GE

2phM

, P

C(V

L),

PT

(VL),

P

S(V

L),

ES

(C),

ES

(H)

D/G

EF

PT

(VL),

PS

(VL)

F/E

GD

PT

(MLL),

PS

(LL)

PT

(MV

L),

PS

(VL)

L-L

V-L

L-S

L-S

L

Sep

ara

tio

n t

as

k -

2S

ep

ara

tio

n t

as

k -

3S

ep

ara

tio

n t

as

k -

4

2phM

, R

(L)

Fe

rme

nta

tion

--D

EF

GIJ

--

Reac

tio

n t

ask

PC

(LS

), P

S(L

S)

DE

FG

I/J

Sep

ara

tio

n t

as

k -

1

DF

/GE

PT

(VL),

PS

(VL)

PT

(MLL),

PS

(LL)

PT

(MV

L),

PS

(VL)

2phM

, P

C(V

L),

PT

(VL),

P

S(V

L),

ES

(C),

ES

(H)

PT

(LS

), P

S(L

S),

ES

(C/H

)

V-L

L-S

L

L-L

V-L

V-L

L-L

V-L

V-L

L-S

L-L

V-L

L-L

V-L

L-S V

-L

V-L

PT

(VL),

PS

(VL)

PT

(MLL),

PS

(LL)

PT

(MV

L),

PS

(VL)

2phM

, P

C(V

L),

PT

(VL),

P

S(V

L),

ES

(C),

ES

(H)

PT

(LS

), P

S(L

S),

ES

(C/H

)2phM

, P

C(V

L),

PT

(VL),

P

S(V

L)*

, E

S(C

), E

S(H

)P

C(L

L),

PT

(LL),

PS

(LL)*

PC

(LS

), P

S(L

S)*

DF

E/G

Cas

e S

tud

ies

14

8

Fig

ure

6.4

3: L

ev

el

1 su

pe

rstr

uct

ure

wit

h t

ran

sla

ted

pri

nci

ple

PB

Bs

to b

asi

c st

ruct

ure

s

F/E

G

D/E

G

D/G

E

--E

/G—

(or

FE

/G o

r D

E/G

)--

E/G

D/E

FG

D/F

GE

L-S

L

Sep

ara

tio

n t

as

k -

2S

ep

ara

tio

n t

as

k -

3S

ep

ara

tio

n t

as

k -

4

Fe

rme

nta

tion

--D

EF

GIJ

--

Reac

tio

n t

ask

DE

FG

I/J

Sep

ara

tio

n t

as

k -

1

DF

/GE

L-S

LM

=2

phM

=R

(L)

M=

PC

(LS

)=P

S(L

S)

M=

PT

(ML

L)=

PS

(LL

)

M=

PT

(MV

L)=

PS

(VL

)

M=

PT

(LS

)=P

S(L

S)

M=

ES

(C/H

)

M=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

D/G

EF

M=

PC

(VL

)=P

S(V

L)

M=

PT

(ML

L)=

PS

(LL

)

M=

PT

(MV

L)=

PS

(VL

)

M=

PT

(LS

)=P

S(L

S)

M=

ES

(C/H

)

M=

PT

(ML

L)=

PS

(LL

)

M=

PT

(MV

L)=

PS

(VL

)

F/E

GD

M=

PT

(ML

L)=

PS

(LL

)

M=

PT

(MV

L)=

PS

(VL

)

M=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PC

(VL

)=P

S(V

L)

M=

PC

(VL

)=P

S(V

L)

M=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PT

(ML

L)=

PS

(LL

)

M=

PT

(MV

L)=

PS

(VL

)

M=

PT

(LS

)=P

S(L

S)

M=

ES

(C/H

)

DF

E/G

M=

PC

(VL

)=P

S(V

L)

M=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PT

(ML

L)=

PS

(LL

)

M=

PT

(MV

L)=

PS

(VL

)

M=

PC

(TS

)=P

S(L

S)

M=

ES

(C/H

)

M=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PC

(VL

)=P

T(V

L)*

=P

S(V

L)

M=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PC

(LL

)=P

T(L

L)=

PS

(LL

)*

M=

PC

(LS

)=P

S(L

S)*

M=

PC

(VL

)=P

S(V

L)

M=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PT

(ML

L)=

PS

(LL

)

M=

PT

(MV

L)=

PS

(VL

)

M=

PT

(LS

)=P

S(L

S)

M=

ES

(C/H

)

M=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PC

(VL

)=P

T(V

L)*

=P

S(V

L)

M=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PC

(LL

)=P

T(L

L)=

PS

(LL

)*

M=

PC

(LS

)=P

S(L

S)*

M=

PC

(VL

)=P

S(V

L)

M=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PT

(ML

L)=

PS

(LL

)

M=

PT

(MV

L)=

PS

(VL

)

M=

PT

(LS

)=P

S(L

S)

M=

ES

(C/H

)

M=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PC

(VL

)=P

T(V

L)*

=P

S(V

L)

M=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PC

(LL

)=P

T(L

L)=

PS

(LL

)*

M=

PC

(LS

)=P

S(L

S)*

M=

ES

(C)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

ES

(H)=

PC

(VL

)=P

T(V

L)=

PS

(VL

)

M=

PT

(ML

L)=

PS

(LL

)

M=

PT

(MV

L)=

PS

(VL

)

S*/

G

L-L

L-L

L-L

L-L

L-S

V-L

L-S

L-L

V-L

L-S

V-L

V-L V-L

V-L

L-L

V-L

V-L

V-L

V-L

V-L

V-L

V-L

LL-L

V-L

L-L

L-S

V-L

V-L

V-L

LL-L

V-L

V-L

V-L

L-L


149

Figure 6.44: Combination of basic structures-(A)-Membrane bio-reactor, (B)-Membrane crystallizer, (C)-Extractive divided wall column, (D)-L-L membrane extraction

M=PT(MLL)=PS(LL)

M=ES(C)

M=PT(LS)=PS(LS)

M=ES(C)=PC(VL)=PT(VL)=PS(VL)

M=PC(VL)=PT(VL)=PS(VL)*

M=PC(VL)=PT(VL)=PS(VL)

M=ES(H)=PC(VL)=PT(VL)=PS(VL)

M=PC(LL)=PT(LL)=PS(LL)*

M=PT(MLL)=PS(LL)

M=2phM=R(L)

M=PC(LS)=PS(LS)


(A)

(B)

(C)

(D)

Non cond. gases

Glucose, Water

CO2Fermentation

broth

Succinic Acid

crystals

Waste

water

Succinic Acid

+ Water

Succinic Acid

+ Water

Succinic Acid +

Water

Water

MSA

MSA

Succinic Acid

+ Water

Water

MSA

Succinic

Acid + water

MSA

Case Studies

150

Figure 6.45 gives an overview of generation of process alternatives at different steps while

applying the framework.




- S12.1. Ranking of unit-operation based flowsheet alternatives Table 6.28 shows the 3 alternatives along with thier Enthalpy Index (EI) at different

levels. These are the selected alternatives that does not consider individual recovery

of unwanted by products.

Table 6.28: Enthalpy index for flowsheet alternatives at different levels

Level Alternative


3 773 Membrane bio-reactor → Carbon treatment → Adsorptive

membrane crystallizer (L-L membrane) 1.000

2 787 Membrane bio-reactor → L-L membrane extraction → Carbon

treatment → Crystallization 0.999

1 250 Fermenter → Microfiltration→ Carbon treatment → Liquid-

liquid membrane → Crystallization→ 0.997

- S12.2. Verification of selected flowsheet alternative

In this section of the case study, the selected alternative is verified and analyzed in

order to compare with the base case and previously generated intensified alternatives.

The three alternatives presented in section 6.3.2 are also generated in this framework.

In this alternative, the membrane bio-reactor performs the fermentation at desired

conditions and allows the biomass free fermentation broth to pass through the

1080

26332

874

789

Mathematical

alternatives

All possible


Total number of

alternatives before

combination






151

membrane. Same hypothesis as in flowsheet alternative 1 of section 6.3.1 is also

considered here. The clarified broth is then passed through liquid-liquid extraction

column with an inbuilt membrane module. The novel equipment separates most of

the water from the clarified broth and the mass separating agent (ionic liquid) is

recovered to be sent back for the makeup. The leftover is then passed through

activated carbon to remove colored impurities. Then the outlet is fed to crystallizer

to obtain pure succinic acid crystals. A hydrophobic phosphonium based ionic liquid

has been used for multistep extraction of the bio-succinic acid (Oliveira, 2012). The

membrane data for separation of hydrophobic ionic liquid from mixture of water and

organic acid is taken from Zhang et al. (2017). The membrane separates the mixture

at high efficiency of >98% and high flux rate to keep the membrane area in acceptable

range based on the super wettability phenomena. The schematic of this alternative is

shown in Figure 6.46. The alternative is simulated in PRO/IITM to resolve the mass

and energy balance to be used for further analysis.

Figure 6.46: Schematic of process alternative 4 (787)



The selected flowsheet alternative from step 12 is analyzed in terms of economics,

sustainability parameters and LCA to generate the values of performance indicators.

The parameters calculated are shown in Table 6.29. The analysis does not include the

cost of ionic liquid.


In this step, the comparison (Table 6.29) of above alternative is made with the base

case and alternatives from section 6.3.2. Various parameters at general level for

example, purity, target production, RM cost etc. are selected including sustainability

and LCA indicators like HTPI (human toxicity potential by ingestion), PCOP (photo

chemical oxidation potential) and GWP is global warming potential.

Succinic Acid

crystals

Waste waterFermentation

broth

Waste

water

Act. CarbonSuccinic Acid + water

MSA

Non cond. gases

Glucose, Water

CO2

Recovered MSA

Spent

Carbon

Membrane bio-reactor

Membrane liquid-liquid

extractor

Adsorption column

Crystallization

Case Studies

152

Table 6.29: Analysis of results for base case and generated intensified alternatives

Parameter Base Case

Alternative 1

(429)

Alternative 2

(668)

Alternative 3

(724)

Alternative 4

(787)

General results Succinic Acid Production (kt/y) 30.00 30.31 32.32 32.65 32.48

Succinic acid purity (wt. %) >99 >99 >99 >99 >99

Utility Cost (M$/y) 4.95 4.13 4.98 4.16 1.26

Raw material cost (M$/y) 29.04 29,09 29.04 29.09 28.94

RM (Glucose) loss (kt/y) 1.49 1.49 1.49 1.49 1.49

Total Process water (kt/y) 13,534.07 11,447.73 13,534.07 11,447.73 11,447.73

Number of unit operations 6 5 5 4 5

Performance

metrics

Succinic acid (kg/kg main RM) 0.86 0.87 0.92 0.93 0.93

Utility cost ($/kg product) 0.16 0.14 0.15 0.13 0.10

RM Cost ($/kg product) 0.97 0.96 0.90 0.89 0.89

Product sale ($/y) 8,58,09,289 8,66,76,411 9,24,46,064 9,33,80,221 9,29,00,753

LCA results GWP (CO2 eq.) 5.41 4.48 5.02 4.16 0.19

HTPI (1/LD50) 2.66E-04 2.20E-04 2.47E-04 2.04E-04 3.21E-05

PCOP 1.50E-01 1.24E-01 1.39E-01 1.15E-01 6.14E-05

HTC (kg benzene eq.) 3.74E+00 3.10E+00 3.48E+00 2.87E+00 7.45E-05

The 4 alternatives are more sustainable and economic than the base case for example resulting

in nearly 22 % reduction in utility cost and 23 % reduction in the global warming potential for

alternative 3 (724), employing membrane bio-reactor and membrane crystallizer. The alternative

787 has approximately 74 % less utility cost and extremely low sustainability and LCA indicators,

owing to highly selective and permeable membrane for separating ionic liquid. Alternative 787

presents the best results among all selected alternatives as compared to the base case. For each

of the alternatives the product purity has been kept or improved from the base case while

maintaining the production target. The number of unit operations have been reduced in all the

alternatives in comparison to the base case (Table 6.29).

A graphical comparison of all the generated alternatives with the base case is shown in Figure

6.47 as a radar plot. The radar plot confirms that the generated alternatives are more sustainable

and non-trade-off, in terms of the selected performance criteria. Here, the outer boundary of the

plot represents the base case design while all the more sustainable alternatives should be within

the boundary. The values are calculated by taking percentage ratios of different factors with

respect to the base case except product (kg/kg RM) where inverse ratio has been taken. Also, in

Figure 6.47 due to considerably low values of HTPI and GWP for alternative 787, a factor of 5


153

and 15 is taken for comparison. Here, RM is raw material, HTPI is human toxicity potential by

ingestion, GWP is global warming potential and HTC is Human Toxicity Carcinogenic.

Figure 6.47: Comparison of economic and LCA improvements relative to the base case

Further, recalling the design targets set in step 4, which are required to be met in order to achieve

more sustainable, economic and innovative solutions. These are as follows:

- Reduce energy consumption –Yes (<40 % reduction annually)

- Reduce utility cost - Yes (12-37 % reduction per kg of product)

- Improvement in LCA/sustainability indictors – Yes (>7 % reduction)

- Unit operation reduction – Yes (1-2)

- Product purity (to be kept at least as base case) – Yes (achieved as required)

- Production target (to be kept at least as base case) – Yes (achieved as required)

- Waste minimization – Yes (<15 % reduction annually)

- Increase product recovery – Yes (<8 % increase annually)

6.3.4. Discussion

A brief summary for the production of bio-succinic acid case study utilizing CO2 is shown in

Figure 6.48. The results are shown across 3 sections (6.3.1-6.3.3) and how the process alternatives

are identified using different approaches. More than 11,500 alternatives are generated while

synthesizing the optimal processing route using the superstructure network optimization based

50%

60%

70%

80%

90%

100%

Product (kg/Kg main RM)^-1

Utility cost (USD/kg product)

RM Cost (USD/kg product)

RM (Glucose) loss (kT/yr)GWP (CO2 eq.)

HTPI(1/LD50)

Process water (kg/kg of product)

Base Case Alternative 1 Alternative 2 Alternative 3 Alternative 4

Case Studies

154

approach out of which more than 2,600 alternatives are found feasible along with existing routes.

The optimal processing route is identified as a novel process alternative to produce bio-succinic

acid. The selected alternative is then designed and analyzed in detail to identify process hotspots

and set targets for improvement. Further, the framework developed in this work is applied on

the same base case identified using superstructure optimization. The framework generates over

700 alternatives including the solutions generated using extended phenomena-based synthesis

method. Some of the alternatives are feasible but may not be practically applicable as they require

either high membrane area or high amount of adsorbent to remove large volume of water. The

novel and intensified flowsheet alternatives are verified and analyzed further and compared with

the base case to achieve set design targets.

Figure 6.48: Summary of results for production of bio-succinic acid

This case study presents the capability of the framework to generate wide range of novel and

innovative solutions involving a bioprocess. The intensified alternative with the membrane

crystallizer may also be studied by performing experiments for verification. While, membrane

bio-reactors involving in-situ product removal are well known techniques. The methodology also

generates another potential novel intensified equipment involving extraction and membrane

separation in a single unit significantly improving results.


The chapter presents 3 case studies spanning chemical and biochemical process applications.

The chapter also shows key feature of the framework to perform direct and indirect phenomena

based synthesis-intensification. Out of the 3 case studies, first case study is an example of direct

Flowsheet alternatives

Total alternatives: 11520

Feasible alternatives: 2604

Existing routes generated: 5


Intensified alternatives: 3


Total feasible alterantives: 789

Selected alternatives: 4

Superstructure Optimization

Detailed design and analysisPhenomena based intensification

Integrated phenomena-based

synthesis-intensification

3 different scenarios

Synthesis and Design Extended Phenomena-based

synthesis-intensificationPBS-Intensification

Novel processing route

Indirect approach

Novel Unit-operations

Novel Unit-operations


155

synthesis while other two are performed via indirect synthesis-intensification. Further, for

indirect synthesis-intensification, in case study 2, a base case flowsheet is used from literature.

While in case study 3, the base case is first synthesized using mathematical optimization of the

superstructure of alternatives. An overview of the case studies is shown in Table 6.30.

Table 6.30: Overview of 3 case studies solved using PBS-Intensification method

Case study 1

(DME)

Case study 2

(Toluene)

Case study 3

(Bio-succinic acid)

Problem type Direct Indirect Indirect

Base Case flowsheet used No Yes Yes

Base case source - Tula, 2016 Synthesized

No. of mathematical alternatives 6 39636 1080

No. of feasible flowsheets 88 726 789

No. of alternatives analyzed 3 3 5

Performance criteria Achieved Achieved Achieved

For all the case studies, several innovative solutions with number of potentially feasible novel

unit-operations are synthesized. The selected novel intensified unit-operations are validated by

using simple mass and energy balance models to show feasibility. These unit-operations can be

further validated by performing detailed modelling and experiments.

Case Studies

156


157

PART - IV

This is the last part of the thesis, where necessary conclusions are

drawn from the research presented in this work. The main

highlights of the framework from perspective of achievements

are presented. The conclusions are then drawn on the basis of the

novelty of the work and research challenges addressed from the

viewpoint of process intensification (PI) in process systems

engineering (PSE). Further, results of the case studies are briefly

discussed in lieu of the framework developed (chapter 7). Finally,

some of the open challenges that could be addressed in future

research to make the framework more robust and develop a

possible interactive tool out of it are discussed (chapter 8).

Case Studies

158

159

Chapter 7 Conclusions

In this chapter of the thesis, the achievements and conclusions are presented. The

achievement section presents the main highlights of the developed framework.

Then, conclusion section provides a summary of the need for innovative solutions,

the developed framework, its key features and the application case studies.

Chapter outline:

7.1. Achievements

7.2. Conclusions

Conclusions

160

7.1. Achievements

In this work, the main achievement is the development of a systematic framework to perform

process synthesis-intensification generating novel, innovative and intensified process flowsheet

alternatives. The main highlights of the bottom-up approach (phenomena) based framework are

as follows:

• The framework can be applied for both direct (new) and indirect (existing) synthesis-

intensification problems.

• The framework based on the decomposition strategy starting at the lowest level of

aggregation (phenomena) does not need detailed or rigorous models at every decision

making step of synthesis-intensification.

• The framework enables a systematic generation of the completely new and novel unit-

operation based flowsheet alternatives without any pre postulation.

• The framework covers a complete search space of possible phases including vapor, liquid

and solid systems at phenomena scale.

• The framework has the potential to generate novel solutions based on special energy

sources operating at lower level of aggregation.

• The framework generates a phenomena based superstructure consisting of all possible

solutions covering complete feasible search space for considered problem.

• The framework allows to rank and select novel and intensified alternatives based on

Enthalpy Index (EI) for detailed analysis and comparison.

• The framework is flexible to handle changes, extensions or different types of chemical

and biochemical processes.

• The framework incorporates economic, life cycle and sustainability analysis to assist in

generation of potential green solutions.

• The framework can be easily translated to an interactive systems engineering tool as it is

based on database, knowledge base and systematic algorithms and rules for every step.

The successful application of the framework for three different case studies shows the capability

of the framework to systematically generate potential novel, innovative and intensified flowsheet

alternatives. The framework presented in this work fulfills the challenges a) and d) mentioned in

the section 2.1 (chapter 2) completely as it is capable of generating non trade off, sustainable and

innovative solutions systematically while partially b) and d) as the future work (chapter 8)

incorporates addition of operability and safety parameters to screen and assess the different

solutions while managing the complexity inherited by them.

161

7.2. Conclusions

The traditional concepts of process synthesis need to be expanded in order to generate novel and

innovative solutions that can significantly improve process performance to cope up with global

competition, economics and induce sustainability. Process intensification (PI) has proven its

potential to generate solutions that bring significant improvements in terms of size, economics,

efficiency, and sustainability. Though, full potential of PI is yet to be unfolded. One of the

highlighted PI approach that guarantees to generate novel and innovative solutions is bottom-

up approach. This solves the challenge of process synthesis by departing from conventional

approach and thus operating at lower level of aggregation. Within bottom-up approaches, several

methodologies have been developed solving different types of problems including simultaneous

synthesis and intensification within a single framework. This allows to incorporate process

intensification principles during process synthesis. However, these simultaneous approaches are

not integrated enough to directly synthesize intensified solutions without a priori information.

In this work, a systematic phenomena-based synthesis-intensification framework is developed.

The framework consists of 4 stages and 13 steps. Several algorithms and knowledge base are also

developed to aid systematic solution generation. The developed framework is different from

other bottom-up approaches as it is not iterative and does not completely depend upon

mathematical optimization based techniques. Here, the synthesis-intensification problem is

solved by decomposition into different parts and then simultaneously generating both novel and

intensified solutions starting from phenomena. Unlike enumeration techniques that struggle

with exponentially increasing combinations, in this framework it is tackled by introducing

ranking based on enthalpy index (EI). The explosion of alternatives generated using the

mathematical combinatorial algorithms are countered using logical and feasibility reduction

rules. These rules are based on the thermodynamic insights, thus making them feasible to be

considered for further analysis. The framework also includes economic, sustainability and life

cycle analysis to compare and ensure that selected alternatives are sustainable solutions.

One of the key novelties of this framework is that it not only generates more economic and

sustainable novel intensified solutions for an existing process but also can perform simultaneous

direct synthesis-intensification via generation of phenomena based superstructure to achieve

desired objectives without any prior postulation of equipments or any process information. The

solutions are generated at different levels using combinatorial rules i.e. flowsheet options based

on existing equipments, existing intensified equipments and completely novel equipment. The

framework does not claim to generate global optimal solutions.

The framework was applied to three different case studies performing direct and indirect

synthesis-intensification. The case studies span chemical and biochemical process applications.

DME case study shows that novel and intensified solutions can be generated at different levels

Conclusions

162

by application of the framework without any prior information and pre postulation about the

equipment. The framework generates novel flowsheet alternatives including both existing and

novel equipments (reactive distillation vapor permeation in a single unit (RDVPSU)). The novel

equipment performs all the required tasks to obtain pure DME while saving around 29 % energy

with significant reduction in environmental parameters as compared to conventional process.

The HDA of toluene and biological production of succinic acid case study are application of

indirect synthesis-intensification. In HDA of toluene, an existing process flowsheet is taken from

literature as the base case while in bio-succinic acid case study the base case is synthesized using

mathematical optimization of superstructure approach. In both the case studies more

sustainable, economic and novel process flowsheet alternatives are synthesized as compared to

the base case. The novel flowsheet alternative in HDA case study reduces the annual hydrogen

loss by 96 % and energy consumption by 10-15 % as compared to the base case. In bio-succinic

acid case study, all the alternatives from synthesis to intensification are novel with novel

equipments like membrane crystallizer and membrane based liquid-liquid extraction. Here, the

intensified solutions result in 12-37 % reduction of utility cost while increasing the product

recovery up to 8 percent.

It should be noted that the novel and intensified unit-operations generated in this work are

simulated using simple models (with experimental data from literature). The novel solutions

generated that are verified using simple models can be further verified by performing detailed

modelling and experimentation.

163

Chapter 8 Future Perspectives

In the last chapter of the thesis, some of the open challenges that could be used for

future research are presented. The challenges for example introduction of safety

and operability, expansion of knowledge bases, more layer of ranking could make

the methodology more robust are mentioned.

Chapter outline:

8.1. Open challenges and future work

Future Perspectives

164

8.1. Open challenges and future work

The challenges that can be addressed in the future research are as follows:

• Inclusion of the operability and safety analysis: Generation of intensified unit-

operations (single unit-operation performing multiple tasks) sometimes significantly

reduces the degree of freedom. Thus, easy operability and considerate safety may become

an issue while realizing these solutions at practical level. So, operability is a key issue to

be addressed while generating intensified alternatives. Thus, the current framework can

be extended by incorporating operability and safety analysis in stage IV of the framework.

This can also be added as a part of the ranking where alternatives ranked better on the

operability and safety at different levels are considered for detailed analysis.

• Additional layers for ranking of alternatives: Currently, the alternatives are ranked

based on Enthalpy Index (EI), which is the lone parameter for ranking in this framework.

This is justified as ready information is not available for new equipments. Also, the

generation of equipments is not known apriori which restricts the development of simple

models. Though, EI alone, is not sufficient to preselect alternatives from simplification,

possible assumptions and solution feasibility point of view. Thus, additional layers of the

ranking are also required to rank the flowsheet alternatives. Some of the options for

future work are to include simplified Gibbs free energy and entropy calculations.

• Framework to a tool: As the framework is systematic and is based on algorithms and

rules developed at each step, it has potential to develop as a tool where certain parts of

the framework requires human interaction. This kind of tool can quickly generate

alternatives where it can be integrated with ICAS (Gani et al. 1997; Gani 2002) property

database to fetch information about the components while missing properties can be

automatically generated using algorithm behind ProPred tool of ICAS. Also, the current

implementation of framework is very convenient and intuitive because of the developed

knowledge bases. However, generating novel and intensified solutions may significantly

benefit by incorporating the algorithms to a dedicated modeling and optimization

environment such as GAMS (GAMS Development Corporation, 2012).

• Expansion of reduction algorithms: The reduction algorithms helps in reducing

infeasible and not logical alternatives from the superstructure. More constraints can be

added here depending on the problem type to reduce the number of alternatives to be

ranked and analyzed in stage IV of the framework.

• Expansion of phenomena database and knowledge bases: The strength of the

framework lies in the generation of alternatives using its phenomena database and

knowledge bases where several algorithms are developed. These can be developed and

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Appendices

Appendix A: Process hotspots identification

A.1: Indicative list for process hotspots identification based on economic,

sustainability and life cycle analysis (adapted from Babi, 2014; Tula, 2016)

Indicator values Base Case property

Reason Identified Process hot-spot

- Raw material recycle/cost - Material value added

Un-reacted raw materials

Equilibrium reaction

- Activation problems - Limiting equilibrium/raw material loss - Contact problems of raw materials/limited mass transfer - Limited heat transfer

- Utility cost - Energy waste cost - CO2 equivalent

Heat of reaction Exothermic reaction - Highly exothermic reaction

- Utility cost - Energy waste cost - CO2 equivalent

Heat of reaction Endothermic reaction - Highly Endothermic reaction

- Utility cost - Capital cost

Operating conditions

Temperature and pressure operating window for the reactor

- Explosive mixture - Product degradation by temperature

- Product sale Formation of byproduct(s)

number of desired products plus number of undesired products

- Formation of undesired side-products

- Utility cost - Material value added - Energy waste cost - CO2 equivalent

Un-reacted raw materials and products recovery

Presence of azeotrope(s), High energy usage heating and/or cooling

- Azeotrope - Difficult separation - Low driving force - High energy consumption and/or demand

-Insufficient purity Presence of other compounds and product recovery

Presence of azeotrope(s), eutectic point

- Azeotrope - Difficult separation - Low driving force

Ap

pen

dic

es

18

0

Ap

pe

nd

ix B

: D

esi

gn

ta

rge

ts i

de

nti

fica

tio

n

B.1

: A

n i

nd

ica

tiv

e l

ist

for

de

sig

n t

arg

ets

ba

sed

on

pro

cess

ho

tsp

ots

(a

da

pte

d f

rom

Ba

bi,

20

14;

Tu

la,

20

16)

Pro

cess

ho

tsp

ot/

De

sig

n t

arg

et

Act

ivat

ion

p

rob

lem

s L

imit

ing

eq

uil

ibri

um

L

imit

ed m

ass

tran

sfer

L

imit

ed h

eat

tran

sfer

Fo

rmat

ion

of

un

des

ired

sid

e-p

rod

uct

s A

zeo

tro

pe

Dif

ficu

lt s

epar

atio

n d

ue

to l

ow

dri

vin

g f

orc

e H

igh

en

erg

y co

nsu

mp

tio

n/d

eman

d

Incr

ease

raw

mat

eria

l co

nve

rsio

n

* *

* *

*

* *

Red

uce

raw

mat

eria

l lo

ss

* *

* *

* *

* *

Red

uce

pro

du

ct l

oss

*

* *

*

Red

uce

en

erg

y co

nsu

mp

tio

n

*

*

* *

Incr

ease

pu

rity

*

* *

*

Red

uce

uti

lity

co

st

*

*

* *

Un

it o

per

atio

ns

red

uct

ion

*

* *

* *

* *

*

Imp

rove

men

t in

L

CA

/su

stai

nab

ilit

y in

dic

ato

rs

* *

* *

* *

* *

Pro

du

ct p

uri

ty

* *

* *

* *

* *

Pro

du

ctio

n t

arg

et

* *

* *

* *

* *

Was

te m

inim

izat

ion

*

* *

* *

* *

*

Ap

pen

dic

es

18

1

Ap

pe

nd

ix C

: K

no

wle

dg

e b

ase

s (K

B)

C.1

: T

ran

sla

tio

n o

f u

nit

-op

era

tio

ns

to t

ask

an

d p

he

no

me

na

(K

B2

.1)

(ex

pa

nd

ed

fro

m L

utz

e,

20

12 a

nd

Ba

bi,

20

14)

Inte

nsi

fie

d E

qu

ipm

en

t F

ee

d P

ha

se

Ta

sk

PB

Bs

Cre

ate

d o

r a

dd

ed

ph

ase

M

SA

-Y

/N

Se

pa

rati

ng

ag

en

t

Bat

ch r

eact

or

S,

V a

nd

/or

L

Rea

ctio

n

M,

2p

hM

(tw

o p

has

es),

R,

ES

(C)

(exo

ther

mic

), E

S(H

)(e

nd

oth

erm

ic)

-Y

/NL

iqu

id s

olv

ent

(MS

A)

and

en

erg

y tr

ansf

er (

ES

A)

Sem

i-b

atch

rea

cto

r S

, V

an

d/o

r L

R

eact

ion

M

, 2

ph

M(t

wo

ph

ases

), R

, E

S(C

) (e

xoth

erm

ic),

ES

(H )

(en

do

ther

mic

) -

Y/N

Liq

uid

so

lven

t (M

SA

) an

d

ener

gy

tran

sfer

(E

SA

)

CS

TR

L

R

eact

ion

M

, R

, E

S(C

) (e

xoth

erm

ic),

ES

(H )

(en

do

ther

mic

) -

Y/N

Liq

uid

so

lven

t (M

SA

) an

d

ener

gy

tran

sfer

(E

SA

)

Tu

bu

lar

Rea

cto

r (P

FR

) V

R

eact

ion

M

, R

, E

S(C

) (e

xoth

erm

ic),

ES

(H )

(en

do

ther

mic

) -

N

En

erg

y tr

ansf

er (

ES

A)

Pac

k-b

ed r

eact

or

S a

nd

/or

V

Rea

ctio

n

M,

2p

hM

(tw

o p

has

es),

R,

ES

(C)

(exo

ther

mic

), E

S(H

)(e

nd

oth

erm

ic)

-N

E

ner

gy

tran

sfer

(E

SA

)

Par

tial

co

nd

ensa

tio

n o

r va

po

riza

tio

n

V a

nd

/or

L

Sep

arat

ion

M

, P

T(V

L),

PS

(VL

), E

S(H

)/E

S(C

) V

or

L

N

En

erg

y tr

ansf

er (

ES

A)

Fla

sh v

apo

riza

tio

n

L

Sep

arat

ion

M

, P

T(V

L),

PS

(VL

) V

N

P

ress

ure

red

uct

ion

Dis

till

atio

n

V a

nd

/or

L

Sep

arat

ion

M

, 2

ph

M,

PC

(VL

), P

T(V

L),

PS

(VL

), E

S(C

), E

S(H

) V

an

d L

N

H

eat

tran

sfer

(E

SA

) an

d

som

etim

es w

ork

tra

nsf

er

Ext

ract

ive

dis

till

atio

n

V a

nd

/or

L

Sep

arat

ion

M

, 2

ph

M,

PC

(VL

), P

T(V

L),

PS

(VL

), E

S(C

), E

S(H

) V

an

d L

Y

L

iqu

id s

olv

ent

(MS

A)

and

h

eat

tran

sfer

(E

SA

)

Reb

oil

ed a

bso

rpti

on

V

an

d/o

r L

S

epar

atio

n

M,

2p

hM

, P

C(V

L),

PT

(VL

), P

S(V

L),

ES

(H)

V a

nd

L

Y

Liq

uid

ab

sorb

ent

(MS

A)

and

hea

t tr

ansf

er (

ES

A)

Gas

Ab

sorp

tio

n

V a

nd

/or

L

Sep

arat

ion

M

, P

T(V

L),

PS

(VL

) L

iqu

id

Y

Liq

uid

ab

sorb

ent

(MS

A)

Str

ipp

ing

L

S

epar

atio

n

M,

2p

hM

, P

C(V

L),

PT

(VL

), P

S(V

L)

V

Y

Str

ipp

ing

vap

or

(MS

A)

Ste

am d

isti

llat

ion

V

an

d/o

r L

S

epar

atio

n

M,

2p

hM

, P

C(V

L),

PT

(VL

), P

S(V

L),

ES

(C)

V a

nd

/or

L

Y

Str

ipp

ing

vap

or

(MS

A)

and

hea

t tr

ansf

er (

ES

A)

Reb

oil

ed s

trip

pin

g

L

Sep

arat

ion

M

, 2

ph

M,

PC

(VL

), P

T(V

L),

PS

(VL

), E

S(H

) V

N

H

eat

tran

sfer

(E

SA

)

Aze

otr

op

ic d

isti

llat

ion

V

an

d/o

r L

S

epar

atio

n

M,

2p

hM

, P

C(V

L),

PT

(VL

), P

S(V

L),

PC

(LL

), P

S(L

L),

ES

(C),

ES

(H)

V a

nd

L

Y

Liq

uid

en

trai

ner

(M

SA)

and

hea

t tr

ansf

er (

ES

A)

Ap

pen

dic

es

18

2

Liq

uid

–li

qu

id e

xtra

ctio

n

L

Sep

arat

ion

M

, P

C(L

L),

PT

(LL

), P

S(L

L)

L

Y

Liq

uid

so

lven

t (M

SA

)

Liq

uid

–li

qu

id e

xtra

ctio

n (

two

so

lven

t)

L

Sep

arat

ion

M

, P

C(L

L),

PT

(LL

), P

S(L

L)

L

Y

Tw

o l

iqu

id s

olv

ents

(M

SA

1 an

d M

SA2

)

Dry

ing

L

/S

Sep

arat

ion

M

, P

C(L

S),

PT

(VL

), P

S(V

L),

ES

(H)

V

Y

Gas

(M

SA

) an

d/o

r h

eat

tran

sfer

(E

SA

)

Eva

po

rati

on

L

S

epar

atio

n

M,

PT

(VL

), P

S(V

L),

ES(

H)

V

N

En

erg

y tr

ansf

er (

ES

A)

Cry

stal

liza

tio

n

L

Sep

arat

ion

M

, P

T(L

S),

PS

(LS

), E

S(H

) S

an

d V

N

E

ner

gy

tran

sfer

(E

SA

)

L

Sep

arat

ion

M

, P

T(L

S),

PS

(LS

), E

S(C

) S

N

E

ner

gy

tran

sfer

(E

SA

)

Des

ub

lim

atio

n

V

Sep

arat

ion

M

, P

T(V

S),

PS

(VS

), E

S(C

) S

N

E

ner

gy

tran

sfer

(E

SA

)

Lea

chin

g (

liq

uid

–so

lid

ext

ract

ion

) S

S

epar

atio

n

M,

2p

hM

, P

C(L

S),

PT

(LS

), P

S(L

S)

L

Y

Liq

uid

so

lven

t (M

SA

)

Div

idin

g W

all

Co

lum

n

V a

nd

/or

L

Sep

arat

ion

M

, 2

ph

M,

PC

(VL

), P

T(V

L),

PS

(VL

), E

S(C

), E

S(H

) V

an

d L

N

H

eat

tran

sfer

(E

SA

) an

d

som

etim

es w

ork

tra

nsf

er

Dec

ante

r L

S

epar

atio

n

M,

PC

(LL

), P

S(L

L)

L

N

-

Su

per

crit

ical

Ext

ract

ion

L

S

epar

atio

n

M,

PC

(LL

), P

T(L

L),

PS

(LL

), E

S(C

), E

S(H

) L

Y

S

up

ercr

itic

al a

bso

rben

t (M

SA

)

Mem

bra

ne-

Per

vap

ora

tio

n

V a

nd

L

Sep

arat

ion

M

, P

T(M

VL

), P

S(V

L)

L

N

En

erg

y tr

ansf

er (

ES

A)

Mem

bra

ne-

Vap

or-

per

mea

tio

n

V

Sep

arat

ion

M

, P

T(M

VV

), P

S(V

V)

V

N

En

erg

y tr

ansf

er (

ES

A)

Mem

bra

ne

(Per

vap

ora

tio

n)

R

eact

or

V a

nd

L

Rea

ctio

n+

S

epar

atio

n

M,

2p

hM

(tw

o p

has

es),

R,

PT

(MV

L)

, E

S(C

)(ex

oth

erm

ic),

E

S(H

)(en

do

ther

mic

) V

an

d L

N

E

ner

gy

tran

sfer

(E

SA

)

Rea

ctiv

e D

isti

llat

ion

V

an

d/o

r L

R

eact

ion

+

Sep

arat

ion

M

, 2

ph

M,

R,

PC

(VL

), P

T(V

L),

PS

(VL

), E

S(C

), E

S(H

) V

an

d L

N

E

ner

gy

tran

sfer

(E

SA

)

Rea

ctiv

e D

ivid

ing

Wal

l C

olu

mn

V

an

d/o

r L

R

eact

ion

+

Sep

arat

ion

M

, 2

ph

M,

R,

PC

(VL

), P

T(V

L),

PS

(VL

), E

S(C

), E

S(H

) V

an

d L

N

E

ner

gy

tran

sfer

(E

SA

)

Div

idin

g w

all

colu

mn

V

an

d/o

r L

S

epar

atio

n

M,

2p

hM

, P

C(V

L),

PT

(VL

), P

S(V

L),

ES

(C),

ES

(H)

V a

nd

L

N

En

erg

y tr

ansf

er (

ES

A)

Rea

ctiv

e d

isti

llat

ion

V

an

d/o

r L

R

eact

ion

+

Sep

arat

ion

M

, 2

ph

M,

R,

PC

(VL

), P

T(V

L),

PS

(VL

), E

S(C

), E

S(H

) V

an

d L

N

E

ner

gy

tran

sfer

(E

SA

)

Mem

bra

ne-

reac

tive

dis

till

atio

n

V a

nd

/or

L

Rea

ctio

n +

S

epar

atio

n

M,

2p

hM

, R

, P

C(V

L),

PT

(VL

), P

S(V

L),

PT

(MV

L/M

VV

/ML

L),

P

S(L

L/V

V),

E

S(C

), E

S(H

) V

an

d L

N

E

ner

gy

tran

sfer

(E

SA

)

Ap

pen

dic

es

18

3

Mic

row

ave

dry

ing

S a

nd

L

Sep

arat

ion

M

, P

C(L

S),

PT

(VL

), P

S(V

L),

ES

(D)

V

N

En

erg

y tr

ansf

er (

ES

A)

Sta

tic

mix

er r

eact

ors

fo

r co

nti

nu

ou

s re

acti

on

s L

an

d/o

r S

an

d/o

r V

R

eact

ion

M

, 2

ph

M ,

R,

ES

(C)(

exo

ther

mic

), E

S(H

)(en

do

ther

mic

) -

Y/N

L

iqu

id s

olv

ent

(MS

A)

and

en

erg

y tr

ansf

er (

ES

A)

Pu

lsed

co

mp

ress

ion

rea

cto

r V

R

eact

ion

M

, R

, E

S(D

) -

Y/N

L

iqu

id s

olv

ent

(MS

A)

and

en

erg

y tr

ansf

er (

ES

A)

Cen

trif

ug

al l

iqu

id-l

iqu

id

con

tact

ors

L

iqu

id

Sep

arat

ion

M

, P

C(L

L),

PS

(LL

), E

S(D

) -

N

-

Ph

oto

chem

ical

rea

cto

r L

an

d/o

r S

an

d/o

r V

R

eact

ion

M

, 2

ph

M(t

wo

ph

ases

), R

, E

S(D

), E

S(C

)(ex

oth

erm

ic),

E

S(H

)(en

do

ther

mic

) -

Y/N

L

iqu

id s

olv

ent

(MS

A)

and

en

erg

y tr

ansf

er (

ES

A)

Rea

ctiv

e ab

sorp

tio

n

V

Rea

ctio

n +

S

epar

atio

n

M,

R,

PT

(VL

), P

S(V

L)

L

Y

Liq

uid

ab

sorb

ent

(MS

A)

Mem

bra

ne

crys

tall

izat

ion

L

S

epar

atio

n

M,

PT

(LS

), P

S(L

S),

PT

(ML

L),

PS

(LL

,VV

), E

S(C

) S

N

E

ner

gy

tran

sfer

(E

SA

)

M,

PC

(LS

), P

T(L

S),

PS

(LS

), P

T(M

VL

/ML

L),

PC

(VL

), P

T(V

L),

P

S(L

L,V

V),

ES

(H)

S a

nd

V

N

En

erg

y tr

ansf

er (

ES

A)

Mem

bra

ne

dis

till

atio

n

V a

nd

/or

L

Sep

arat

ion

M

, 2

ph

M,

PC

(VL

), P

T(V

L),

PS

(VL

), P

T(M

VL

/MV

V/M

LL

),

PS

(LL

,VV

), E

S(C

), E

S(H

) V

an

d L

N

E

ner

gy

tran

sfer

(E

SA

)

Ult

raso

un

d r

eact

or

L a

nd

/or

S

and

/or

V

Rea

ctio

n

M,

2p

hM

(tw

o p

has

es),

R,

ES

(D),

ES

(C)(

exo

ther

mic

),

ES

(H)(

end

oth

erm

ic)

- Y

/N

Liq

uid

so

lven

t (M

SA

) an

d

ener

gy

tran

sfer

(E

SA

)

So

no

chem

ical

rea

cto

r L

an

d/o

r S

an

d/o

r V

R

eact

ion

M

, 2

ph

M(t

wo

ph

ases

), R

, E

S(D

), E

S(C

)(ex

oth

erm

ic),

E

S(H

)(en

do

ther

mic

) -

Y/N

L

iqu

id s

olv

ent

(MS

A)

and

en

erg

y tr

ansf

er (

ES

A)

Ult

raso

un

d e

nh

ance

d

crys

tall

izat

ion

L

S

epar

atio

n

M,

PT

(LS

), P

S(L

S),

ES

(D)

S o

r V

N

E

ner

gy

tran

sfer

(E

SA

)

Pu

lse

com

bu

stio

n d

ryin

g

S a

nd

L

Sep

arat

ion

M

, P

T(V

L),

PS

(VL

), E

S(D

) V

N

E

ner

gy

tran

sfer

(E

SA

)

Ad

sorp

tive

dis

till

atio

n

V a

nd

/or

L

Sep

arat

ion

M

, 2

ph

M,

PC

(VL

), P

T(V

L),

PS

(VL

), P

C(L

S),

PS

(LS)

, E

S(C

), E

S(H

) S

Y

S

oli

d a

gen

t (M

SA

)

Rea

ctiv

e ex

trac

tio

n c

olu

mn

s L

S

epar

atio

n

M,

R,

PC

(LL

), P

S(L

L)

Liq

uid

Y

L

iqu

id s

olv

ent

(MS

A)

Div

ided

wal

l co

lum

n (

extr

acti

ve)

V a

nd

/or

L

Sep

arat

ion

M

, 2

ph

M,

PC

(VL

), P

T(V

L),

PS

(VL

), E

S(C

), E

S(H

) V

an

d L

Y

L

iqu

id s

olv

ent

(MS

A)

and

en

erg

y tr

ansf

er (

ES

A)

Mic

row

ave-

assi

sted

dis

till

atio

n

V a

nd

/or

L

Sep

arat

ion

M

, 2

ph

M,

PC

(VL

), P

T(V

L),

PS

(VL

), E

S(C

), E

S(D

), E

S(D

) V

an

d L

N

E

ner

gy

tran

sfer

(E

SA

)

Mic

row

ave-

assi

sted

rea

ctiv

e d

isti

llat

ion

V

an

d/o

r L

R

eact

ion

+

Sep

arat

ion

M

, 2

ph

M,

R,

PC

(VL

), P

T(V

L),

PS

(VL

), E

S(C

), E

S(D

), E

S(D

) V

an

d L

N

E

ner

gy

tran

sfer

(E

SA

)

Mem

bra

ne

reac

tor

L a

nd

/or

S

and

/or

V

Rea

ctio

n +

S

epar

atio

n

M,

2p

hM

(tw

o p

has

es),

R,

PT

(MV

L/M

VV

/ML

L),

PS

(LL

,VV

, V

L)

- N

E

ner

gy

tran

sfer

(E

SA

)

Ap

pen

dic

es

18

4

Fil

trat

ion

or

Cen

trif

ug

e L

an

d/o

r S

Sep

arat

ion

M

, P

C(L

S),

PS

(LS

) -

N

-

Liq

uid

Mem

bra

ne-

Sep

arat

ion

(eg

R

ever

se o

r fo

rwar

d o

smo

ssis

) L

S

epar

atio

n

M,

PT

(ML

L),

PS

(LL

) -

N

-

Ad

sorp

tio

n

V o

r L

S

epar

atio

n

M,

PC

(LS

/VS

), P

S(L

S/V

S)

S

Y

So

lid

ag

ent

(MS

A)

Ad

sorp

tio

n

V

Sep

arat

ion

M

, P

C(V

L),

PS

(VL

) L

Y

L

iqu

id a

gen

t (M

SA

)

Mic

row

ave

reac

tor

L a

nd

/or

S

and

/or

V

Rea

ctio

n

M,

2p

hM

(tw

o p

has

es),

R,

ES

(D)

, E

S(C

)(ex

oth

erm

ic),

E

S(H

)(en

do

ther

mic

) -

Y/N

L

iqu

id s

olv

ent

(MS

A)

and

en

erg

y tr

ansf

er (

ES

A)

Ult

raso

un

d r

eact

or

L a

nd

/or

S

and

/or

V

Rea

ctio

n

M,

2p

hM

(tw

o p

has

es),

R,

ES

(D)

, E

S(C

)(ex

oth

erm

ic),

E

S(H

)(en

do

ther

mic

) -

Y/N

L

iqu

id s

olv

ent

(MS

A)

and

en

erg

y tr

ansf

er (

ES

A)

Mel

ter

S

Sep

arat

ion

P

T(L

S),

PS

(LS

) L

N

-

Ap

pen

dic

es

18

5

C.2

: T

ran

sla

tio

n o

f p

roce

ss h

ots

po

ts t

o p

rin

cip

le P

BB

s (K

B2

.2)

(ex

pa

nd

ed

fro

m L

utz

e,

20

12 a

nd

Ba

bi,

20

14)

Sr.

No

. P

roce

ss H

ots

po

t M

ain

ta

sk

Pro

pe

rty

/Bin

ary

Ra

tio

A

lte

rna

tiv

e

Ta

sk

MS

A-

Y/N

A

dd

itio

na

l in

form

ati

on

P

BB

1 A

ctiv

atio

n p

rob

lem

s R

eact

ion

C

alcu

late

ΔG

rxn

R

eact

ion

N

U

se o

f ca

taly

st

2p

hM

(tw

o p

has

es),

E

S(H

)

R

eact

ion

C

alcu

late

ΔG

rxn

R

eact

ion

N

U

se o

f d

irec

t en

erg

y so

urc

e 2

ph

M (

two

ph

ases

),

ES

(H)

2

Lim

itin

g

equ

ilib

riu

m/r

aw

mat

eria

l lo

ss

Rea

ctio

n

So

lub

ilit

y p

aram

eter

S

epar

atio

n

Y

Eq

uil

ibri

um

sh

ift

PC

(LL

), P

T(L

L),

PS

(LL

)

R

eact

ion

V

apo

r p

ress

ure

, h

eat

of

vap

ori

zati

on

, b

oil

ing

po

int

Sep

arat

ion

N

E

qu

ilib

riu

m s

hif

t 2

ph

M,

PC

(VL

), P

T(V

L),

P

S(V

L),

ES

(C),

ES

(H)

R

eact

ion

M

ola

r vo

lum

e, s

olu

bil

ity

par

amet

er

Sep

arat

ion

N

E

qu

ilib

riu

m s

hif

t P

T(M

VL

), P

S(V

L)

R

eact

ion

V

an d

er W

aals

vo

lum

e, c

riti

cal

tem

p

Sep

arat

ion

N

E

qu

ilib

riu

m s

hif

t P

T(M

VV

), P

S(V

V)

R

eact

ion

M

ole

cula

r w

eig

ht,

mo

lecu

lar

dia

met

er

Sep

arat

ion

N

E

qu

ilib

riu

m s

hif

t P

C(L

S),

PS

(LS

)

R

eact

ion

S

olu

bil

ity

par

amet

er,

rad

ius

of

gyr

atio

n,

mo

lar

volu

me

Sep

arat

ion

N

E

qu

ilib

riu

m s

hif

t P

T(M

LL

), P

S(L

L)

3 H

igh

ly e

nd

oth

erm

ic

Rea

ctio

n

Cal

cula

te Δ

Hrx

n

Rea

ctio

n

N

Hea

tin

g

ES

(H)

R

eact

ion

C

alcu

late

ΔH

rxn

R

eact

ion

N

H

eati

ng

E

S(D

)

4

Hig

hly

exo

ther

mic

R

eact

ion

C

alcu

late

ΔH

rxn

R

eact

ion

N

C

oo

lin

g E

S(C

)

R

eact

ion

C

alcu

late

ΔH

rxn

R

eact

ion

N

A

lter

nat

ive

coo

lin

g s

ou

rce

ES

(D)

5

Fo

rmat

ion

of

un

des

ired

sid

e-p

rod

uct

s

Rea

ctio

n

- R

eact

ion

N

R

eact

ion

fo

r re

acti

ng

aw

ay s

ide

pro

du

cts

R

R

eact

ion

S

olu

bil

ity

par

amet

er

Sep

arat

ion

Y

S

epar

atio

n o

f si

de-

pro

du

cts

PC

(LL

), P

T(L

L),

PS

(LL

)

R

eact

ion

V

apo

r p

ress

ure

, h

eat

of

vap

ori

zati

on

, b

oil

ing

po

int

Sep

arat

ion

N

S

epar

atio

n o

f si

de-

pro

du

cts

2p

hM

, P

C(V

L),

PT

(VL

),

PS

(VL

), E

S(C

), E

S(H

)

R

eact

ion

M

ola

r vo

lum

e, s

olu

bil

ity

par

amet

er

Sep

arat

ion

N

S

epar

atio

n o

f si

de-

pro

du

cts

PT

(MV

L),

PS

(VL

)

R

eact

ion

V

an d

er W

aals

vo

lum

e, c

riti

cal

tem

p

Sep

arat

ion

N

S

epar

atio

n o

f si

de-

pro

du

cts

PT

(MV

V),

PS

(VV

)

R

eact

ion

S

olu

bil

ity

par

amet

er,

rad

ius

of

gyr

atio

n,

mo

lar

volu

me

Sep

arat

ion

N

S

epar

atio

n o

f si

de-

pro

du

cts

PT

(ML

L),

PS

(LL

)

Ap

pen

dic

es

18

6

6

Co

nta

ct p

rob

lem

of

RM

/lim

ited

mas

s tr

ansf

er

Rea

ctio

n

- M

ixin

g

N

Mix

ing

alt

ern

ativ

es

M,

2p

hM

(tw

o p

has

es)

R

eact

ion

-

Mix

ing

N

M

ixin

g a

lter

nat

ives

M

, 2

ph

M,

ES

(D)

7

Exp

losi

ve m

ixtu

re

Rea

ctio

n

Mix

ture

fla

sh p

oin

t R

eact

ion

N

C

oo

lin

g E

S(C

)

Rea

ctio

n

So

lub

ilit

y p

aram

eter

S

epar

atio

n

Y

Mix

ture

fla

sh p

oin

t, r

emo

vin

g o

ne

com

po

un

d a

ffec

ts t

he

flas

h p

oin

t P

C(L

L),

PT

(LL

), P

S(L

L)

Rea

ctio

n

Mo

lar

volu

me,

so

lub

ilit

y p

aram

eter

S

epar

atio

n

N

Mix

ture

fla

sh p

oin

t, r

emo

vin

g o

ne

com

po

un

d a

ffec

ts t

he

flas

h p

oin

t P

T(M

VL

), P

S(V

L)

Rea

ctio

n

Van

der

Waa

ls v

olu

me,

cri

tica

l te

mp

S

epar

atio

n

N

Mix

ture

fla

sh p

oin

t, r

emo

vin

g o

ne

com

po

un

d a

ffec

ts t

he

flas

h p

oin

t P

T(M

VV

), P

S(V

V)

Rea

ctio

n

So

lub

ilit

y p

aram

eter

, ra

diu

s o

f g

yrat

ion

, m

ola

r vo

lum

e S

epar

atio

n

N

Mix

ture

fla

sh p

oin

t, r

emo

vin

g o

ne

com

po

un

d a

ffec

ts t

he

flas

h p

oin

t P

T(M

LL

), P

S(L

L)

8

Deg

rad

atio

n b

y te

mp

erat

ure

R

eact

ion

-

Rea

ctio

n

N

Co

oli

ng

ES

(C)

Rea

ctio

n

So

lub

ilit

y p

aram

eter

S

epar

atio

n

Y

Rem

ovi

ng

pro

du

cts/

des

irab

le s

ide-

pro

du

cts

that

are

deg

rad

ed b

y h

igh

tem

per

atu

res

PC

(LL

), P

T(L

L),

PS

(LL

)

Rea

ctio

n

Mo

lar

volu

me,

so

lub

ilit

y p

aram

eter

S

epar

atio

n

N

Rem

ovi

ng

pro

du

cts/

des

irab

le s

ide-

pro

du

cts

that

are

deg

rad

ed b

y h

igh

tem

per

atu

res

PT

(MV

L),

PS

(VL

)

Rea

ctio

n

Van

der

Waa

ls v

olu

me,

cri

tica

l te

mp

S

epar

atio

n

N

Rem

ovi

ng

pro

du

cts/

des

irab

le s

ide-

pro

du

cts

that

are

deg

rad

ed b

y h

igh

tem

per

atu

res

PT

(MV

V),

PS

(VV

)

Rea

ctio

n

So

lub

ilit

y p

aram

eter

, ra

diu

s o

f g

yrat

ion

, m

ola

r vo

lum

e S

epar

atio

n

N

Rem

ovi

ng

pro

du

cts/

des

irab

le s

ide-

pro

du

cts

that

are

deg

rad

ed b

y h

igh

tem

per

atu

res

PT

(ML

L),

PS

(LL

)

9

Lim

ited

hea

t tr

ansf

er

Rea

ctio

n

- M

ixin

g

N

Incr

ease

hea

t tr

ansf

er

M,

2p

hM

(tw

o p

has

es)

10

Aze

otr

op

e S

epar

atio

n

Vap

or

pre

ssu

re,

solu

bil

ity

par

amet

er

Sep

arat

ion

Y

F

orm

atio

n o

f A

zeo

tro

pe

(s)

2p

hM

, P

C(V

L),

PT

(VL

),

PS

(VL

), E

S(C

), E

S(H

),

PC

(LL

), P

S(L

L)

Sep

arat

ion

K

inet

ic d

iam

eter

, V

an d

er W

aals

vo

lum

e S

epar

atio

n

Y (

S/L

) A

ffin

ity

for

MS

A/F

orm

atio

n o

f A

zeo

tro

pe

PC

(VL

/LS

/VS

),

PS

(VL

/LS

/VS

)

Sep

arat

ion

S

olu

bil

ity

par

amet

er

Sep

arat

ion

Y

F

orm

atio

n o

f A

zeo

tro

pe

(s)

PC

(LL

), P

T(L

L),

PS

(LL

)

Sep

arat

ion

V

apo

r p

ress

ure

, h

eat

of

vap

ori

zati

on

, b

oil

ing

po

int,

so

lub

ilit

y p

aram

eter

S

epar

atio

n

Y

Fo

rmat

ion

of

Aze

otr

op

e (s

) 2

ph

M,

PC

(VL

), P

T(V

L),

P

S(V

L),

ES

(C),

ES

(H)

Sep

arat

ion

V

apo

r p

ress

ure

, h

eat

of

vap

ori

zati

on

, b

oil

ing

po

int

Sep

arat

ion

N

F

orm

atio

n o

f A

zeo

tro

pe

(s)

2p

hM

, P

C(V

L),

PT

(VL

),

PS

(VL

), E

S(C

), E

S(H

)

Sep

arat

ion

M

ola

r vo

lum

e, s

olu

bil

ity

par

amet

er

Sep

arat

ion

N

F

orm

atio

n o

f A

zeo

tro

pe

(s)

PT

(MV

L),

PS

(VL

)

Sep

arat

ion

V

an d

er W

aals

vo

lum

e, c

riti

cal

tem

p

Sep

arat

ion

N

F

orm

atio

n o

f A

zeo

tro

pe

(s)

PT

(MV

V),

PS

(VV

)

Ap

pen

dic

es

18

7

Sep

arat

ion

S

olu

bil

ity

par

amet

er

Sep

arat

ion

N

F

orm

atio

n o

f A

zeo

tro

pe

(s)

PT

(ML

L),

PS

(LL

)

11

Deg

rad

atio

n b

y te

mp

erat

ure

S

epar

atio

n

Bo

ilin

g p

oin

t S

epar

atio

n

N

Red

uct

ion

of

tem

per

atu

re

ES

(C)

12

Dif

ficu

lt s

epar

atio

n

du

e to

lo

w d

rivi

ng

fo

rce

Sep

arat

ion

V

apo

r p

ress

ure

, so

lub

ilit

y p

aram

eter

S

epar

atio

n

Y

DF

an

alys

is

2p

hM

, P

C(V

L),

PT

(VL

),

PS

(VL

), E

S(C

), E

S(H

)

S

epar

atio

n

So

lub

ilit

y p

aram

eter

S

epar

atio

n

Y

Aff

init

y fo

r M

SA

P

C(L

L),

PT

(LL

), P

S(L

L)

S

epar

atio

n

Kin

etic

dia

met

er,

Van

der

Waa

ls

volu

me

Sep

arat

ion

Y

(S

/L)

Aff

init

y fo

r M

SA

P

C(V

L/L

S/V

S),

P

S(V

L/L

S/V

S)

S

epar

atio

n

Vap

or

pre

ssu

re,

hea

t o

f va

po

riza

tio

n,

bo

ilin

g p

oin

t, s

olu

bil

ity

par

amet

er

Sep

arat

ion

Y

D

F a

nal

ysis

2

ph

M,

PC

(VL

), P

T(V

L),

P

S(V

L),

ES

(C),

ES

(H)

S

epar

atio

n

Vap

or

pre

ssu

re,

hea

t o

f va

po

riza

tio

n,

bo

ilin

g p

oin

t S

epar

atio

n

N

DF

an

alys

is

2p

hM

, P

C(V

L),

PT

(VL

),

PS

(VL

), E

S(C

), E

S(H

)

S

epar

atio

n

Mo

lar

volu

me,

so

lub

ilit

y p

aram

eter

S

epar

atio

n

N

Co

mp

on

ent

affi

nit

y P

T(M

VL

), P

S(V

L)

S

epar

atio

n

Van

der

Waa

ls v

olu

me,

cri

tica

l te

mp

S

epar

atio

n

N

Co

mp

on

ent

affi

nit

y P

T(M

VV

), P

S(V

V)

S

epar

atio

n

So

lub

ilit

y p

aram

eter

, ra

diu

s o

f g

yrat

ion

, m

ola

r vo

lum

e S

epar

atio

n

N

Co

mp

on

ent

affi

nit

y P

T(M

LL

), P

S(L

L)

13

Hig

h e

ner

gy

con

sum

pti

on

/dem

and

S

epar

atio

n

Vap

or

pre

ssu

re,

solu

bil

ity

par

amet

er

Sep

arat

ion

Y

A

ffin

ity

for

MS

A

PC

(LL

), P

T(L

L),

PS

(LL

)

Sep

arat

ion

K

inet

ic d

iam

eter

, V

an d

er W

aals

vo

lum

e S

epar

atio

n

Y (

S/L

) A

ffin

ity

for

MS

A

PC

(VL

/LS

/VS

),

PS

(VL

/LS

/VS

)

Sep

arat

ion

V

apo

r p

ress

ure

, h

eat

of

vap

ori

zati

on

, b

oil

ing

po

int,

so

lub

ilit

y p

aram

eter

S

epar

atio

n

Y

DF

an

alys

is

2p

hM

, P

C(V

L),

PT

(VL

),

PS

(VL

), E

S(C

), E

S(H

)

Sep

arat

ion

V

apo

r p

ress

ure

, h

eat

of

vap

ori

zati

on

, b

oil

ing

po

int

Sep

arat

ion

N

D

F a

nal

ysis

2

ph

M,

PC

(VL

), P

T(V

L),

P

S(V

L),

ES

(C),

ES

(H))

Sep

arat

ion

M

ola

r vo

lum

e, s

olu

bil

ity

par

amet

er

Sep

arat

ion

N

C

om

po

nen

t af

fin

ity

PT

(MV

L),

PS

(VL

)

Sep

arat

ion

V

an d

er W

aals

vo

lum

e, c

riti

cal

tem

p

Sep

arat

ion

N

C

om

po

nen

t af

fin

ity

PT

(MV

V),

PS

(VV

)

Sep

arat

ion

S

olu

bil

ity

par

amet

er,

rad

ius

of

gyr

atio

n,

mo

lar

volu

me

Sep

arat

ion

N

C

om

po

nen

t af

fin

ity

PT

(ML

L),

PS

(LL

)

14

Insu

ffic

ien

t p

uri

ty

Sep

arat

ion

S

olu

bil

ity

par

amet

er,

mel

tin

g p

oin

t S

epar

atio

n

N

DF

an

alys

is

PT

(LS

), P

S(L

S),

ES

(C/H

)

Sep

arat

ion

M

ola

r vo

lum

e, s

olu

bil

ity

par

amet

er

Sep

arat

ion

N

C

om

po

nen

t af

fin

ity

PT

(MV

L),

PS

(VL

)

S

epar

atio

n

Van

der

Waa

ls v

olu

me,

cri

tica

l te

mp

S

epar

atio

n

N

Co

mp

on

ent

affi

nit

y P

T(M

VV

), P

S(V

V)

S

epar

atio

n

So

lub

ilit

y p

aram

eter

, ra

diu

s o

f g

yrat

ion

, m

ola

r vo

lum

e S

epar

atio

n

N

Co

mp

on

ent

affi

nit

y P

T(M

LL

), P

S(L

L)

Ap

pen

dic

es

18

8

C.3

: Id

en

tifi

cati

on

of

pri

nci

ple

PB

Bs

(KB

3.1)

Pro

pe

rty

T

hre

sho

ld

va

lue

s P

oss

ible

Fe

ed

p

ha

se

Pri

nci

ple

SP

B o

r P

BB

s P

oss

ible

ou

tle

t p

ha

se

Ag

en

t a

dd

ed

So

lub

ilit

y p

aram

eter

1.

11

V

PT

(VL

), P

S(V

L)

V

MS

A (

L)

0.0

0

L

2p

hM

, P

C(V

L),

PT

(VL

), P

S(V

L)

V a

nd

L

MS

A(V

)

Aze

otr

op

e Y

es

V a

nd

/or

L

2p

hM

, P

C(V

L),

PT

(VL

), P

S(V

L)

V,

L a

nd

LL

M

SA

(L

), E

SA

P

C(L

L),

PS

(LL

)

V a

nd

/or

L

2p

hM

, P

C(V

L),

PT

(VL

), P

S(V

L),

ES

(C),

ES(

H)

V a

nd

L

MS

A (

L),

ES

A

V a

nd

/or

L

PT

(MV

V),

PS

(VV

) V

E

SA

Rel

ativ

e vo

lati

lity

<

=1.

05

L

PC

(LL

), P

T(L

L),

PS

(LL

) L

M

SA

(L

)

V a

nd

/or

L

PT

(ML

L),

PS

(LL

) L

E

SA

V a

nd

/or

L

PC

(LS

/VS

), P

S(L

S/V

S)

V a

nd

/or

L

MS

A (

S)

V a

nd

/or

L

PT

(MV

L),

PS

(VL

) V

an

d L

E

SA

Aze

otr

op

e an

d

Pre

ssu

re s

ensi

tive

sy

stem

Y

es

V a

nd

/or

L

2p

hM

, P

C(V

L),

PT

(VL

), P

S(V

L),

ES

(D),

ES

(C),

ES

(H)

V a

nd

L

ES

A

Mel

tin

g p

oin

t 1.

20

L

P

T(L

S),

PS

(LS

), E

S(C

/H)

S a

nd

L a

nd

/or

V

ES

A

Bo

ilin

g p

oin

t,

1.2

3 V

an

d/o

r L

P

T(V

L),

PS(

VL

) V

an

d L

E

SA

V

apo

r p

ress

ure

10

.00

Tri

ple

po

int

tem

per

atu

re

30.0

0

V

PT

(VS

), P

S(V

S)

V a

nd

/or

S

ES

A

Tri

ple

po

int

pre

ssu

re

1.10

Van

der

Waa

ls v

olu

me

1.0

7 V

an

d/o

r L

P

T(M

VV

), P

S(V

V)

V

ES

A

Cri

tica

l te

mp

1.

10

So

lub

ilit

y p

aram

eter

1.

20

V a

nd

/or

L

PT

(ML

L),

PS

(LL

) L

E

SA

R

adiu

s o

f g

yrat

ion

1.

01

Mo

lar

volu

me

1.0

2

Ap

pen

dic

es

18

9

Mo

lecu

lar

dia

met

er

2.0

0

Liq

uid

P

C(L

S),

PS

(LS

) L

an

d S

-

Mo

lecu

lar

wei

gh

t 1.

90

Mo

lar

volu

me

1.0

2

V a

nd

/or

L

PT

(MV

L),

PS

(VL

) V

an

d L

E

SA

S

olu

bil

ity

par

amet

er

1.0

0

Tri

ple

po

int

tem

per

atu

re

30.0

0

S

PT

(VS

), P

S(V

S)

V a

nd

/or

S

ES

A

Tri

ple

po

int

pre

ssu

re

1.10

Mo

lecu

lar

dia

met

er

2.0

0

L

PC

(LS

), P

S(L

S)

L a

nd

S

- M

ole

cula

r w

eig

ht

1.7

0

Bo

ilin

g p

oin

t,

1.0

1

Liq

uid

, L

iqu

id

and

Vap

or

2p

hM

, P

C(V

L),

PT

(VL

), P

S(V

L),

ES

(C),

ES(

H)

V a

nd

L

ES

A

Vap

or

pre

ssu

re

1.0

5

Aze

otr

op

e N

o

Van

der

Waa

ls v

olu

me

1.0

7 V

an

d/o

r L

P

C(L

S/V

S),

PS

(LS

/VS

) V

M

SA

(S

)

Kin

etic

dia

met

er

1.0

5

V

PC

(VL

), P

S(V

L)

V a

nd

L

MS

A (

L)

En

do

ther

mic

rea

ctio

n

Hig

h

V a

nd

/or

L

and

/or

S

M,

ES

(D)

V a

nd

/or

L

and

/or

S

ES

A

Ap

pen

dic

es

19

0

C.4

: T

ran

sla

tio

n o

f b

asi

c st

ruct

ure

s to

un

it o

pe

rati

on

s (K

B3.

2)

(ex

pa

nd

ed

fro

m L

utz

e,

20

12 a

nd

Ba

bi,

20

14)

SP

B w

ith

in b

asi

c st

ruct

ure

T

ask

R

ea

ctio

n/S

ep

ara

tio

n

un

it-o

pe

rati

on

Scr

ee

nin

g 1

:

Fe

ed

ph

ase

Scr

ee

nin

g 2

: M

SA

-Y/N

S

cre

en

ing

3:

Az

eo

tro

pe

Scr

ee

nin

g 4

:

No

. o

f o

utl

ets

M=

R=

R

eact

ion

R

eact

or

S,

gas

(V

) an

d/o

r L

Y

/N

N

1

=R

=E

S(D

) R

eact

ion

M

icro

wav

e re

acto

r S

, g

as (

V)

and

/or

L

Y/N

N

1

=R

=E

S(D

) R

eact

ion

U

ltra

sou

nd

rea

cto

r S

, g

as (

V)

and

/or

L

Y/N

N

1

=R

=E

S(D

) R

eact

ion

S

on

och

emic

al r

eact

or

S,

gas

(V

) an

d/o

r L

Y

/N

N

1

=P

T(V

L)=

PS

(VL

)/E

S(C

/H)

Sep

arat

ion

P

arti

al c

on

den

sati

on

or

vap

ori

zati

on

V

an

d/o

r L

N

N

1

=P

T(V

L)=

PS

(VL

) S

epar

atio

n

Fla

sh v

apo

riza

tio

n

L

N

N

2

=2

ph

M=

PC

(VL

)=P

T(V

L)=

PS(

VL

) S

epar

atio

n

Dis

till

atio

n

V a

nd

/or

L

N

Y/N

2

=P

C(L

L)=

PT

(LL

)=P

S(L

L)

Sep

arat

ion

L

iqu

id–

liq

uid

ext

ract

ion

L

Y

Y

2

=2

ph

M=

PC

(VL

)=P

T(V

L)=

PS(

VL

) S

epar

atio

n

Kai

bel

Co

lum

n

V a

nd

/or

L

Y/N

Y

/N

4

=2

ph

M=

PC

(VL

)=P

T(V

L)=

PS(

VL

) S

epar

atio

n

Eva

po

rati

on

L

N

N

1

=2

ph

M=

PC

(VL

)=P

T(V

L)=

PS(

VL

) S

epar

atio

n

Div

idin

g W

all

Co

lum

n

V a

nd

/or

L

N

N

3

=P

C(L

L)=

PS(

LL

) S

epar

atio

n

Dec

ante

r L

N

Y

/N

2

=P

T(L

S)=

PS

(LS

),P

T(M

LL

/MV

L/M

VV

)=P

S(L

L)/

E

S(H

/C)

Sep

arat

ion

M

emb

ran

e cr

ysta

lliz

atio

n

L

N

N

3

=P

T(M

VV

)=P

S(V

V)

Sep

arat

ion

M

emb

ran

e-V

apo

r-p

erm

eati

on

V

N

Y

2

=P

T(V

L)=

PS

(VL

) S

epar

atio

n

Ab

sorp

tio

n

Gas

or

V

Y

Y/N

2

=2

ph

M=

PC

(VL

)=P

T(V

L)=

PS

(VL

), E

S(C

/H)

Sep

arat

ion

E

xtra

ctiv

e d

isti

llat

ion

V

an

d/o

r L

Y

Y

/N

2

=P

C(V

L)=

PS

(VL

) S

epar

atio

n

Ad

sorp

tio

n

V a

nd

/or

L

Y

Y/N

2

=P

C(L

S/V

S)=

PS

(LS

/VS

) S

epar

atio

n

Mo

lecu

lar

siev

e ad

sorp

tio

n

V

Y

Y/N

2

=P

T(M

VL

)=P

S(V

L)

Sep

arat

ion

P

erva

po

rati

on

mem

bra

ne

L

N

Y/N

2

=P

T(M

VV

)=P

S(V

V)

Sep

arat

ion

V

apo

r p

erm

eati

on

m

emb

ran

e V

N

Y

/N

2

Ap

pen

dic

es

19

1

=P

T(M

LL

)=P

S(L

L)

Sep

arat

ion

L

iqu

id-l

iqu

id m

emb

ran

e L

N

Y

/N

2

=P

T(L

S)=

PS

(LS

)/E

S(C

/H)

Sep

arat

ion

C

ryst

alli

zati

on

L

Y

/N

N

2

=P

T(V

L)=

PS

(VL

), P

C(L

S),

ES

(H)

Sep

arat

ion

D

ryin

g

L a

nd

S

N

N

2

=P

C(L

L)=

PS(

LL

), E

S(D

) S

epar

atio

n

Cen

trif

ug

al l

iqu

id-l

iqu

id

con

tact

ors

L

an

d/o

r S

N

N

2

=P

T(V

L)=

PS

(VL

), P

C(L

S),

ES

(D)

Sep

arat

ion

M

icro

wav

e d

ryin

g

L a

nd

S

N

N

2

=2

ph

M=

PC

(VL

)=P

T(V

L)=

PS(

VL

), E

S(C

/H/D

) S

epar

atio

n

Mic

row

ave

assi

sted

d

isti

llat

ion

V

an

d/o

r L

N

Y

/N

2

=2

ph

M=

PC

(VL

)=P

T(V

L)=

PS(

VL

),

=P

T(M

VL

/MV

V/M

LL

)=P

S(L

L,V

V),

ES

(C/H

) S

ep.

+ S

ep.

Mem

bra

ne

dis

till

atio

n

V a

nd

/or

L

N

Y/N

3

=P

C(V

L/V

S/L

S)=

PS

(VL

/VS

/LS

) S

ep.

+ S

ep.

Mu

lti

adso

rpti

on

co

lum

n

V a

nd

or

L

Y

Y/N

3

=2

ph

M=

PC

(VL

)=P

T(V

L)=

PS(

VL

),

=P

C(L

S)=

PS

(LS

), E

S(C

/H)

Sep

. +

Sep

. A

dso

rpti

ve d

isti

llat

ion

V

an

d o

r L

Y

Y

/N

3

=P

T(V

L)=

PS

(VL

),

=P

C(V

L/L

S/V

S)=

PS

(VL

/LS

/VS

) S

ep.

+ S

ep.

Ad

sorp

tive

fla

sh

V a

nd

or

L

Y

Y/N

3

=2

ph

M=

R=

PC

(VL

)=P

T(V

L)=

PS

(VL

) R

eact

ion

+S

epar

atio

n

Rea

ctiv

e D

isti

llat

ion

V

an

d/o

r L

N

Y

/N

2

=2

ph

m=

R=

PC

(LL

)=P

S(L

L)

Rea

ctio

n +

Sep

arat

ion

R

eact

ive

extr

acti

on

co

lum

n

V a

nd

/or

L

N

Y/N

2

=2

ph

M=

R=

PC

(VL

)=P

T(V

L)=

PS

(VL

) R

eact

ion

+S

epar

atio

n

Rea

ctiv

e D

ivid

ing

Wal

l C

olu

mn

V

an

d/o

r L

N

N

3

=R

==

PC

(VL

/VS

/LS

)=P

S(V

L/V

S/L

S)

Rea

ctio

n +

Sep

arat

ion

R

eact

ive

adso

rpti

on

co

lum

n

V a

nd

/or

L

Y

Y/N

2

=R

=P

T(M

LL

)=P

S(L

L)

Rea

ctio

n +

Sep

arat

ion

M

emb

ran

e (l

iqu

id-l

iqu

id)

reac

tor

V a

nd

/or

L

N

Y/N

2

=R

=P

T(M

VV

)=P

S(V

V)

Rea

ctio

n +

Sep

arat

ion

M

emb

ran

e (v

apo

r p

erm

eati

on

) re

acto

r V

an

d/o

r L

N

Y

/N

2

=R

=P

T(M

VL

)=P

S(V

L)

Rea

ctio

n +

Sep

arat

ion

M

emb

ran

e (P

erva

po

rati

on

) re

acto

r V

an

d/o

r L

N

Y

/N

2

=R

=P

C(L

S)=

PS

(LS

) R

eact

ion

+ S

epar

atio

n

Mem

bra

ne

Rea

cto

r (b

io)

L a

nd

/or

S

N

Y/N

2

=2

ph

M=

R=

PC

(VL

)=P

T(V

L)=

PS

(VL

),

=P

T(V

L/L

S/V

S)=

PS

(VL

/LS

/VS

), E

S(C

/H)

Rea

ctio

n +

Sep

. +

Sep

. A

dso

rpti

ve r

eact

ive

dis

till

atio

n

V a

nd

/or

L

Y

Y/N

3

=R

=P

C(V

L)=

PS

(VL

)=P

T(V

L),

PT

(MV

L)

Rea

ctio

n +

Sep

. +

Sep

. M

emb

ran

e re

acti

ve

dis

till

atio

n

V a

nd

/or

L

N

Y/N

3

Appendices

192

Appendix D

D.1: Simple mass balance models

o Mixer model: The mass balance model for a mixer consisting of N streams and a single

outlet is as follows:

𝜇𝑖,𝑁𝑀+1= ∑ 𝜇𝑖,𝑗

𝑁𝑚

𝑗=1

Here, μ is the molar flowrate, i denotes the components, j denotes the stream number

while Nm is the number of inlet streams. An example of mixer is shown in Figure D.1.1.

Figure D.1.1: Connections for a mixer

o Reactor model: The mass balance model for a reactor is as follows:

𝜇𝑖,𝑗+1 = 𝜇𝑖,𝑗 + ∑ 𝛾𝑟,𝑖 η𝑟 𝜇𝑖,𝑗

𝑟

Here, 𝛾 is the stoichiometric coefficient, η is the reaction conversion and r denotes the

reactor. An example of reactor is shown in Figure D.1.2.

Figure D.1.2: Connections for a reactor

o Splitter model: The splitter model is generally used to represent the separation unit

operations. This mainly requires the separation factors to calculate the mass balance. The

mass balance equations for a splitter with multiple outlet is as follows:

𝜇𝑖,𝑗+1 = 휀𝑖,𝑗 𝜇𝑖,𝑗

𝜇𝑖,𝑁𝑆 = (1 − ∑ 휀𝑖,𝑗

𝑗

𝑗=1

)𝜇𝑖,𝑗

Here, 휀𝑖,𝑗 denotes the separation factor while NS is the number of streams. An example

of splitter is shown in Figure D.1.3.

µI,j

µI,j+Nm

µI,Nm+1Mixer

µI,j µI,j+1 Reactor

Appendices

193

Figure D.1.3: Connections for a splitter

o Divider model: This model can be used for recycle or purge streams where the

composition of all inlet and outlet streams is same. The mass balance equations for the

divider are as follows:

𝜇𝑖,𝑗+1 = 𝛿𝑖,𝑗 𝜇𝑖,𝑗

𝜇𝑖,𝑁𝑆 = (1 − ∑ 𝛿𝑖,𝑗

𝑗

𝑗=1

)𝜇𝑖,𝑗

Here, 𝛿 denotes split fraction. The example of divider is same as splitter in Figure D.1.3.

D.2: Recovery, purity factors and process conditions (adapted from Tula, 2016)

This section of Appendix D provides the values that are used to calculate the mass balance for

generated process alternatives. In case of other unit-operations including intensified options are

calculated based on knowledge based insights.

Unit-operation Recovery Process conditions

Reactor - Reaction conditions

Distillation column

Key component – 0.998, others – 1.00 (above and below key component)

Top – Bubble point (Dew point for non-condensable),

Bottom – bubble point

Crystallizer Key component – 0.999

(purity) Based on melting points

Liquid membrane Key component – 0.995 Same as inlet Vapor permeation membrane

Key component – 0.995 Permeate at bubble point

temperature of key component

Gas membrane Key component – 0.99 Same as inlet

Pervaporation membrane

Key component – 0.99 Permeate at bubble point

temperature of key component

Adsorption Key component – 0.99 Same as inlet/ΔT of 10 OC

Liquid-liquid extraction

Key component – 0.99 Same as inlet

Extractive distillation

Key component – 0.995, others – 1.00 (above and below key component)

Top – Bubble point (Dew point for non-condensable),

Bottom – bubble point

µI,j

µI,1 Splitter

µI,j+NS

Appendices

194

Appendix E: Production of DME case study

E.1: Generated feasible flowsheet alternatives

Level 1 Alternative

No. A->BC---ABC A/BC B/C

1 Reactor Adsorption (MSA(S)) Flash

2 Reactor Adsorption (MSA(S)) Vapor permeation membrane

3 Reactor Adsorption (MSA(S)) Distillation

4 Reactor Adsorption (MSA(S)) Adsorption (MSA(S))

A->BC---ABC B/CA C/A

6 Reactor Flash Crystallization

7 Reactor Flash Liquid membrane

8 Reactor Flash Pervaporation membrane

9 Reactor Flash Distillation

10 Reactor Flash Adsorption (MSA(S))

11 Reactor Distillation Crystallization

12 Reactor Distillation Liquid membrane

13 Reactor Distillation Pervaporation membrane

14 Reactor Distillation Distillation

15 Reactor Distillation Adsorption (MSA(S))




A->BC---ABC C/AB B/A

19 Reactor Distillation Flash

20 Reactor Distillation Vapor permeation membrane

21 Reactor Distillation Distillation

22 Reactor Distillation Adsorption (MSA(S))

23 Reactor Adsorption (MSA(S)) Flash




27 Reactor Flash Flash

28 Reactor Flash Distillation

29 Reactor Flash Adsorption (MSA(S))

Level 2 Alternative

No. A->BC---ABC A/BC---B/C

30 Reactor Membrane (vapor) distillation

Appendices

195

31 Reactor Membrane (vapor) adsorption-both

32 Reactor Adsorptive distillation

33 Reactor Multi-stage adsorption

A->BC---ABC B/CA---C/A

34 Reactor Flash crystallization

35 Reactor Flash Membrane (liquid)

36 Reactor Flash distillation

37 Reactor Flash adsorption

38 Reactor Membrane (vapor) distillation


40 Reactor Distillation Membrane (vapor-liquid)

41 Reactor Distillation Membrane (liquid)

42 Reactor Divided wall column

43 Reactor Adsorptive distillation - both


A->BC---ABC C/BA---B/A

45 Reactor Flash membrane (vapor)

46 Reactor Membrane (vapor) distillation-both


48 Reactor Flash distillation

49 Reactor Adsorptive distillation-both

50 Reactor Divided wall column

51 Reactor Flash adsorption


A->BC---ABC----A/BC B/C

53 Membrane (vapor) reactor Flash

54 Membrane (vapor) reactor Vapor permeation membrane

55 Membrane (vapor) reactor Distillation

56 Membrane (vapor) reactor Adsorption (MSA(S))

57 Reactive adsorption Flash

58 Reactive adsorption Vapor permeation membrane

59 Reactive adsorption Distillation

60 Reactive adsorption Adsorption (MSA(S))

A->BC---ABC----B/CA C/A




64 Reactive distillation Crystallization

65 Reactive distillation Liquid membrane

Appendices

196

66 Reactive distillation Pervaporation membrane

67 Reactive distillation Distillation

68 Reactive distillation Adsorption (MSA(S))




A->BC---ABC----C/AB B/A

71 Membrane (vapor) reactor Flash




75 Reactive distillation Flash

76 Reactive distillation Distillation

77 Reactive adsorption Flash




Level 3

Alternative No.

A->BC---ABC----A/B/C

81 Reactive membrane(vapor) distillation

82 Reactive membrane(vapor) adsorption

83 Reactive adsorptive distillation

84 Reactive multi-stage adsorption

85 Reactive divided wall distillation

A->BC---B/C

86 Membrane reactor (vapor permeation)

87 Reactive distillation

88 Reactive adsorption

E.2: Membrane data for vapor permeation of water (Lee et al., 2004)

Vapor permeation

membrane details

Water flux 0.037 kmol/m2/min

MeOH flux 2.02E-07 kmol/ m2/min

Selectivity (Water : MeOH) 100:1 -

Membrane area Alternative 81 142.38 m2

Alternative 74 142.51 m2

E.3: Adsorption data for adsorption of MeOH (Rao et al., 2007) – Alternative 74

Adsorbent

capacity (w/w) 14.03

Adsorbent

required 1798.81 kg/12 hr

Appendices

197

Appendix F: Hydrodealkylation (HDA) of toluene case study

F.1: Overview of analysis for existing process flowsheet (base case) (Tula, 2016)

Figure F.1.1: Utility cost for HDA base case flowsheet

Figure F.1.2: Carbon footprint for HDA base case flowsheet

Table F.1.1: Sustainability analysis for HDA base case flowsheet

Path Component Flow-rate (kg/h) MVA (103$/yr) EWC (103$/yr) TVA(103$/yr)

OP 2 H2 283.23 -3258.98 34.04 -3293.03

OP 7 Methane 2005.51 -9843.81 8.88 -9852.69

CP 9 Toluene 4094.35 - 662.76 -

15

,3

0,0

13

,8

2,0

0,3

68

,5

UTI

LITY

CO

ST %

EQUIPMENT UNIT OPERATION

T1-RB T1-CD T2-RB T2-CD CRZ HEXC

O2

EQU

IVA

LEN

T

EQUIPMENT UNIT OPERATION

HEX T1-RB T1-CD T2-RB T2-CD CRZ

Appendices

198

OP 2 – H2 Feed -> HEX -> REC -> HEX -> FLSH -> PUR ->

OP 7 – CH4 Feed -> HEX -> REC -> HEX -> FLSH -> PUR ->

CP 9 – T1 -> T2 -> REC -> CRY -> HEX -> REC -> HEX-> FLS -> T1

Here, OP is open path, while CP is close path. H2: Hydrogen, CH4: Methane, HEX: Heat

exchanger, REC: reactor, FLSH: Flash, PUR: Purge, T1: Distillation column 1, T2: Distillation

column 2, CRY: Crystallizer

Table F.1.2: LCA indicators for HDA base case flowsheet

Indicator Impact factor

HTPI 51.05

HTPE 47.48

ATP 59.20

GWP 7.90

Appendices

199

F.2: Level 2 phenomena based superstructure of alternatives

A + C B + D

2D A + E

--ABCDE--

M=2phM=R(V)=ES(C) V

AB/CDE---C/ED

M=P T(MVV)=PS(V V)


AB/CDE---CD/E

M=PT(VL)=PS(VL)

M=PT(MVL)=PS(VL)

M=PT(VL)=PS(VL)

M=2phM=E S(C)=P C(V L)=P T(VL)=PS(VL)

M=2phM=P C(V L)=P T(VL)=PS(VL)


M=PT(VL)=PS(VL)

M=PT(MVV)=PS(VV)

M=PT(VL)=PS(VL)


M=PT(MVV)=PS(VV)



M=2phM=E S(H)=P C(V L)=P T(VL)=PS(VL)

M=PT(MVL)=PS(VL)













M=PT(MVV)=PS(VV)


M=PC(VS/LS)=P S(VS/LS)**

M=PT(MVL)=PS(VL)


AB/CDE---D/EC

M=PT(VL)=PS(VL)

M=PT(MVL)=PS(VL)

M=PT(MVV)=PS(VV)


M=PT(MVL)=PS(VL)


M=PC(VS/LS)=PS(VS/LS)**

M=PT(VL)=PS(VL)




M=PT(VL)=PS(VL)


M=PT(VL)=PS(VL)

M=PT(MVV)=PS(VV)

M=PT(MVV)=PS(VV)











M=2phM=PC(VL)=PT(V L)=P S(VL


AB/CDE---C/DE

M=P T(VL)=PS(VL)

M=PT(MV L)=P S(VL)

M=P T(VL)=PS(VL)

M=PC(VS/LS)=P S(VS/LS)*

M=PT(MVV)=P S(VV)

M=PC(VS/VL)=PS(VS/VL)*

M=2phM=ES(C)=PC(VL)=PT(V L)=P S(VL)

M=2phM=PC(VL)=PT(V L)=P S(VL)

M=2phM=ES(H)=PC(VL)=PT(V L)=P S(VL)

M=PT(MVL)=P S(VL)




M=2phM=PC(VL)=PT(VL)=PS(V L


M=PT(MVL)=PS(VL)


M=PC(VS/LS)=PS(V S/LS)**

D/E

M=PT(VL)=PS(VL)

M=P T(MVV)=PS(VV)

M=PC(LS)=PS(LS)

M=PT(MVL)=PS(V L)

M=2phM=ES(C)=PC(VL)=PT(VL)=PS(V L)

M=2phM=PC(VL)=PT(VL)=PS(V L)

M=2phM=ES(H)=PC(VL)=PT(VL)=PS(V L)


M=PT(LS)=PS(LS)

M=ES(C)

C/D

M=PT(LS)=P S(LS)

M=ES(C)

M=PT(MVL)=PS(V L)





M=PC(LL)=PT(LL)PS(LL)*

M=2phM=E S(C)=P C(VL)=PT(VL)=PS(VL)

M=2phM=P C(V L)=P T(VL)=PS(VL)*


C/E

M=PT(VL)=PS(VL)

M=P T(MVV)=PS(VV)

M=PT(MV L)=P S(VL)





M=PT(LS)=PS(LS)

M=ES(C)

Reaction taskSeparation-

Separation taskSeparation task

Level 2a

V-L

V-L

V-V

V-L

V-L

V-L

V-L

V-V

V-L

V-L

V-V

V-L

V-L

V-L

V-L

V-L

V-V

V-L

V-L

V-L

V-L

V-L

V-V

V-V

V-L

V-L

V-V

V-L

V-L

Appendices

200

C/DE

C/ED

D/E

C/D

M=PT(MVV)=PS(VV)

M=PT(MVL)=PS(VL)

M=PC(VL/V S/LS)=PS(VL/VS/LS)*

M=P T(LS)=PS(LS)

M=ES(C/H)

M=PT(MV L)=P S(VL)




M=PC(V L/VS/LS)=P S(VL/VS/LS)*

D/EC

M=PT(VL)=PS(VL)

M=PT(MVV)=P S(VV)

M=PC(LS)=PS(LS)

M=PT(MVL)=PS(VL)




CD/E

M=PT(VL)=P S(VL)

M=P T(MVV)=PS(V V)

M=PC(LS)=PS(LS)

M=PT(MV L)=P S(VL)


M=2phM=PC(VL)=PT(V L)=PS(VL)



M=PT(LS)=P S(LS)

M=ES(C)

M=P T(VL)=PS(VL)

M=PT(MVV)=P S(VV)

M=PC(LS)=PS(LS)

M=PT(MVL)=PS(VL)





M=P T(LS)=PS(LS)

M=ES(C/H)

C/E

M=PT(VL)=PS(VL)

M=PT(MVV)=PS(VV)

M=PT(MVL)=PS(V L)





M=PT(LS)=PS(LS)

M=E S(C)


M=2phM=E S(C)=P C(V L)=PT(VL)=PS(VL)

M=2phM=PC(VL)=PT(VL)=PS(VL)*

M=2phM=E S(H)=P C(V L)=PT(VL)=PS(VL)

D/CE


M=2phM=ES(C)=PC(VL)=PT(VL)=P S(VL)


M=2phM=ES(H)=PC(VL)=PT(VL)=P S(VL)





M=PT(LS)=PS(LS)

M=E S(C)

V-V

A + C B + D

2D A + E

--ABCDE—AB/CDE

M=2phM=R(V)=E S(C)

M=P T(MVV)=PS(VV)


M=2phM=R(V)=PC(VL)=PT(V L)=PS(VL)


M=2phM=R(V)=ES(C)


M=PC(VL/VS/LS)=PS(V L/VS/LS)*

Reaction-Separation

taskSeparation task Separation task

Level 2b

V-L

V-V

L-S

V-L

V-L/V-V

L-L

V-L

V-V

L-S

V-L

V-V

L-S

V-L

V-L

V-L/V-V

L-L

V-L

V-L/V-V

V-L

V-V

L-S

V-L

V-L

Appendices

201

A + C B + D

2D A + E

--ABCDE--

M=2phM=R(V)=ES(C)

AB/CDE

M=PT(VL)=PS(VL)

M=PT(MVV)=PS(VV)




M=PC(VS)=PS(VS)*

V

M=PT(LS)=PS(LS)

M=ES(C)

M=PT(MV L)=PS(V L)

M=PT(LS)=PS(LS)

M=ES(C)

M=PC(VS/LS)=PS(V S/LS)*

M=PT(VL)=PS(VL)

M=PT(MV L)=PS(V L)

M=PT(VL)=PS(VL)

M=2phM=E S(C)=PC(VL)=PT(VL)=PS(VL)


M=2phM=E S(H)=PC(VL)=PT(VL)=PS(VL)

M=PT(VL)=PS(VL)


D/EC---C/E

M=PT(MVL)=PS(VL)




M=PT(MV L)=PS(V L)


M=2phM=ES(C)=P C(V L)=P T(V L)=P S(V L)

M=2phM=PC(VL)=P T(VL)=P S(VL)



M=2phM=ES(H)=P C(V L)=P T(V L)=P S(V L)




M=PT(MVV)=PS(V V)

M=PT(MVV)=PS(V V)


M=PT(LS)=PS(LS)

M=ES(C)

M=P T(MVL)=PS(VL)

M=PT(LS)=PS(LS)

M=ES(C)


M=PT(VL)=PS(VL)

M=PT(MVL)=PS(VL)

M=PT(VL)=PS(VL)




M=PT(VL)=PS(VL)


CD/E---C/D

M=PT(MVL)=PS(VL)




M=PT(MVL)=PS(VL)













M=2phM=ES(C)=P C(V L)=PT(V L)=PS(V L)


M=2phM=ES(H)=P C(V L)=PT(V L)=PS(V L)

M=P T(MVV)=PS(VV)

M=P T(MVV)=PS(VV)

M=PC(V S/LS)=PS(VS/LS)*

C/DE---D/E

M=P T(LS)=P S(LS)

M=ES(C)

M=P T(MVL)=PS(VL

M=PT(MVL)=PS(VL)




M=PT(MVL)=PS(VL)


M=P T(LS)=P S(LS)

M=ES(C)


M=PC(LS)=P S(LS)








M=PC(LS)=P S(LS)

M=PT(MVL)=PS(VL)

C/ED---D/E




M=PT(MVV)=PS(VV)

M=PT(MVV)=PS(VV)








Reaction taskSeparation-

Separation task

Level 2c

Separation-

Separation task

Separation-

Separation task

V-L

V-V

V-L

V-V

Appendices

202

F.3: Level 3 phenomena-based superstructure of alternatives

C/E

M=PT(VL)=PS(VL)

M=P T(MVV)=PS(VV)

M=PT(MVL)=PS(VL)





M=PT(LS)=PS(LS)

M=ES(C)

A + C B + D

2D A + E

--ABCDE---AB/CDE---C/DE

M=PT(MVV)=PS(VV)

M=2phM=R(V)=ES(C)


M=P T(MVV)=PS(VV)

M=2phM=ES(C)=PC(V L)=P T(V L)=P S(V L)


M=2phM=ES(H)=PC(V L)=P T(V L)=P S(V L)

M=2phM=ES(C)=PC(V L)=P T(V L)=P S(V L)


M=2phM=ES(H)=PC(V L)=P T(V L)=P S(V L)



M=2phM=R(V)=ES(C)


D/E

M=PT(VL)=PS(VL)

M=PT(MVV)=PS(VV)

M=PC(LS)=P S(LS)

M=PT(MVL)=PS(VL)





M=PT(LS)=PS(LS)

M=ES(C)

A + C B + D

2D A + E

--ABCDE---AB/CDE---C/ED

M=PT(MVV)=PS(VV)

M=2phM=R(V)=ES(C)

M=PC(V S/LS)=P S(VS/LS)*

A + C B + D

2D A + E

--ABCDE---AB/CDE---CD/E

M=PT(MVV)=PS(VV)

M=2phM=R(V)=ES(C)


M=PT(MV V)=P S(VV)

M=2phM=ES(C)=P C(V L)=PT(VL)=PS(VL)


M=2phM=ES(H)=P C(V L)=PT(VL)=PS(VL)


M=2phM=PC(V L)=P T(V L)=P S(V L)


M=2phM=PC(V L)=P T(V L)=P S(V L)




M=2phM=ES(H)=P C(V L)=PT(VL)=PS(VL)

M=PT(MVL)=P S(VL)






M=2phM=R(V)=ES(C)

M=PT(MVL)=P S(VL)


M=2phM=R(V)=ES(C)


C/D

M=PT(LS)=PS(LS)

M=ES(C)

M=P T(MVL)=PS(VL)




M=PC(VL/VS/LS)=PS(VL/V S/LS)*



M=2phM=P C(V L)=PT(V L)=PS(V L)*


A + C B + D

2D A + E

--ABCDE---AB/CDE---D/EC

M=PT(MVV)=PS(VV)

M=2phM=R(V)=E S(C)


M=PT(MVV)=PS(VV)


M=2phM=R(V)=P C(VL)=PT(VL)=PS(VL)










M=PT(MVL)=PS(VL)






M=2phM=R(V)=ES(C)


A + C B + D

2D A + E

--ABCDE--

M=2phM=R(V)=ES(C)

AB/CDE---CD/E---C/D

M=PT(MVV)=PS(VV)






M=PT(MVV)=PS(VV)


M=2phM=R(V)=ES(C)







M=PT(MVL)=PS(VL)













AB/CDE---CD/E---C/D


M=2phM=R(V)=ES(C)


M=P T(MVL)=PS(VL)


M=2phM=PC(VL)=P T(V L)=P S(V L)




M=PT(MVL)=PS(VL)






M=P T(MVV)=PS(VV)






M=PT(MVV)=PS(VV)


M=2phM=R(V)=ES(C)


Reaction-Separation-

Separation taskSeparation task

Level 3

Separation-Separation-Separation task

Reaction task

Appendices

203

F.4: Generated feasible flowsheet alternatives

Level 1

ABCDE (A+C--B+D, 2D--A+E) AB/CDE C/DE D/E

1 Reaction Flash distillation Crystallization Melting 2 Reaction Flash distillation Pervaporation membrane Crystallization 3 Reaction Flash distillation Pervaporation membrane Flash 4 Reaction Flash distillation Pervaporation membrane Pervaporation membrane 5 Reaction Flash distillation Pervaporation membrane Distillation 6 Reaction Flash distillation Pervaporation membrane Adsorption (solid MSA) 7 Reaction Flash distillation Adsorption (solid/liquid MSA) Crystallization 8 Reaction Flash distillation Adsorption (solid/liquid MSA) Flash 9 Reaction Flash distillation Adsorption (solid/liquid MSA) Pervaporation membrane 10 Reaction Flash distillation Adsorption (solid/liquid MSA) Distillation 11 Reaction Flash distillation Adsorption (solid/liquid MSA) Adsorption (solid MSA) 12 Reaction Distillation Crystallization Melting 13 Reaction Distillation Pervaporation membrane Crystallization 14 Reaction Distillation Pervaporation membrane Flash 15 Reaction Distillation Pervaporation membrane Pervaporation membrane 16 Reaction Distillation Pervaporation membrane Distillation 17 Reaction Distillation Pervaporation membrane Adsorption (solid MSA) 18 Reaction Distillation Adsorption (solid/liquid MSA) Crystallization 19 Reaction Distillation Adsorption (solid/liquid MSA) Flash 20 Reaction Distillation Adsorption (solid/liquid MSA) Pervaporation membrane 21 Reaction Distillation Adsorption (solid/liquid MSA) Distillation 22 Reaction Distillation Adsorption (solid/liquid MSA) Adsorption (solid MSA) 23 Reaction Adsorption (solid MSA) Crystallization Melting 24 Reaction Adsorption (solid MSA) Pervaporation membrane Crystallization 25 Reaction Adsorption (solid MSA) Pervaporation membrane Flash 26 Reaction Adsorption (solid MSA) Pervaporation membrane Pervaporation membrane 27 Reaction Adsorption (solid MSA) Pervaporation membrane Distillation 28 Reaction Adsorption (solid MSA) Pervaporation membrane Adsorption (solid MSA) 29 Reaction Adsorption (solid MSA) Adsorption (solid/liquid MSA) Crystallization 30 Reaction Adsorption (solid MSA) Adsorption (solid/liquid MSA) Flash 31 Reaction Adsorption (solid MSA) Adsorption (solid/liquid MSA) Pervaporation membrane 32 Reaction Adsorption (solid MSA) Adsorption (solid/liquid MSA) Distillation 33 Reaction Adsorption (solid MSA) Adsorption (solid/liquid MSA) Adsorption (solid MSA)

ABCDE (A+C--B+D, 2D--A+E)

AB/CDE C/ED D/E

34 Reaction Adsorption (solid MSA) Vapor permeation membrane Flash 35 Reaction Adsorption (solid MSA) Vapor permeation membrane Vapor permeation membrane 36 Reaction Adsorption (solid MSA) Vapor permeation membrane Distillation 37 Reaction Adsorption (solid MSA) Vapor permeation membrane Adsorption (solid MSA)

ABCDE (A+C--B+D, 2D--A+E) AB/CDE CD/E C/D

38 Reaction Flash distillation Crystallization Crystallization 39 Reaction Flash distillation Crystallization Pervaporation membrane 40 Reaction Flash distillation Crystallization Distillation 41 Reaction Flash distillation Crystallization Adsorption (solid/liquid MSA) 42 Reaction Flash distillation Flash distillation Crystallization 43 Reaction Flash distillation Flash distillation Pervaporation membrane 44 Reaction Flash distillation Flash distillation Distillation 45 Reaction Flash distillation Flash distillation Adsorption (solid/liquid MSA) 46 Reaction Flash distillation Pervaporation membrane Crystallization 47 Reaction Flash distillation Pervaporation membrane Pervaporation membrane

Appendices

204

48 Reaction Flash distillation Pervaporation membrane Distillation 49 Reaction Flash distillation Pervaporation membrane Adsorption (solid/liquid MSA) 50 Reaction Flash distillation Distillation Crystallization 51 Reaction Flash distillation Distillation Pervaporation membrane 52 Reaction Flash distillation Distillation Distillation 53 Reaction Flash distillation Distillation Adsorption (solid/liquid MSA) 54 Reaction Flash distillation Adsorption (solid MSA) Crystallization 55 Reaction Flash distillation Adsorption (solid MSA) Pervaporation membrane 56 Reaction Flash distillation Adsorption (solid MSA) Distillation 57 Reaction Flash distillation Adsorption (solid MSA) Adsorption (solid/liquid MSA) 58 Reaction Distillation Crystallization Crystallization 59 Reaction Distillation Crystallization Pervaporation membrane 60 Reaction Distillation Crystallization Distillation 61 Reaction Distillation Crystallization Adsorption (solid MSA) 62 Reaction Distillation Flash distillation Crystallization 63 Reaction Distillation Flash distillation Pervaporation membrane 64 Reaction Distillation Flash distillation Distillation 65 Reaction Distillation Flash distillation Adsorption (solid MSA) 66 Reaction Distillation Pervaporation membrane Crystallization 67 Reaction Distillation Pervaporation membrane Pervaporation membrane 68 Reaction Distillation Pervaporation membrane Distillation 69 Reaction Distillation Pervaporation membrane Adsorption (solid MSA) 70 Reaction Distillation Distillation Crystallization 71 Reaction Distillation Distillation Pervaporation membrane 72 Reaction Distillation Distillation Distillation 73 Reaction Distillation Distillation Adsorption (solid MSA) 74 Reaction Distillation Adsorption (solid MSA) Crystallization 75 Reaction Distillation Adsorption (solid MSA) Pervaporation membrane 76 Reaction Distillation Adsorption (solid MSA) Distillation 77 Reaction Distillation Adsorption (solid MSA) Adsorption (solid MSA) 78 Reaction Adsorption (solid MSA) Crystallization Crystallization 79 Reaction Adsorption (solid MSA) Crystallization Pervaporation membrane 80 Reaction Adsorption (solid MSA) Crystallization Distillation 81 Reaction Adsorption (solid MSA) Crystallization Adsorption (solid MSA) 82 Reaction Adsorption (solid MSA) Flash distillation Crystallization 83 Reaction Adsorption (solid MSA) Flash distillation Pervaporation membrane 84 Reaction Adsorption (solid MSA) Flash distillation Distillation 85 Reaction Adsorption (solid MSA) Flash distillation Adsorption (solid MSA) 86 Reaction Adsorption (solid MSA) Vapor permeation membrane Distillation 87 Reaction Adsorption (solid MSA) Vapor permeation membrane Adsorption (solid MSA) 88 Reaction Adsorption (solid MSA) Pervaporation membrane Crystallization 89 Reaction Adsorption (solid MSA) Pervaporation membrane Pervaporation membrane 90 Reaction Adsorption (solid MSA) Pervaporation membrane Distillation 91 Reaction Adsorption (solid MSA) Pervaporation membrane Adsorption (solid MSA) 92 Reaction Adsorption (solid MSA) Distillation Crystallization 93 Reaction Adsorption (solid MSA) Distillation Pervaporation membrane 94 Reaction Adsorption (solid MSA) Distillation Distillation 95 Reaction Adsorption (solid MSA) Distillation Adsorption (solid MSA) 96 Reaction Adsorption (solid MSA) Adsorption (solid MSA) Crystallization 97 Reaction Adsorption (solid MSA) Adsorption (solid MSA) Pervaporation membrane 98 Reaction Adsorption (solid MSA) Adsorption (solid MSA) Distillation 99 Reaction Adsorption (solid MSA) Adsorption (solid MSA) Adsorption (solid MSA)


AB/CDE D/EC C/E

100 Reaction Flash distillation Flash distillation Crystallization

101 Reaction Flash distillation Flash distillation Flash distillation

Appendices

205

102 Reaction Flash distillation Flash distillation Pervaporation membrane 103 Reaction Flash distillation Flash distillation Distillation 104 Reaction Flash distillation Flash distillation Adsorption (solid MSA) 105 Reaction Flash distillation Crystallization Crystallization 106 Reaction Flash distillation Crystallization Flash distillation 107 Reaction Flash distillation Crystallization Pervaporation membrane 108 Reaction Flash distillation Crystallization Distillation 109 Reaction Flash distillation Crystallization Adsorption (solid MSA) 110 Reaction Flash distillation Pervaporation membrane Crystallization 111 Reaction Flash distillation Pervaporation membrane Flash distillation 112 Reaction Flash distillation Pervaporation membrane Pervaporation membrane 113 Reaction Flash distillation Pervaporation membrane Distillation 114 Reaction Flash distillation Pervaporation membrane Adsorption (solid MSA) 115 Reaction Flash distillation Distillation Crystallization 116 Reaction Flash distillation Distillation Flash distillation 117 Reaction Flash distillation Distillation Pervaporation membrane 118 Reaction Flash distillation Distillation Distillation 119 Reaction Flash distillation Distillation Adsorption (solid MSA) 120 Reaction Flash distillation Adsorption (solid MSA) Crystallization 121 Reaction Flash distillation Adsorption (solid MSA) Flash distillation 122 Reaction Flash distillation Adsorption (solid MSA) Pervaporation membrane 123 Reaction Flash distillation Adsorption (solid MSA) Distillation 124 Reaction Flash distillation Adsorption (solid MSA) Adsorption (solid MSA) 125 Reaction Distillation Flash distillation Crystallization 126 Reaction Distillation Flash distillation Flash distillation 127 Reaction Distillation Flash distillation Pervaporation membrane 128 Reaction Distillation Flash distillation Distillation 129 Reaction Distillation Flash distillation Adsorption (solid MSA) 130 Reaction Distillation Crystallization Crystallization 131 Reaction Distillation Crystallization Flash distillation 132 Reaction Distillation Crystallization Pervaporation membrane 133 Reaction Distillation Crystallization Distillation 134 Reaction Distillation Crystallization Adsorption (solid MSA) 135 Reaction Distillation Pervaporation membrane Crystallization 136 Reaction Distillation Pervaporation membrane Flash distillation 137 Reaction Distillation Pervaporation membrane Pervaporation membrane 138 Reaction Distillation Pervaporation membrane Distillation 139 Reaction Distillation Pervaporation membrane Adsorption (solid MSA) 140 Reaction Distillation Distillation Crystallization 141 Reaction Distillation Distillation Flash distillation 142 Reaction Distillation Distillation Pervaporation membrane 143 Reaction Distillation Distillation Distillation 144 Reaction Distillation Distillation Adsorption (solid MSA) 145 Reaction Distillation Adsorption (solid MSA) Crystallization 146 Reaction Distillation Adsorption (solid MSA) Flash distillation 147 Reaction Distillation Adsorption (solid MSA) Pervaporation membrane 148 Reaction Distillation Adsorption (solid MSA) Distillation 149 Reaction Distillation Adsorption (solid MSA) Adsorption (solid MSA) 150 Reaction Adsorption (solid MSA) Flash distillation Crystallization 151 Reaction Adsorption (solid MSA) Flash distillation Flash distillation 152 Reaction Adsorption (solid MSA) Flash distillation Pervaporation membrane 153 Reaction Adsorption (solid MSA) Flash distillation Distillation 154 Reaction Adsorption (solid MSA) Flash distillation Adsorption (solid MSA) 155 Reaction Adsorption (solid MSA) Vapor permeation membrane Flash distillation 156 Reaction Adsorption (solid MSA) Vapor permeation membrane Vapor permeation membrane 157 Reaction Adsorption (solid MSA) Vapor permeation membrane Distillation

Appendices

206

158 Reaction Adsorption (solid MSA) Vapor permeation membrane Adsorption (solid MSA) 159 Reaction Adsorption (solid MSA) Pervaporation membrane Flash distillation 160 Reaction Adsorption (solid MSA) Pervaporation membrane Pervaporation membrane 161 Reaction Adsorption (solid MSA) Pervaporation membrane Distillation 162 Reaction Adsorption (solid MSA) Pervaporation membrane Adsorption (solid MSA) 163 Reaction Adsorption (solid MSA) Distillation Crystallization 164 Reaction Adsorption (solid MSA) Distillation Flash distillation 165 Reaction Adsorption (solid MSA) Distillation Pervaporation membrane 166 Reaction Adsorption (solid MSA) Distillation Distillation 167 Reaction Adsorption (solid MSA) Distillation Adsorption (solid MSA) 168 Reaction Adsorption (solid MSA) Adsorption (solid MSA) Flash distillation 169 Reaction Adsorption (solid MSA) Adsorption (solid MSA) Distillation 170 Reaction Adsorption (solid MSA) Adsorption (solid MSA) Adsorption (solid MSA)

Level 2a


AB/CDE C/DE---D/E

171 Reaction Flash distillation Membrane (pervaporation) crystallization 172 Reaction Flash distillation Membrane distillation (pervaporation) 173 Reaction Flash distillation Membrane adsorption (pervaporation) 174 Reaction Flash distillation Adsorption (solid MSA) crystallization 175 Reaction Flash distillation Membrane adsorption (pervaporation) 176 Reaction Flash distillation Adsorptive (solid MSA) distillation 177 Reaction Flash distillation Multi stage adsorption 178 Reaction Vapor permeation membrane Membrane crystallization (pervaporation) 179 Reaction Vapor permeation membrane Membrane distillation (pervaporation) 180 Reaction Vapor permeation membrane Membrane adsorption (pervaporation) 181 Reaction Vapor permeation membrane Adsorption (solid MSA) crystallization 182 Reaction Vapor permeation membrane Membrane adsorption (pervaporation) 183 Reaction Vapor permeation membrane Adsorptive (solid MSA) distillation 184 Reaction Vapor permeation membrane Multi stage adsorption 185 Reaction Distillation Membrane crystallization (pervaporation) 186 Reaction Distillation Membrane distillation (pervaporation) 187 Reaction Distillation Membrane adsorption (pervaporation) 188 Reaction Distillation Adsorption (solid MSA) crystallization 189 Reaction Distillation Membrane adsorption (pervaporation) 190 Reaction Distillation Adsorptive (solid MSA) distillation 191 Reaction Distillation Multi stage adsorption 192 Reaction Adsorption (solid MSA) Membrane crystallization (pervaporation) 193 Reaction Adsorption (solid MSA) Membrane distillation (pervaporation) 194 Reaction Adsorption (solid MSA) Membrane adsorption (pervaporation) 195 Reaction Adsorption (solid MSA) Adsorption (solid MSA) crystallization 196 Reaction Adsorption (solid MSA) Membrane adsorption (pervaporation) 197 Reaction Adsorption (solid MSA) Adsorptive (solid MSA) distillation 198 Reaction Adsorption (solid MSA) Multi stage adsorption

ABCDE (A+C--B+D, 2D--A+E) AB/CDE C/ED---D/E

199 Reaction Vapor permeation membrane Membrane distillation (vapor permeation) 200 Reaction Vapor permeation membrane Membrane adsorption (vapor permeation) 201 Reaction Adsorption (solid MSA) Membrane distillation (vapor permeation) 202 Reaction Adsorption (solid MSA) Membrane adsorption (vapor permeation)

203 Reaction Adsorption (solid MSA) Membrane distillation (vapor permeation) 204 Reaction Adsorption (solid MSA) Membrane adsorption (vapor permeation)


AB/CDE CD/E---C/D

Appendices

207

205 Reaction Flash distillation Membrane crystallization (pervaporation) 206 Reaction Flash distillation Membrane crystallization (pervaporation) 207 Reaction Flash distillation Adsorption (solid MSA) crystallization 208 Reaction Flash distillation Membrane flash 209 Reaction Flash distillation Flash distillation 210 Reaction Flash distillation Adsorptive flash 211 Reaction Flash distillation Membrane crystallization (pervaporation) 212 Reaction Flash distillation Membrane distillation (pervaporation) 213 Reaction Flash distillation Membrane adsorption (pervaporation) 214 Reaction Flash distillation Membrane distillation (pervaporation) 215 Reaction Flash distillation Divided wall distillation 216 Reaction Flash distillation Adsorptive distillation 217 Reaction Flash distillation Adsorption (solid MSA) crystallization 218 Reaction Flash distillation Membrane adsorption (pervaporation) 219 Reaction Flash distillation Adsorptive distillation 220 Reaction Flash distillation Multi stage adsorption 221 Reaction Vapor permeation membrane Membrane flash (vapor permeation) 222 Reaction Vapor permeation membrane Flash distillation 223 Reaction Vapor permeation membrane Adsorptive flash 224 Reaction Vapor permeation membrane Membrane distillation (vapor permeation) 225 Reaction Vapor permeation membrane Membrane adsorption (vapor permeation) 226 Reaction Vapor permeation membrane Membrane distillation (pervaporation) 227 Reaction Vapor permeation membrane Divided wall distillation 228 Reaction Vapor permeation membrane Adsorptive distillation 229 Reaction Vapor permeation membrane Adsorption (solid MSA) crystallization 230 Reaction Vapor permeation membrane Membrane adsorption (pervaporation) 231 Reaction Vapor permeation membrane Adsorptive distillation 232 Reaction Vapor permeation membrane Multi stage adsorption 233 Reaction Distillation Membrane crystallization (pervaporation) 234 Reaction Distillation Adsorption (solid MSA) crystallization 235 Reaction Distillation Membrane flash (pervaporation) 236 Reaction Distillation Flash distillation 237 Reaction Distillation Adsorptive flash 238 Reaction Distillation Membrane crystallization (pervaporation) 239 Reaction Distillation Membrane distillation (pervaporation) 240 Reaction Distillation Membrane adsorption (pervaporation) 241 Reaction Distillation Membrane distillation (pervaporation) 242 Reaction Distillation Divided wall distillation 243 Reaction Distillation Adsorptive distillation 244 Reaction Distillation Adsorption (solid MSA) crystallization 245 Reaction Distillation Membrane adsorption (pervaporation) 246 Reaction Distillation Adsorptive distillation 247 Reaction Distillation Multi stage adsorption 248 Reaction Adsorption (solid MSA) Membrane flash 249 Reaction Adsorption (solid MSA) Flash distillation 250 Reaction Adsorption (solid MSA) Adsorptive flash 251 Reaction Adsorption (solid MSA) Membrane distillation (vapor permeation) 252 Reaction Adsorption (solid MSA) Membrane adsorption (vapor permeation) 253 Reaction Adsorption (solid MSA) Membrane crystallization (pervaporation) 254 Reaction Adsorption (solid MSA) Membrane distillation (pervaporation) 255 Reaction Adsorption (solid MSA) Membrane adsorption (pervaporation) 256 Reaction Adsorption (solid MSA) Membrane distillation (pervaporation) 257 Reaction Adsorption (solid MSA) Divided wall distillation 258 Reaction Adsorption (solid MSA) Adsorptive distillation 259 Reaction Adsorption (solid MSA) Adsorption (solid MSA) crystallization 260 Reaction Adsorption (solid MSA) Membrane adsorption (pervaporation)

Appendices

208

261 Reaction Adsorption (solid MSA) Adsorptive distillation 262 Reaction Adsorption (solid MSA) Multi stage adsorption

ABCDE (A+C--B+D, 2D--A+E) AB/CDE D/EC---C/E

263 Reaction Flash distillation Membrane flash (pervaporation) 264 Reaction Flash distillation Flash distillation 265 Reaction Flash distillation Adsorptive flash 266 Reaction Flash distillation Membrane crystallization (pervaporation) 267 Reaction Flash distillation Adsorption (solid MSA) crystallization 268 Reaction Flash distillation Membrane crystallization (pervaporation) 269 Reaction Flash distillation Membrane distillation (pervaporation) 270 Reaction Flash distillation Membrane adsorption (pervaporation) 271 Reaction Flash distillation Membrane distillation (pervaporation) 272 Reaction Flash distillation Divided wall column 273 Reaction Flash distillation Adsorptive distillation 274 Reaction Flash distillation Membrane adsorption (pervaporation) 275 Reaction Flash distillation Adsorptive distillation 276 Reaction Flash distillation Multi stage adsorption 277 Reaction Vapor permeation membrane Membrane flash (pervaporation) 278 Reaction Vapor permeation membrane Flash distillation 279 Reaction Vapor permeation membrane Adsorptive flash 280 Reaction Vapor permeation membrane Membrane distillation (vapor permeation) 281 Reaction Vapor permeation membrane Membrane adsorption (vapor permeation) 282 Reaction Vapor permeation membrane Membrane distillation (pervaporation) 283 Reaction Vapor permeation membrane Divided wall column 284 Reaction Vapor permeation membrane Adsorptive distillation 285 Reaction Vapor permeation membrane Membrane adsorption (pervaporation) 286 Reaction Vapor permeation membrane Adsorptive distillation 287 Reaction Vapor permeation membrane Multi stage adsorption 288 Reaction Distillation Membrane flash (pervaporation) 289 Reaction Distillation Flash distillation 290 Reaction Distillation Adsorptive flash 291 Reaction Distillation Membrane crystallization (pervaporation) 292 Reaction Distillation Adsorption (solid MSA) crystallization 293 Reaction Distillation Membrane crystallization (pervaporation) 294 Reaction Distillation Membrane distillation (pervaporation) 295 Reaction Distillation Membrane adsorption (pervaporation) 296 Reaction Distillation Membrane distillation (pervaporation) 297 Reaction Distillation Divided wall column 298 Reaction Distillation Adsorptive distillation 299 Reaction Distillation Membrane adsorption (pervaporation) 300 Reaction Distillation Adsorptive distillation 301 Reaction Distillation Multi stage adsorption 302 Reaction Adsorption (solid MSA) Membrane flash (pervaporation) 303 Reaction Adsorption (solid MSA) Flash distillation 304 Reaction Adsorption (solid MSA) Adsorptive flash 305 Reaction Adsorption (solid MSA) Membrane distillation (vapor permeation) 306 Reaction Adsorption (solid MSA) Membrane adsorption (vapor permeation) 307 Reaction Adsorption (solid MSA) Membrane distillation (pervaporation) 308 Reaction Adsorption (solid MSA) Membrane adsorption (pervaporation) 309 Reaction Adsorption (solid MSA) Membrane distillation (pervaporation) 310 Reaction Adsorption (solid MSA) Divided wall column 311 Reaction Adsorption (solid MSA) Adsorptive distillation 312 Reaction Adsorption (solid MSA) Adsorptive distillation 313 Reaction Adsorption (solid MSA) Multi stage adsorption

Appendices

209

Level 2b


AB/CDE---C/DE D/E

314 Reaction Membrane (pervaporation) flash Crystallization 315 Reaction Membrane (pervaporation) flash Flash 316 Reaction Membrane (pervaporation) flash Pervaporation membrane 317 Reaction Membrane (pervaporation) flash Distillation 318 Reaction Membrane (pervaporation) flash Adsorption (solid MSA) 319 Reaction Adsorptive (solid MSA) flash Crystallization 320 Reaction Adsorptive (solid MSA) flash Flash 321 Reaction Adsorptive (solid MSA) flash Pervaporation membrane 322 Reaction Adsorptive (solid MSA) flash Distillation 323 Reaction Adsorptive (solid MSA) flash Adsorption (solid MSA) 324 Reaction Membrane adsorption (vapor permeation) Crystallization 325 Reaction Membrane adsorption (vapor permeation) Flash 326 Reaction Membrane adsorption (vapor permeation) Pervaporation membrane 327 Reaction Membrane adsorption (vapor permeation) Distillation 328 Reaction Membrane adsorption (vapor permeation) Adsorption (solid MSA) 329 Reaction Membrane distillation (pervaporation) Crystallization 330 Reaction Membrane distillation (pervaporation) Flash 331 Reaction Membrane distillation (pervaporation) Pervaporation membrane 332 Reaction Membrane distillation (pervaporation) Distillation 333 Reaction Membrane distillation (pervaporation) Adsorption (solid MSA) 334 Reaction Adsorptive (solid MSA) distillation Crystallization 335 Reaction Adsorptive (solid MSA) distillation Flash 336 Reaction Adsorptive (solid MSA) distillation Pervaporation membrane 337 Reaction Adsorptive (solid MSA) distillation Distillation 338 Reaction Adsorptive (solid MSA) distillation Adsorption (solid MSA) 339 Reaction Membrane adsorption (pervaporation) Crystallization 340 Reaction Membrane adsorption (pervaporation) Flash 341 Reaction Membrane adsorption (pervaporation) Pervaporation membrane 342 Reaction Membrane adsorption (pervaporation) Distillation 343 Reaction Membrane adsorption (pervaporation) Adsorption (solid MSA) 344 Reaction Multi stage adsorption Crystallization 345 Reaction Multi stage adsorption Flash 346 Reaction Multi stage adsorption Pervaporation membrane 347 Reaction Multi stage adsorption Distillation 348 Reaction Multi stage adsorption Adsorption (solid MSA) 349 Reaction Membrane adsorption (vapor permeation) Flash 350 Reaction Membrane adsorption (vapor permeation) Vapor permeation membrane 351 Reaction Membrane adsorption (vapor permeation) Distillation 352 Reaction Membrane adsorption (vapor permeation) Adsorption (solid/liquid MSA)

ABCDE (A+C--B+D, 2D--A+E) AB/CDE---CD/E C/D

353 Reaction Membrane flash (pervaporation) Crystallization 354 Reaction Membrane flash (pervaporation) Pervaporation membrane 355 Reaction Membrane flash (pervaporation) Distillation 356 Reaction Membrane flash (pervaporation) Adsorption (solid MSA) 357 Reaction Flash distillation Crystallization 358 Reaction Flash distillation Pervaporation membrane 359 Reaction Flash distillation Distillation 360 Reaction Flash distillation Adsorption (solid MSA) 361 Reaction Adsorptive flash Crystallization 362 Reaction Adsorptive flash Pervaporation membrane 363 Reaction Adsorptive flash Distillation 364 Reaction Adsorptive flash Adsorption (solid MSA)

Appendices

210

365 Reaction Membrane flash (vapor permeation) Crystallization 366 Reaction Membrane flash (vapor permeation) Pervaporation membrane 367 Reaction Membrane flash (vapor permeation) Distillation 368 Reaction Membrane flash (vapor permeation) Adsorption (solid MSA) 369 Reaction Membrane distillation (vapor permeation) Crystallization 370 Reaction Membrane distillation (vapor permeation) Pervaporation membrane 371 Reaction Membrane distillation (vapor permeation) Distillation 372 Reaction Membrane distillation (vapor permeation) Adsorption (solid MSA) 373 Reaction Membrane adsorption (vapor permeation) Crystallization 374 Reaction Membrane adsorption (vapor permeation) Pervaporation membrane 375 Reaction Membrane adsorption (vapor permeation) Distillation 376 Reaction Membrane adsorption (vapor permeation) Adsorption (solid MSA) 377 Reaction Flash distillation Crystallization 378 Reaction Flash distillation Pervaporation membrane 379 Reaction Flash distillation Distillation 380 Reaction Flash distillation Adsorption (solid MSA) 381 Reaction Membrane distillation (pervaporation) Crystallization 382 Reaction Membrane distillation (pervaporation) Pervaporation membrane 383 Reaction Membrane distillation (pervaporation) Distillation 384 Reaction Membrane distillation (pervaporation) Adsorption (solid MSA) 385 Reaction Divided wall distillation Crystallization 386 Reaction Divided wall distillation Pervaporation membrane 387 Reaction Divided wall distillation Distillation 388 Reaction Divided wall distillation Adsorption (solid MSA) 389 Reaction Adsorptive distillation Crystallization 390 Reaction Adsorptive distillation Pervaporation membrane 391 Reaction Adsorptive distillation Distillation 392 Reaction Adsorptive distillation Adsorption (solid MSA) 393 Reaction Adsorptive flash Crystallization 394 Reaction Adsorptive flash Pervaporation membrane 395 Reaction Adsorptive flash Distillation 396 Reaction Adsorptive flash Adsorption (solid MSA) 397 Reaction Membrane adsorption (vapor permeation) Distillation 398 Reaction Membrane adsorption (vapor permeation) Adsorption (solid MSA) 399 Reaction Membrane adsorption (pervaporation) Crystallization 400 Reaction Membrane adsorption (pervaporation) Pervaporation membrane 401 Reaction Membrane adsorption (pervaporation) Distillation 402 Reaction Membrane adsorption (pervaporation) Adsorption (solid MSA) 403 Reaction Adsorptive distillation Crystallization 404 Reaction Adsorptive distillation Pervaporation membrane 405 Reaction Adsorptive distillation Distillation 406 Reaction Adsorptive distillation Adsorption (solid MSA) 407 Reaction Multi stage adsorption Crystallization 408 Reaction Multi stage adsorption Pervaporation membrane 409 Reaction Multi stage adsorption Distillation 410 Reaction Multi stage adsorption Adsorption (solid MSA)

ABCDE (A+C--B+D, 2D--A+E) AB/CDE---D/EC C/E

411 Reaction Membrane flash (pervaporation) Crystallization 412 Reaction Membrane flash (pervaporation) Flash distillation 413 Reaction Membrane flash (pervaporation) Pervaporation membrane 414 Reaction Membrane flash (pervaporation) Distillation 415 Reaction Membrane flash (pervaporation) Adsorption (solid MSA) 416 Reaction Flash distillation Crystallization 417 Reaction Flash distillation Flash distillation 418 Reaction Flash distillation Pervaporation membrane

Appendices

211

419 Reaction Flash distillation Distillation 420 Reaction Flash distillation Adsorption (solid MSA) 421 Reaction Adsorptive flash Crystallization 422 Reaction Adsorptive flash Flash distillation 423 Reaction Adsorptive flash Pervaporation membrane 424 Reaction Adsorptive flash Distillation 425 Reaction Adsorptive flash Adsorption (solid MSA) 426 Reaction Membrane flash (vapor permeation) Crystallization 427 Reaction Membrane flash (vapor permeation) Flash distillation 428 Reaction Membrane flash (vapor permeation) Pervaporation membrane 429 Reaction Membrane flash (vapor permeation) Distillation 430 Reaction Membrane flash (vapor permeation) Adsorption (solid MSA) 431 Reaction Membrane distillation (vapor permeation) Crystallization 432 Reaction Membrane distillation (vapor permeation) Flash distillation 433 Reaction Membrane distillation (vapor permeation) Pervaporation membrane 434 Reaction Membrane distillation (vapor permeation) Distillation 435 Reaction Membrane distillation (vapor permeation) Adsorption (solid MSA) 436 Reaction Membrane adsorption (vapor permeation) Crystallization 437 Reaction Membrane adsorption (vapor permeation) Flash distillation 438 Reaction Membrane adsorption (vapor permeation) Pervaporation membrane 439 Reaction Membrane adsorption (vapor permeation) Distillation 440 Reaction Membrane adsorption (vapor permeation) Adsorption (solid MSA) 441 Reaction Flash distillation Crystallization 442 Reaction Flash distillation Flash distillation 443 Reaction Flash distillation Pervaporation membrane 444 Reaction Flash distillation Distillation 445 Reaction Flash distillation Adsorption (solid MSA) 446 Reaction Membrane distillation (pervaporation) Crystallization 447 Reaction Membrane distillation (pervaporation) Flash distillation 448 Reaction Membrane distillation (pervaporation) Pervaporation membrane 449 Reaction Membrane distillation (pervaporation) Distillation 450 Reaction Membrane distillation (pervaporation) Adsorption (solid MSA) 451 Reaction Divided wall column Crystallization 452 Reaction Divided wall column Flash distillation 453 Reaction Divided wall column Pervaporation membrane 454 Reaction Divided wall column Distillation 455 Reaction Divided wall column Adsorption (solid MSA) 456 Reaction Adsorptive distillation Crystallization 457 Reaction Adsorptive distillation Flash distillation 458 Reaction Adsorptive distillation Pervaporation membrane 459 Reaction Adsorptive distillation Distillation 460 Reaction Adsorptive distillation Adsorption (solid MSA) 461 Reaction Adsorptive flash Crystallization 462 Reaction Adsorptive flash Flash distillation 463 Reaction Adsorptive flash Pervaporation membrane 464 Reaction Adsorptive flash Distillation 465 Reaction Adsorptive flash Adsorption (solid MSA) 466 Reaction Membrane adsorption (vapor permeation) Flash distillation 467 Reaction Membrane adsorption (vapor permeation) Vapor permeation membrane 468 Reaction Membrane adsorption (vapor permeation) Distillation 469 Reaction Membrane adsorption (vapor permeation) Adsorption (solid MSA) 470 Reaction Membrane adsorption (pervaporation) Flash distillation 471 Reaction Membrane adsorption (pervaporation) Pervaporation membrane 472 Reaction Membrane adsorption (pervaporation) Distillation 473 Reaction Membrane adsorption (pervaporation) Adsorption (solid MSA) 474 Reaction Adsorptive distillation Crystallization

Appendices

212

475 Reaction Adsorptive distillation Flash distillation 476 Reaction Adsorptive distillation Pervaporation membrane 477 Reaction Adsorptive distillation Distillation 478 Reaction Adsorptive distillation Adsorption (solid MSA) 479 Reaction Multi stage adsorption Flash distillation 480 Reaction Multi stage adsorption Distillation 481 Reaction Multi stage adsorption Adsorption (solid MSA)

Level 2c

ABCDE (A+C--B+D, 2D--A+E)---AB/CDE C/DE D/E

482 Membrane reactor (vapor permeation) Crystallization Melting 483 Membrane reactor (vapor permeation) Pervaporation membrane Crystallization 484 Membrane reactor (vapor permeation) Pervaporation membrane Flash 485 Membrane reactor (vapor permeation) Pervaporation membrane Pervaporation membrane 486 Membrane reactor (vapor permeation) Pervaporation membrane Distillation 487 Membrane reactor (vapor permeation) Pervaporation membrane Adsorption (solid MSA) 488 Membrane reactor (vapor permeation) Adsorption (solid MSA) Crystallization 489 Membrane reactor (vapor permeation) Adsorption (solid MSA) Flash 490 Membrane reactor (vapor permeation) Adsorption (solid MSA) Pervaporation membrane 491 Membrane reactor (vapor permeation) Adsorption (solid MSA) Distillation 492 Membrane reactor (vapor permeation) Adsorption (solid MSA) Adsorption (solid MSA) 493 Reactive distillation Crystallization Melting 494 Reactive distillation Pervaporation membrane Crystallization 495 Reactive distillation Pervaporation membrane Flash 496 Reactive distillation Pervaporation membrane Pervaporation membrane 497 Reactive distillation Pervaporation membrane Distillation 498 Reactive distillation Pervaporation membrane Adsorption (solid MSA) 499 Reactive distillation Adsorption (solid MSA) Crystallization 500 Reactive distillation Adsorption (solid MSA) Flash 501 Reactive distillation Adsorption (solid MSA) Pervaporation membrane 502 Reactive distillation Adsorption (solid MSA) Distillation 503 Reactive distillation Adsorption (solid MSA) Adsorption (solid MSA) 504 Reactive adsorption Crystallization Melting 505 Reactive adsorption Pervaporation membrane Crystallization 506 Reactive adsorption Pervaporation membrane Flash 507 Reactive adsorption Pervaporation membrane Pervaporation membrane 508 Reactive adsorption Pervaporation membrane Distillation 509 Reactive adsorption Pervaporation membrane Adsorption (solid MSA) 510 Reactive adsorption Adsorption (solid MSA) Crystallization 511 Reactive adsorption Adsorption (solid MSA) Flash 512 Reactive adsorption Adsorption (solid MSA) Pervaporation membrane 513 Reactive adsorption Adsorption (solid MSA) Distillation 514 Reactive adsorption Adsorption (solid MSA) Adsorption (solid MSA)

ABCDE (A+C--B+D, 2D--A+E)---AB/CDE C/ED D/E

515 Membrane reactor (vapor permeation) Vapor permeation membrane Flash 516 Membrane reactor (vapor permeation) Vapor permeation membrane Distillation 517 Membrane reactor (vapor permeation) Vapor permeation membrane Adsorption (solid MSA) 518 Reactive adsorption Vapor permeation membrane Flash

519 Reactive adsorption Vapor permeation membrane Vapor permeation membrane 520 Reactive adsorption Vapor permeation membrane Distillation 521 Reactive adsorption Vapor permeation membrane Adsorption (solid MSA)

ABCDE (A+C--B+D, 2D--A+E)---AB/CDE CD/E C/D

Appendices

213

522 Membrane reactor (vapor permeation) Distillation Crystallization 523 Membrane reactor (vapor permeation) Distillation Pervaporation membrane 524 Membrane reactor (vapor permeation) Distillation Distillation 525 Membrane reactor (vapor permeation) Distillation Adsorption (solid MSA) 526 Membrane reactor (vapor permeation) Adsorption (solid MSA) Crystallization 527 Membrane reactor (vapor permeation) Adsorption (solid MSA) Pervaporation membrane 528 Membrane reactor (vapor permeation) Adsorption (solid MSA) Distillation 529 Membrane reactor (vapor permeation) Adsorption (solid MSA) Adsorption (solid MSA) 530 Reactive distillation Crystallization Crystallization 531 Reactive distillation Crystallization Pervaporation membrane 532 Reactive distillation Crystallization Distillation 533 Reactive distillation Crystallization Adsorption (solid MSA) 534 Reactive distillation Flash distillation Crystallization 535 Reactive distillation Flash distillation Pervaporation membrane 536 Reactive distillation Flash distillation Distillation 537 Reactive distillation Flash distillation Adsorption (solid MSA) 538 Reactive distillation Pervaporation membrane Crystallization 539 Reactive distillation Pervaporation membrane Pervaporation membrane 540 Reactive distillation Pervaporation membrane Distillation 541 Reactive distillation Pervaporation membrane Adsorption (solid MSA) 542 Reactive distillation Distillation Crystallization 543 Reactive distillation Distillation Pervaporation membrane 544 Reactive distillation Distillation Distillation 545 Reactive distillation Distillation Adsorption (solid MSA) 546 Reactive distillation Adsorption (solid MSA) Crystallization 547 Reactive distillation Adsorption (solid MSA) Pervaporation membrane 548 Reactive distillation Adsorption (solid MSA) Distillation 549 Reactive distillation Adsorption (solid MSA) Adsorption (solid MSA) 550 Reactive Adsorption (solid MSA) Crystallization Crystallization 551 Reactive Adsorption (solid MSA) Crystallization Pervaporation membrane 552 Reactive Adsorption (solid MSA) Crystallization Distillation 553 Reactive Adsorption (solid MSA) Crystallization Adsorption (solid MSA) 554 Reactive Adsorption (solid MSA) Flash distillation Crystallization 555 Reactive Adsorption (solid MSA) Flash distillation Pervaporation membrane 556 Reactive Adsorption (solid MSA) Flash distillation Distillation 557 Reactive Adsorption (solid MSA) Flash distillation Adsorption (solid MSA) 558 Reactive Adsorption (solid MSA) Vapor permeation membrane Distillation 559 Reactive Adsorption (solid MSA) Vapor permeation membrane Adsorption (solid MSA) 560 Reactive Adsorption (solid MSA) Pervaporation membrane Crystallization 561 Reactive Adsorption (solid MSA) Pervaporation membrane Pervaporation membrane 562 Reactive Adsorption (solid MSA) Pervaporation membrane Distillation 563 Reactive Adsorption (solid MSA) Pervaporation membrane Adsorption (solid MSA) 564 Reactive Adsorption (solid MSA) Distillation Crystallization 565 Reactive Adsorption (solid MSA) Distillation Pervaporation membrane 566 Reactive Adsorption (solid MSA) Distillation Distillation 567 Reactive Adsorption (solid MSA) Distillation Adsorption (solid MSA) 568 Reactive Adsorption (solid MSA) Adsorption (solid MSA) Crystallization 569 Reactive Adsorption (solid MSA) Adsorption (solid MSA) Pervaporation membrane 570 Reactive Adsorption (solid MSA) Adsorption (solid MSA) Distillation 571 Reactive Adsorption (solid MSA) Adsorption (solid MSA) Adsorption (solid MSA)

ABCDE (A+C--B+D, 2D--A+E)---AB/CDE D/EC C/E

572 Membrane reactor (vapor permeation) Flash distillation Crystallization 573 Membrane reactor (vapor permeation) Flash distillation Flash distillation 574 Membrane reactor (vapor permeation) Flash distillation Pervaporation membrane 575 Membrane reactor (vapor permeation) Flash distillation Distillation

Appendices

214

576 Membrane reactor (vapor permeation) Flash distillation Adsorption (solid MSA) 577 Membrane reactor (vapor permeation) Vapor permeation membrane Crystallization 578 Membrane reactor (vapor permeation) Vapor permeation membrane Flash distillation 579 Membrane reactor (vapor permeation) Vapor permeation membrane Vapor permeation membrane 580 Membrane reactor (vapor permeation) Vapor permeation membrane Pervaporation membrane 581 Membrane reactor (vapor permeation) Vapor permeation membrane Distillation 582 Membrane reactor (vapor permeation) Vapor permeation membrane Adsorption (solid MSA) 583 Membrane reactor (vapor permeation) Distillation Crystallization 584 Membrane reactor (vapor permeation) Distillation Flash distillation 585 Membrane reactor (vapor permeation) Distillation Pervaporation membrane 586 Membrane reactor (vapor permeation) Distillation Distillation 587 Membrane reactor (vapor permeation) Distillation Adsorption (solid MSA) 588 Membrane reactor (vapor permeation) Adsorption (solid MSA) Crystallization 589 Membrane reactor (vapor permeation) Adsorption (solid MSA) Flash distillation 590 Membrane reactor (vapor permeation) Adsorption (solid MSA) Pervaporation membrane 591 Membrane reactor (vapor permeation) Adsorption (solid MSA) Distillation 592 Membrane reactor (vapor permeation) Adsorption (solid MSA) Adsorption (solid MSA) 593 Reactive distillation Flash distillation Crystallization 594 Reactive distillation Flash distillation Flash distillation 595 Reactive distillation Flash distillation Pervaporation membrane 596 Reactive distillation Flash distillation Distillation 597 Reactive distillation Flash distillation Adsorption (solid MSA) 598 Reactive distillation Crystallization Crystallization 599 Reactive distillation Crystallization Flash distillation 600 Reactive distillation Crystallization Pervaporation membrane 601 Reactive distillation Crystallization Distillation 602 Reactive distillation Crystallization Adsorption (solid MSA) 603 Reactive distillation Pervaporation membrane Crystallization 604 Reactive distillation Pervaporation membrane Flash distillation 605 Reactive distillation Pervaporation membrane Pervaporation membrane 606 Reactive distillation Pervaporation membrane Distillation 607 Reactive distillation Pervaporation membrane Adsorption (solid MSA) 608 Reactive distillation Distillation Crystallization 609 Reactive distillation Distillation Flash distillation 610 Reactive distillation Distillation Pervaporation membrane 611 Reactive distillation Distillation Distillation 612 Reactive distillation Distillation Adsorption (solid MSA) 613 Reactive distillation Adsorption (solid MSA) Crystallization 614 Reactive distillation Adsorption (solid MSA) Flash distillation 615 Reactive distillation Adsorption (solid MSA) Pervaporation membrane 616 Reactive distillation Adsorption (solid MSA) Distillation 617 Reactive Adsorption (solid MSA) Adsorption (solid MSA) Adsorption (solid MSA) 618 Reactive Adsorption (solid MSA) Flash distillation Crystallization 619 Reactive Adsorption (solid MSA) Flash distillation Flash distillation 620 Reactive Adsorption (solid MSA) Flash distillation Pervaporation membrane 621 Reactive Adsorption (solid MSA) Flash distillation Distillation 622 Reactive Adsorption (solid MSA) Flash distillation Adsorption (solid MSA) 623 Reactive Adsorption (solid MSA) Vapor permeation membrane Flash distillation 624 Reactive Adsorption (solid MSA) Vapor permeation membrane Vapor permeation membrane 625 Reactive Adsorption (solid MSA) Vapor permeation membrane Distillation 626 Reactive Adsorption (solid MSA) Vapor permeation membrane Adsorption (solid MSA) 627 Reactive Adsorption (solid MSA) Pervaporation membrane Flash distillation 628 Reactive Adsorption (solid MSA) Pervaporation membrane Pervaporation membrane 629 Reactive Adsorption (solid MSA) Pervaporation membrane Distillation 630 Reactive Adsorption (solid MSA) Pervaporation membrane Adsorption (solid MSA) 631 Reactive Adsorption (solid MSA) Distillation Crystallization

Appendices

215

632 Reactive Adsorption (solid MSA) Distillation Flash distillation 633 Reactive Adsorption (solid MSA) Distillation Pervaporation membrane 634 Reactive Adsorption (solid MSA) Distillation Distillation 635 Reactive Adsorption (solid MSA) Distillation Adsorption (solid MSA) 636 Reactive Adsorption (solid MSA) Adsorption (solid MSA) Flash distillation 637 Reactive Adsorption (solid MSA) Adsorption (solid MSA) Distillation 638 Reactive Adsorption (solid MSA) Adsorption (solid MSA) Adsorption (solid MSA)

Level 3a ABCDE (A+C--B+D, 2D--A+E)---AB/CDE---C/DE D/E

639 Reactive Membrane adsorption (vapor permeation) Flash 640 Reactive Membrane adsorption (vapor permeation) Vapor permeation membrane 641 Reactive Membrane adsorption (vapor permeation) Distillation 642 Reactive Membrane adsorption (vapor permeation) Adsorption (solid MSA) 643 Reactive Membrane distillation (pervaporation) Crystallization 644 Reactive Membrane distillation (pervaporation) Flash 645 Reactive Membrane distillation (pervaporation) Pervaporation membrane 646 Reactive Membrane distillation (pervaporation) Distillation 647 Reactive Membrane distillation (pervaporation) Adsorption (solid MSA) 648 Reactive Adsorptive (solid MSA) distillation Crystallization 649 Reactive Adsorptive (solid MSA) distillation Flash 650 Reactive Adsorptive (solid MSA) distillation Pervaporation membrane 651 Reactive Adsorptive (solid MSA) distillation Distillation 652 Reactive Adsorptive (solid MSA) distillation Adsorption (solid MSA) 653 Reactive Membrane adsorption (pervaporation) Crystallization 654 Reactive Membrane adsorption (pervaporation) Flash 655 Reactive Membrane adsorption (pervaporation) Pervaporation membrane 656 Reactive Membrane adsorption (pervaporation) Distillation 657 Reactive Membrane adsorption (pervaporation) Adsorption (solid MSA) 658 Reactive Multi stage adsorption Vapor permeation membrane 659 Reactive Multi stage adsorption Flash 660 Reactive Multi stage adsorption Distillation 661 Reactive Multi stage adsorption Adsorption (solid MSA) ABCDE (A+C--B+D, 2D--A+E)---AB/CDE---C/ED D/E

662 Reactive Membrane adsorption (vapor permeation) Flash 663 Reactive Membrane adsorption (vapor permeation) Vapor permeation membrane 664 Reactive Membrane adsorption (vapor permeation) Distillation

665 Reactive Membrane adsorption (vapor permeation) Adsorption (solid MSA)

ABCDE (A+C--B+D, 2D--A+E)---AB/CDE---CD/E C/D

666 Reactive Membrane distillation (vapor permeation) Pervaporation membrane 667 Reactive Membrane distillation (vapor permeation) Distillation 668 Reactive Membrane distillation (vapor permeation) Adsorption (solid MSA) 669 Reactive Membrane distillation (pervaporation) Crystallization 670 Reactive Membrane distillation (pervaporation) Pervaporation membrane 671 Reactive Membrane distillation (pervaporation) Distillation 672 Reactive Membrane distillation (pervaporation) Adsorption (solid MSA) 673 Reactive divided wall column Crystallization 674 Reactive divided wall column Pervaporation membrane 675 Reactive divided wall column Distillation 676 Reactive divided wall column Adsorption (solid MSA) 677 Reactive Adsorptive (solid MSA) distillation Crystallization 678 Reactive Adsorptive (solid MSA) distillation Pervaporation membrane 679 Reactive Adsorptive (solid MSA) distillation Distillation

Appendices

216

680 Reactive Adsorptive (solid MSA) distillation Adsorption (solid MSA) 681 Reactive Membrane adsorption (vapor permeation) Distillation 682 Reactive Membrane adsorption (vapor permeation) Adsorption (solid MSA) 683 Reactive Membrane adsorption (pervaporation) Crystallization 684 Reactive Membrane adsorption (pervaporation) Pervaporation membrane 685 Reactive Membrane adsorption (pervaporation) Distillation 686 Reactive Membrane adsorption (pervaporation) Adsorption (solid MSA) 687 Reactive Multi stage adsorption Distillation 688 Reactive Multi stage adsorption Adsorption (solid MSA)

ABCDE (A+C--B+D, 2D--A+E)---AB/CDE---D/EC E/C

689 Reactive Membrane distillation (vapor permeation) Flash 690 Reactive Membrane distillation (vapor permeation) Vapor permeation membrane 691 Reactive Membrane distillation (vapor permeation) Distillation 692 Reactive Membrane distillation (vapor permeation) Adsorption (solid MSA) 693 Reactive Membrane distillation (pervaporation) Crystallization 694 Reactive Membrane distillation (pervaporation) Flash 695 Reactive Membrane distillation (pervaporation) Pervaporation membrane 696 Reactive Membrane distillation (pervaporation) Distillation 697 Reactive Membrane distillation (pervaporation) Adsorption (solid MSA) 698 Reactive Membrane adsorption (vapor permeation) Flash 699 Reactive Membrane adsorption (vapor permeation) Vapor permeation membrane 700 Reactive Membrane adsorption (vapor permeation) Distillation 701 Reactive Membrane adsorption (vapor permeation) Adsorption (solid MSA) 702 Reactive divided wall column Crystallization 703 Reactive divided wall column Flash 704 Reactive divided wall column Pervaporation membrane 705 Reactive divided wall column Distillation 706 Reactive divided wall column Adsorption (solid MSA) 707 Reactive Adsorptive (solid MSA) distillation Crystallization 708 Reactive Adsorptive (solid MSA) distillation Flash 709 Reactive Adsorptive (solid MSA) distillation Pervaporation membrane 710 Reactive Adsorptive (solid MSA) distillation Distillation 711 Reactive Adsorptive (solid MSA) distillation Adsorption (solid MSA) 712 Reactive Multi stage adsorption Crystallization 713 Reactive Multi stage adsorption Flash 714 Reactive Multi stage adsorption Pervaporation membrane 715 Reactive Multi stage adsorption Distillation 716 Reactive Multi stage adsorption Adsorption (solid MSA)

Level 3b


AB/CDE---CD/E---C/D

717 Reaction Adsorptive membrane (vapor permeation) distillation 718 Reaction Multi stage membrane adsorption (vapor permeation) 719 Reaction Adsorptive membrane distillation (pervaporation) 720 Reaction Divided wall adsorptive distillation 721 Reaction Multi stage adsorptive distillation


AB/CDE---D/EC---C/E

722 Reaction Adsorptive membrane distillation (Pervaporation) 723 Reaction Multi stage adsorptive membrane (Pervaporation) 724 Reaction Multi stage adsorptive distillation 725 Reaction Adsorptive membrane distillation (vapor permeation) 726 Reaction Multi stage adsorptive membrane (vapor permeation)

Appendices

217

A/B

Membrane (gas permeation) Adsorption (MSA(S))

AB/CDE---A/B

Flash membrane (gas permeation) Membrane (gas permeation) distillation Membrane (gas permeation adsorption) Multi stage adsorption Adsorptive distillation Adsorptive flash

F.5: Membrane data for permeation of hydrogen (Konda et al., (2006) and Fischer

and Iribarren, (2011))

Gas membrane

details

Hydrogen flux 0.201 kmol/m2/h

Methane flux 1.83E-03 kmol/ m2/h

Selectivity (Hydrogen: Methane) 110:1 -

Membrane area Alternative 118 771.97 m2

Alternative 272 784.03 m2

Appendices

218

Appendix G: Production of bio-succinic acid case study

G.1: Price of raw material (RM), product and utilities

Table G.1.1: Price of the raw material and product $/kg (Synthesis stage)

Compound Price

(Scenario 1 and 2)

Price

(Scenario 3)

Glucose (GLU) 0.428 0.270

Glycerol (GLY) 0.925 0.230

Sucrose (SUC) 0.485 0.265

Maltose (MAL) 0.485 0.265

Succinic acid (SUCA) 2.860 2.860

Table G.1.2: Price of the utilities (Synthesis stage)

Utility Price

(Scenario 1 and 2)

Price

(Scenario 3)

LP Steam ($/t) 27.000 5.000

Cooling water ($/m3) 0.057 0.490

Electricity ($/kWh) 0.120 0.080

G.2: VLE diagram for water-acetic acid and water-ethanol (using PRO/IITM)

Figure G.2.1: VLE diagram for water-acetic acid (Pirola et al., 2014)

Appendices

219

Figure G.2.2: VLE diagram for water-ethanol

Appendices

220

G.3: Level 2 and 3 phenomena based superstructure of alternatives

F/EG

D/EG

D/GE

--E/G—(or FE/G or DE/G)--

E/GD/EFG

D/FGE

DEFG/I

L

Separation task - 2 Separation task - 3 Separation task - 4 Separation task - 5

Fermentation--DEFGI/J

Reaction task-

Separation task - 1

DF/GE

M=2phM=R(L)

M=PC(LS)=PS(LS)

M=PC(LS)=PS(LS)* M=PT(MLL)=PS(LL)

M=PT(MVL)=PS(VL)

M=PT(LS)=PS(LS)

M=ES(C/H)




D/GEF

M=PC(VL)=PS(VL)

M=PT(MLL)=PS(LL)

M=PT(MVL)=PS(VL)

M=PT(LS)=PS(LS)

M=ES(C/H)

M=PT(MLL)=PS(LL)

M=PT(MVL)=PS(VL)

F/EGD

M=PT(MLL)=PS(LL)

M=PT(MVL)=PS(VL)




M=PC(VL)=PS(VL)

M=PC(VL)=PS(VL)




M=PT(MLL)=PS(LL)

M=PT(MVL)=PS(VL)

M=PT(LS)=PS(LS)

M=ES(C/H)

DFE/G

M=PC(VL)=PS(VL)




M=PT(MLL)=PS(LL)

M=PT(MVL)=PS(VL)

M=PC(TS)=PS(LS)

M=ES(C/H)


M=PC(VL)=PT(VL)*=PS(VL)



M=PC(LS)=PS(LS)*

M=PC(VL)=PS(VL)




M=PT(MLL)=PS(LL)

M=PT(MVL)=PS(VL)

M=PT(LS)=PS(LS)

M=ES(C/H)





M=PC(LS)=PS(LS)*

M=PC(VL)=PS(VL)




M=PT(MLL)=PS(LL)

M=PT(MVL)=PS(VL)

M=PT(LS)=PS(LS)

M=ES(C/H)





M=PC(LS)=PS(LS)*




M=PT(MLL)=PS(LL)

M=PT(MVL)=PS(VL)

S*/G

V-L

V-L

L-L

Level 2a

L-L

V-L

L-S

V-L

V-L

V-L

L-L

V-L

V-L

L-L

V-L

L-S

V-L

V-L

L-L

V-L

V-L

L-S

L-S

L-L

V-L

V-L

V-L

V-L

L-S

L-S

L-L

L-L

V-L

V-L

V-L

V-L

L-L

L-L

L-S

Appendices

221

E/GD/FGE--F/EG

L

Separation task – 2 and 3 Separation task - 4

Fermentation

--DEFGIJ--

Reaction task

DEFGI/J

Separation task - 1

DF/GE—E/G

L-SM=2phM=R(L) M=PC(LS)=PS(LS) M=ES(C)=PC(VL)=PT(VL)=PS(VL)


M=PT(MVL)=PS(VL)


F/EGD--D/EG

M=PC(VL)=PS(VL)




M=PT(MLL)=PS(LL)

M=PT(MVL)=PS(VL)

M=PT(LS)=PS(LS)

M=ES(C/H)





M=PC(LS)=PS(LS)*




M=PT(MLL)=PS(LL)

M=PT(MVL)=PS(VL)

S*/G

V-L

V-L

L-L



M=PT(MLL)=PS(LL)


M=PC(VL)=PS(VL)

M=PT(MLL)=PS(LL)

M=PC(VL)=PS(VL)

M=PT(MVL)=PS(VL)



M=PT(MVL)=PS(VL)




M=PT(MLL)=PS(LL)


M=PT(LS)=PS(LS)

M=ES(C/H)

M=PT(MLL)=PS(LL)

M=PT(LS)=PS(LS)

M=ES(C/H)

M=PT(MVL)=PS(VL)

M=PC(VL)=PS(VL)

M=PT(MLL)=PS(LL)

M=PC(VL)=PS(VL)

M=PT(MVL)=PS(VL)

M=PC(VL)=PS(VL)

M=ES(C/H)

M=PT(LS)=PS(LS)

M=PC(VL)=PS(VL)

M=PC(LS)=PS(LS)*



M=PT(MVL)=PS(VL)




M=PT(MLL)=PS(LL)


M=PT(LS)=PS(LS)

M=ES(C/H)

M=PT(MLL)=PS(LL)

M=PT(LS)=PS(LS)

M=ES(C/H)

M=PT(MVL)=PS(VL)

M=PT(MVL)=PS(VL)

M=PC(LS)=PS(LS)*

M=PT(MLL)=PS(LL)

M=PC(LS)=PS(LS)*







M=PC(LS)=PS(LS)*


M=PC(LS)=PS(LS)*

M=ES(C/H)

M=PT(LS)=PS(LS)

V-L

V-L

V-L

V-L

V-L

V-L

L-S

V-L-S

V-L

V-L

V-L-S

V-L

V-L

V-L

L-S

V-L-S

V-L

L-L

V-L

V-L

L-S

Level 2b

Appendices

222

F/EG-E/G

D/EG—E/G

E/GD/EFG

D/FGE

L-S

Separation task - 2 Separation task – 3 and 4 Separation task

Fermentation

--DEFGJ--

Reaction task

DEFG/J

Separation task - 1

DF/GE

L-S LM=2phM=R(L) M=PC(LS)=PS(LS) M=PT(MLL)=PS(LL)

M=PT(MVL)=PS(VL)

M=PT(LS)=PS(LS)

M=ES(C/H)




D/GEF

M=PC(VL)=PS(VL)

F/EGD

M=PT(MLL)=PS(LL)

M=PT(MVL)=PS(VL)

M=PC(VL)=PS(VL)




M=PT(MLL)=PS(LL)

M=PT(MVL)=PS(VL)

M=PT(LS)=PS(LS)

M=ES(C/H)

DFE/G

M=PC(VL)=PS(VL)




M=PT(MLL)=PS(LL)

M=PT(MVL)=PS(VL)

M=PC(TS)=PS(LS)

M=ES(C/H)





M=PC(LS)=PS(LS)*

M=PT(LS)=PS(LS)

M=ES(C/H)

--(DF/D/F)E/G--S*/G

L-L

L-L

L-L

L-L

L-S

V-L

L-S

V-L

V-L

V-L

V-L

V-L

V-L

V-L

V-L

L-S

L-L

V-L



M=PT(MVL)=PS(VL)


M=PT(LS)=PS(LS)

M=ES(C/H)

M=PT(MLL)=PS(LL)

M=PT(LS)=PS(LS)

M=ES(C/H)

M=PT(MVL)=PS(VL)

M=PC(LS)=PS(LS)*

M=PT(MLL)=PS(LL)

M=PC(LS)=PS(LS)*

M=PT(MVL)=PS(VL)



M=PT(MVL)=PS(VL)


M=PT(LS)=PS(LS)

M=ES(C/H)

M=PT(MLL)=PS(LL)

M=PT(LS)=PS(LS)

M=ES(C/H)

M=PT(MVL)=PS(VL)

M=PC(LS)=PS(LS)*

M=PT(MLL)=PS(LL)

M=PC(LS)=PS(LS)*

M=PT(MVL)=PS(VL)

M=PT(LS)=PS(LS)

M=ES(C/H)

M=PT(MLL)=PS(LL)

M=PT(LS)=PS(LS)

M=ES(C/H)

M=PT(MVL)=PS(VL)

M=PC(LS)=PS(LS)*

M=ES(C/H)

M=PT(LS)=PS(LS)

M=PC(VL)=PS(VL)

M=PT(MLL)=PS(LL)

M=PC(VL)=PS(VL)

M=PT(MVL)=PS(VL)

M=PC(VL)=PS(VL)

M=ES(C/H)

M=PT(LS)=PS(LS)

M=PC(VL)=PS(VL)

M=PC(LS)=PS(LS)*



M=PT(MVL)=PS(VL)




M=PT(MLL)=PS(LL)








M=PC(LS)=PS(LS)*


D/GE—G/E



M=PT(MLL)=PS(LL)



M=PT(MLL)=PS(LL)



M=PT(MVL)=PS(VL)







M=PT(MVL)=PS(VL)





E/G

M=PT(LS)=PS(LS)

M=ES(C/H)

Level 2c

V-L

Appendices

223

E/GD/FGE--F/EG-E/G

Separation-Separation-

separationSeparation task



M=PT(MVL)=PS(VL)



M=PT(LS)=PS(LS)

M=ES(C/H)



M=PT(MLL)=PS(LL)



M=PC(VL)=PS(VL)

M=PT(MLL)=PS(LL)

M=ES(C/H)

M=PT(LS)=PS(LS)

M=PC(VL)=PS(VL)

M=PT(MVL)=PS(VL)

M=ES(C/H)

M=PT(LS)=PS(LS)



M=PT(MVL)=PS(VL)

M=PC(LS)=PS(LS)*




M=PT(MLL)=PS(LL)

M=PC(LS)=PS(LS)*


M=PC(VL)=PS(VL)

M=PT(MLL)=PS(LL)

M=PC(LS)=PS(LS)*

M=PC(VL)=PS(VL)

M=PT(MVL)=PS(VL)

M=PC(LS)=PS(LS)*

M=PT(MVL)=PS(VL)

M=PC(LS)=PS(LS)*

M=ES(C/H)

M=PT(LS)=PS(LS)

M=PT(MLL)=PS(LL)

M=PC(LS)=PS(LS)*

M=ES(C/H)

M=PT(LS)=PS(LS)

Level 3

Appendices

224

G.4: Selected list of generated feasible flowsheet alternatives

Level 1 --DEFGIJ-- DEFGI/J DF/GE E/G

149 Fermentation Centrifugation Flash Crystallization

157 Fermentation Centrifugation Liquid-liquid membrane Crystallization

165 Fermentation Centrifugation Pervaporation membrane Crystallization

173 Fermentation Centrifugation Distillation Crystallization

181 Fermentation Centrifugation Crystallization Crystallization --DEFGIJ-- DEFGI/J DFE/G E/G

185 Fermentation Centrifugation Flash Crystallization

186 Fermentation Centrifugation Liquid-liquid membrane Crystallization

187 Fermentation Centrifugation Pervaporation membrane Crystallization

188 Fermentation Centrifugation Distillation Crystallization

189 Fermentation Centrifugation Crystallization

190 Fermentation Centrifugation Extractive distillation Crystallization

191 Fermentation Centrifugation Liquid-liquid extraction Crystallization

192 Fermentation Centrifugation Adsorption (MSA(S)) Crystallization

Level 2a --DEFGIJ—DEFGI/J-- DF/GE E/G

405 Membrane bio-reactor Flash Crystallization

413 Membrane bio-reactor Liquid-liquid membrane Crystallization

421 Membrane bio-reactor Pervaporation membrane Crystallization

429 Membrane bio-reactor Distillation Crystallization

437 Membrane bio-reactor Crystallization Crystallization --DEFGIJ-- DEFGI/J-- DFE/G E/G

441 Membrane bio-reactor Flash Crystallization

442 Membrane bio-reactor Liquid-liquid membrane Crystallization

443 Membrane bio-reactor Pervaporation membrane Crystallization

444 Membrane bio-reactor Distillation Crystallization

445 Membrane bio-reactor Crystallization

446 Membrane bio-reactor Extractive distillation Crystallization

447 Membrane bio-reactor Liquid-liquid extraction Crystallization

448 Membrane bio-reactor Adsorption (MSA(S)) Crystallization

Level 2b --DEFGIJ-- DEFGI/J DF/GE--E/G

571 Fermentation Centrifugation Flash crystallization

575 Fermentation Centrifugation Membrane (pervaporation) crystallization

576 Fermentation Centrifugation Membrane (liquid-liquid) crystallization

581 Fermentation Centrifugation Adsorptive crystallization

Appendices

225

Level 2c

--DEFGIJ-- DEFGI/J D/FGE F/GE--E/G

667 Fermentation Centrifugation Distillation Membrane (pervaporation) crystallization

668 Fermentation Centrifugation Distillation Membrane (liquid-liquid) crystallization --DEFGIJ—DEFGI/J-- D/FGE F/GE--E/G

723 Membrane bio-reactor Distillation Membrane (pervaporation) crystallization

724 Membrane bio-reactor Distillation Membrane (liquid-liquid) crystallization

Level 3a

--DEFGIJ-- DEFGI/J D/FGE--F/EG--E/G

766 Fermentation Centrifugation Flash membrane (liquid-liquid) crystallization

767 Fermentation Centrifugation Flash membrane (pervaporation) crystallization

772 Fermentation Centrifugation Adsorptive membrane (pervaporation) crystallization

773 Fermentation Centrifugation Adsorptive membrane (liquid-liquid) crystallization

Level 3a

--DEFGIJ--DEFGI/J D/FGE--F/EG--E/G

776 Membrane bio-reactor Flash membrane (liquid-liquid) crystallization

777 Membrane bio-reactor Flash membrane (pervaporation) crystallization

782 Membrane bio-reactor Adsorptive membrane (pervaporation) crystallization

783 Membrane bio-reactor Adsorptive membrane (liquid-liquid) crystallization

Level 3b --DEFGIJ-- DEFGI/J-- DFE/G--S*/G E/G

784 Membrane bio-reactor Extractive membrane (liquid-liquid) distillation Crystallization

785 Membrane bio-reactor Extractive membrane (pervaporation) distillation Crystallization

786 Membrane bio-reactor Extractive divided wall column Crystallization

787 Membrane bio-reactor Membrane liquid-liquid extraction Crystallization

788 Membrane bio-reactor Membrane(pervaporation) liquid-liquid extraction Crystallization

789 Membrane bio-reactor Extractive (liquid-liquid) distillation Crystallization

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phenomena-based process synthesis-intensification · to specially thank shivangi, ishan, alay,...

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