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Innovative Waste Recycling and Energy Efficiency Solutions

Session 4 : Early Career Professionals Session

Dr Pedro Yunes

2013

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“Overview of the waste recycling process

in the Zinc smelter at Nyrstar Port Pirie”

Presented by

Dr. Pedro Yunes

Nyrstar Port Pirie

[email protected]

Mobile: (+61) 0419164703

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• Nyrstar – Company Overview • Nyrstar – Port Pirie • Process Flow • Slag Fuming and Kiln Process Operations • Recycling in the Slag Fuming Process • The Transformation – Securing our Future

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Company Overview

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Nyrstar Port Pirie

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Nyrstar Port Pirie – Process Flow

6

CSB/SHED

Acid Plant

KDR

Clean Gas

Copper Leach

Residue

Rich Slag Mix Concentrates

Blended Cons

Sinter Feed

Raw Fume

Coke Sinter

Return Hot

Slag Spent

Slag

Coal

MIXING PLANT

CASTING SRF CADMIUM PLANT

(r)

(r)

(r)

KILN

BAGHOUSE Centrifuge(s)

COPPER PLANT

Rich Gas

Lean Gas

Fume Slurry

Refined Silver 9997 Lead Crude Gold

PM Fume

Copper

Ca Alloy

Caustic Dross

Crude Sb Alloy

Market Zinc

Cathode Zinc

Roast Fume

Zinc

Scum

Zinc

dross

CDF Slag

9999 Lead

CTB

Zinc

PCC Bullion

Bullion

Softener Slag

Effluent KDR U/F

5003 Sb Alloy

Tall Stack

LG Lead

(r)

SRF

INCIRCULATION

REFINERY

ALLOY PLANT

RESIDUE

LEAD ALLOYS

KILNS

SLAG FUMER

LEACH/ELECT

KBA

PRECIOUS METALS

MIXING PLANT

SINTER PLANT

BLAST FURNACE

CDF

Liquation

Copper Matte

VIR Zinc

HG Alloy

Sb Alloy

Zinc Leach residue (r)

ESP

CASTING

Granulated

Slag Ladle

Skull

Boiler

Ash

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Slag Fuming and Kilns - Process Operations

7

Slag Fuming

Furnaces Rich Slag Mix

Blast

Furnace Slag

Recuperators

Bag House

Rotary Kilns Ball Mills

PCI

Secondary Air

(hot)

Natural

Gas

Weak Wash

Water

Leach Plant

Secondary

Air (cold)

Spent Slag

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Slag Fuming and Kilns Process Operations

8

WESTERN SIDE OF THE SLAG

FUMING PLANT

ROTARY KILN #2

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Slag Fumer – Internals

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

1 2 3 4 5 6 7 8 9 10 11 12 13

% Boiler Ash in Rich Slag Mix (35% Zn)

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

1 2 3 4 5 6 7 8 9 10 11 12 13

% Skull fines in Rich Slag Mix ( 15% Zn)

0%

1%

2%

3%

4%

5%

6%

1 2 3 4 5 6 7 8 9 10 11 12 13

% Zn Dross Fines in Rich Slag Mix ( 61% Zn)

0%

1%

2%

3%

4%

5%

6%

1 2 3 4 5 6 7 8 9 10 11 12 13

% KDR U/F in Rich Slag Mix (35% Zn)

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Slag Fumers – External

0%

5%

10%

15%

20%

25%

30%

1 2 3 4 5 6 7 8 9 10 11 12 13

% EAF Dust in Rich Slag Mix (30% Zn)

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From being primarily a lead smelter….

The Transformation – Today

Schematic of the sinter plant that will be phased out

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The Transformation – Tomorrow

…to become an state-of-the-art poly-metallic processing and recovery facility

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The Transformation - Benefits

• Step change reduction in emissions

from the site

• Greater flexibility for processing

wider range of raw materials

• Key e-waste materials can be

recovered (Au, Ag, Ge, In ,Te, etc)

• Energy content in plastics will be

recovered to reduce coal

consumption

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The Transformation – Securing Our Future

The Present

Australia has no facility to process and recover the valuable metals in

this growing waste stream.

The Future

The transformed Port Pirie facility will have the process capability to

meet this need.

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Questions ??

Thanks for your attention

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Lisa Green

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Working with Industry to

Achieve Compliance Lisa Green

Intelligence Unit

Department of Environment and Heritage

Protection

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Background to EHP

Mission:

Strong environmental regulator which supports sustainable long-

term economic development in Queensland

Enabled by:

– Building relationships with government, business, industry and

the community

– Innovative, evidence-based environmental policies, programs

and services

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• Greentape – streamlining application processes to reduce

regulatory burden, increasing compliance effort

• Department to work with industry

• Compliance priorities are targeted, transparent, risk based

• Good performers monitored less, poor performers monitored

more

Regulatory Strategy

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Waste Industry

• Much of Queensland’s waste is sent straight to landfill –

valuable resources are being lost

• Waste levy was repealed following 2012 Queensland State

Elections

• Challenge – encourage innovation and investment in the

state’s recycled waste industry without a levy

• Queensland is currently reviewing its waste strategy through

an ‘industry-led’ process

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Compliance

• Department has increased compliance effort

• Compliance focus is risk-based, targeted and transparent

• Compliance is not intended to inhibit industry’s drive for

innovation

• It is to: understand where key risks exist, why they exist

and develop effective and appropriate strategies to

target these risks

• The department will take prompt, strong enforcement action

to those who intentionally choose not to comply

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Intelligence-Led Compliance

• Purpose:

Collate and analyse information to understand risk to inform

policy development and compliance planning

• This function:

– monitors and identifies risk

– establishes causes of non-compliance

– identifies instances of unlicensed activity

– monitors and informs management and officers of new

technologies and processes

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Composting

• Compositing is a growth industry which

promotes reuse and recycling of waste

• Odour and waste acceptance are risk

areas to the department

• Developed a capacity building project to

work with industry

• Incorporates industry-led waste strategy

review

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Unlined Landfills

• Leachate is a key risk of unlined landfills

• Intelligence Unit is analysing data from a variety of sources to

identify high risk unlined landfill sites

• The department will work with site operators and incorporate

new technologies to improve monitoring

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Sustainable development is a collaboration between regulators,

industry and the community

The department will increase its monitoring to ensure compliance

Business and industry are best-placed to work out how to stay

compliant

EHP will work collaboratively with industry and the community to

develop standards, polices to manage and protect environment and

heritage yet assist investment in the state’s recycled waste industry

Summary

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[email protected]

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Dr Nawshad Haque

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Life cycle based greenhouse gas footprints of metal production with recycling scenarios

Dr Nawshad Haque, Team Leader 4 October 2013

PROCESS SCIENCE AND ENGINEERING/MINERALS DOWN UNDER

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Outline

• Introduction to LCA •LCA of mining and metals •Material recovery facility •Boundary and assessment •Key results for steel and aluminium •Concluding remarks

Life cycle assessment | Nawshad Haque 2 | 20

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Life cycle

Extraction

Processing&

Manufacturing

Transport Use phase

Resource

Landfill

3 | Life cycle assessment | Nawshad Haque 20

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Stages of LCA

• Why and for whom?

• Boundary demarcation, data collection

• Impact category selection, characterisation

• Assessment, interpretation, sensitivity analysis

• Update & improvement with new data

Goal and

scope

definition

Inventory

analysis

Impact

Assessment

Interpretation


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Assessment - LCA Impact/Indicators


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Example flowsheet


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Metals – “Cradle-to-Gate” – GWP

0

5

10

15

20

25

Ste

el

S/S

teel

Alum

inium

Cop

per

Cop

per

Lead

Lead

Nicke

l

Nicke

l

Zinc

Zinc

t C

O2 e

/t o

f m

eta

l

Norgate et al . (2007) J of Cleaner Production, 15:838-848.

Pyro

Hydro

o

BF

ISF

Pyro

Hydro

Electrolytic

ISF


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LCA works of CSIRO in Mining & Metals


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Material Recovery Facility (MRF)

• Courtesy (Visy, 2013)


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Material Recovery Facility (MRF)


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MRF Product Composition

Life cycle assessment | Nawshad Haque 11 |

Plastic

Glass

Steel

Aluminium

Paper

Source: Sustainability Vic (2011) 2013

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MRF Product Revenue (crude estimate)


Plastic

Glass

Steel

Aluminium

Paper

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MRF GHG footprint distribution


Trommel screen

Front-end loader

Conveyor

Glass breaker

Magnetic separator

Eddie current

separator

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GHG footprint of recycled steel if sent overseas for reprocessing


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GHG footprint of recycled aluminium if sent overseas for reprocessing


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Key messages • Process evaluation assists with decision making • Life Cycle Assessment (LCA) is a recognised objective tool • Metals have different specific carbon footprint • Specific carbon footprint is not the only story but

consider the overall total production of particular metal • Carbon footprint can be reduced with various measures

such as recycling • Collection GHG can be 10 times higher than MRF GHG • Most benefit of GHG reduction if it is processed locally • There are other environmental and social impacts need

consideration


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International activities and engagements • Australia-India Workshop on LCA for mining, mineral processing metal making

industries

• Dates: 20 & 21 January 2014

• Will be supported by Indian School of Mines University and Australia India Council division of DFAT

• Working under CSIRO-KIGAM Korea collaboration on rare earth and recycling

• Bangladesh CSIR and CSIRO Collaboration on metals and mineral sands processing

• Hosted Ministerial delegation visit, developed list of action items about process evaluation and other studies

• Mineral samples analysed, recommendations made

• Secondment of a BCSIR staff and a joint workshop planned in January 2014


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• For assistance & supports: • CSIRO Colleagues (T. Norgate, Dr. S. Jahanshahi, Dr. J. Rankin, A Monch, S

Northey, A Littleboy, M Cooksey)

• An unnamed City Council

• For more information:

• Explore website csiro.au

Acknowledgements


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PROCESS SCIENCE AND ENGINEERING/MINERALS DOWN UNDER

Thank you

Dr Nawshad Haque Senior Scientist/Project Leader

t +61 3 9545 8931 e [email protected] w www.csiro.au/people/Nawshad.Haque.html

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Manudha Herath

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Structural Optimisation Using Bend-Twist

Coupling For Wind Turbine Blades

School of Mechanical and Manufacturing Engineering

Prepared By: Mr Aaron Lee

Supervisor: A/Prof. B. Gangadhara Prusty

Co-Supervisor and Presenter:

Mr Manudha (Thinu) Herath

2013 INTERNATIONAL SUSTAINABILITY SYMPOSIUM


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Structural Optimisation Using Bend-Twist Coupling

For Wind Turbine Blades

Presentation overview

Background

Introduction of shape-adaptive blades

Past research findings

Our approach - Preliminary design framework

Differential Stiffness Bend-Twist (DSBT) Coupling

Composite material layup optimisation

Summary and future work

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According to the U.S. National Renewable Energy Laboratory

(NREL)….

Class 5 & 6 wind farm sites

Higher wind speeds

7.5 – 8.8 m/s

500 miles away from load

centres (class 6)

Sites are limited

Most desirable sites have

been developed

Class 4 wind farm sites

Lower wind speeds

Avg. 7.25 m/s

100 miles away from load

centres

Contains 20 times the wind

potential

Lower transmission cost

Why should we study wind turbines?

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In Australia…

High wind energy potential

along the southern coast

Class 4-6 onshore wind

farm sites found

Renewable Energy Target:

20% of electricity from

renewable sources in 2020

Plenty of wind farms

currently being developed

Why should we study wind turbines?

Ref: Geoscience Australia and ABARE, 2010

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Geometry changes based on:

Turbine rotation speed

Incoming wind speed

Loads experienced varies

Pitch angle changes

according to the bending

loads applied

Achieved by bend-twist

coupling

What are shape-adaptive wind turbine blades?

Ref: Capellaro, 2012

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One of the passive pitch

control methods

Bending introduces

torsional deformation

Usually achieved by using

the anisotropic properties of

composites

What is bend-twist coupling?

Ref: Jones, 1999

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Why do we need shape-adaptive blades?

For bend-twist coupled blades that twist towards feather:

Bending load increases as wind speed increases

Induced twist lowers the pitch angle

Lower aerodynamic loads experienced

Reduced fatigue damage

Lower maintenance cost

Extended service life

Weaker, lighter structures can be use

Larger blades can then be designed

More energy can be captured

Design improvements promote the development of low-wind

speed sites

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Instability observed for coupled blades twisting towards stall

Lower fatigue loads for coupled blades twisting towards

feather


Coupled, towards feather

Coupled, towards stall

Uncoupled, baseline

Ref: Adapted from Lobitz and Laino, 1998

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Damage normalised to

the uncoupled blade

3 types of materials

Welded Steel (3)

Aluminium (6)

Composite (9)

3 wind speed settings

8, 14 & 20 m/s

Fatigue damage

reduced for all coupled

blades twisting towards

feather


Uncoupled,

baseline

Coupled,

towards feather,

not pre-twisted

Coupled,

towards feather,

pre-twisted

Coupled,

towards stall,

not pre-twisted


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Not pre-twisted

no power regulation

Increased average power

Pre-twisted

Max. power regulated

Resemble typical

operation

Average power is similar

to that of uncoupled

blades

Primary benefit of coupled

blades is load reduction


Uncoupled,

baseline

Coupled,

towards feather,

pre-twisted

Coupled, towards stall, not pre-twisted

Coupled,

towards feather,

not pre-twisted


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Conventional design

approach

Fibres placed at an angle

to the flexural axis to create

biased laminates

Biased laminates applied

either at the skin panels or

the spar caps

Strain incompatibilities

found

Upper and lower skin joint

Spar cap/web connection


Ref: de Goeij et al., 1999

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Our approach - DSBT coupling

Definition of Differential Stiffness Bend-Twist (DSBT) coupling:

“to control the bend-twist coupling of the global structure by

incorporating structural sub-components with distinctly

different stiffness values that would experience bending as

their main deformation”

Avoids the design of bend-twist coupled sub-components

Minimise/eliminate strain incompatibilities at joints

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Our approach - Preliminary design for DSBT

blades

Model idealisation

Stiffener geometry

Number of stiffeners

Stiffener positions (spacing)

Skin thickness

Boom areas

Boom locations

Loads in components

Numerical analysis

Young’s modulus distribution

No

No

Yes

Preliminary material design

Composite layup sequence

Ply layup sequences

Material properties

Preliminary design of DSBT blade

Yes

Blade profile, Pressure loads

Stiffener geometry

Young’s modulus values

Maximum deflection

< Acceptable limit?

Achieved desired

change in pitch angle?

Finite Element

analysis

Structural

idealisation

Composite layup

optimisation

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Stiffeners are the structural

sub-components

They are used to introduce

bend-twist coupling

Differential bending

Stiffeners with higher

stiffness displace less

Vice versa

Introduces twist in overall

structure

Our approach - DSBT coupling

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Structural idealisation

Existing technique

Used in aircraft structural

design

Stiffeners replaced by

booms

Booms carry all bending

loads

Skin panels only carry

shear load

Our approach – DSBT feasibility study

Ref: Megson, 2007

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Finite Element analysis

Idealised thin-walled box

beam studied

Cantilevered boundary

conditions

Dimensions and material

properties parameterised

Booms modelled with

beam elements

Skin modelled with shell

elements


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Uncoupled model

Uniform Young’s modulus

distribution

Uniform bending observed

No twist


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DSBT model

Higher Young’s modulus

value applied to the left

booms

Differential bending

observed

Twist of 3.28 degrees at tip

Main deformation in booms

remained as pure bending


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Our approach - Composite layup optimisation

Limited Young’s modulus values from typical isotropic

materials

Composites can provide a range of effective Young’s modulus

by varying the layup

Genetic Algorithm is used to search for optimum layup

Material Steel alloys

(ASTM A36)

Aluminium alloys

(Al2024-T3)

E 200 GPa 74 GPa

Material Carbon fibre composite (AS4/3501-6)

E1 126 GPa

E2 11 GPa

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Our approach - Composite layup optimisation

Material design – formulate requirements

Sub-components remain in pure bending

Composite bending stiffness matrix:

Composite bending Matrix:

𝑀𝑥𝑥

𝑀𝑦𝑦

𝑀𝑥𝑦

=

𝐷𝑥𝑥 𝐷𝑥𝑦 𝐷𝑥𝑠

𝐷𝑦𝑥 𝐷𝑦𝑦 𝐷𝑦𝑠

𝐷𝑠𝑥 𝐷𝑠𝑦 𝐷𝑠𝑠

𝜅𝑥𝑥

𝜅𝑦𝑦

𝜅𝑥𝑦

In-plane loads and out-of-plane deformations are decoupled

𝐷𝑥𝑥 =𝐸𝐼𝑥𝑥

𝑏, 𝐷𝑥𝑠 = 𝐷𝑠𝑥 = 𝐷𝑦𝑠 = 𝐷𝑠𝑦 = 0

Other D matrix elements are not of interest at this stage

Cross-ply balanced symmetric layup sequence required

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Our approach – Genetic Algorithm program

In-house Genetic Algorithm (GA) program used for

optimisation

Input variables: Fibre orientation angle of each ply

Target: Required D matrix values

𝑓 𝜽𝑚𝑖𝑛

= 𝐷𝑥𝑥𝑟𝑒𝑞 − 𝐷𝑥𝑥𝐺𝐴

GA optimisation procedure

1st generation randomly formulated

Evaluate error

Formulate next generation through natural selection, cross-over

of parent generation and mutation

Iterate until satisfactory results are obtained

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Required:

𝐷32𝐺𝑃𝑎 =

124416 𝐷𝑥𝑦 0

𝐷𝑦𝑥 𝐷𝑦𝑦 0

0 0 𝐷𝑠𝑠

Achieved by GA program:

𝐷32𝐺𝑃𝑎 =124416.78 8850.99 0

8850.99 62846.83 00 0 18651.03

Required:

𝐷25𝐺𝑃𝑎 =

97200 𝐷𝑥𝑦 0

𝐷𝑦𝑥 𝐷𝑦𝑦 0

0 0 𝐷𝑠𝑠

Achieved by GA program:

𝐷25𝐺𝑃𝑎 =97199.01 8850.99 08850.99 90064.59 0

0 0 18651.03

Our approach - Genetic Algorithm program

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Summary

Preliminary design procedure

Structural idealisation

Finite element analysis to predict twist

Genetic algorithm for layup optimisation

DSBT is a feasible concept

Achieved by applying non-uniform Young’s modulus distribution

in sub-components

Composite layup can be optimised

Provides the required Young’s modulus value

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Future work – where to now?

Experimental verification of the DSBT concept

Improve the design procedure by:

Adapt the procedure for complex non-symmetrical structures

Integrate the FE analysis and the GA program

Consider different load cases

Incorporate failure theories

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References

CAPELLARO, M. 2012. Design Challenges for Bend Twist Coupled Blades for Wind Turbines: and

application to standard blades. 2012 Sandia Wind Turbine Blade Workshop. Albuquerque, New

Mexico: University of Stuttgart.

DE GOEIJ, W. C., VAN TOOREN, M. J. L. & BEUKERS, A. 1999. Implementation of bending-torsion

coupling in the design of a wind-turbine rotor-blade. Applied Energy, 63, 191-207.

GEOSCIENCE AUSTRALIA & ABARE 2010. Australian Energy Resource Assessment.

JONES, R. M. 1999. Mechanics of composite materials, CRC Press.

LOBITZ, D. W. & LAINO, D. J. 1998. Load Mitigation with Twist-coupled HAWT Blades. ASME Wind

Energy Symposium. Reno, Nevada.

MEGSON, T. H. G. 2007. Aircraft structures for engineering students, Elsevier/Butterworth-

Heinemann.

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Questions??

Thank you

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Hewitt Park

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The influence of CaO-FexOy-Al2O3-SiO2 oxide system

on the reduction of carbon composite pellet

04/10/2013

Hewitt Park* and Veena Sahajwalla

Centre for Sustainable Materials Research & Technology (SMaRT@UNSW)

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SMaRT Centre

Thermo gravimetric analyzer (TGA)

Drop Tube Furnace (DTF)

Horizontal Furnace & gas analyzer

Fixed bed reactor

BET machine

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SMaRT Centre

July 5th, 2013

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Why Carbon Composite Pellets?

Carbon

Composite

Pellet

Utilization of

secondary materials

(mill scale, dust

and slags)

Diversifying

carbon sources

(Non-coking coal,

hydro carbons)

Depletion of

high quality coal

and Iron ore

Consumption of

low grade ores

(goethite,

limonite etc.)

CO2 Emission

Kyoto protocol

20%↓ by ‘2020

Sustainable

development of

steelworks

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Floor of rotary hearth furnace

Room temp. → 1723K (1450oC)

Coal composite iron ore pellet

Iron nugget

Slag??

8 ~ 12 minutes

Rotary Heart Furnace (RHF)

ITmk3 process®

FASMET®, INMETCO®

Raw material

storage pile

Coal

Iron ore

Mill scale

Electric Arc Furnace (EAF)

Iron

Nugget

Hot

Metal

Direct reduced iron (DRI) making process

DRI

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CaO – SiO2 – Al2O3 – MgO – FexO –..

Thermodynamics of slags

1. CaO-SiO2-Al2O3 ternary oxide system

2. Influence of dolomite (MgO)

3. Raw materials from steelworks

Classification

of oxide Oxide

Electro -

negativity

of cation

Cationic

radius(Å)

Ion-oxygen

attraction

↑ CaO 1.0 0.99 0.70

Basic FeO 1.7 0.75 0.87

↕ MgO 1.2 0.65 0.95

Intermediate Fe2O3 1.8 0.60 1.50

↕ Al2O3 1.5 0.50 1.66

Acidic SiO2 1.8 0.41 2.44

Table1. Index of slag basicity (Ban-ya, 1988)

Research interests

35 - 45 12 - 18 3 - 8 30 - 40 Mass %

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Research objective

• Understand the influence of CaO-FexOy-Al2O3-SiO2 oxide system on the reduction

behavior of carbon composite pellet

• Investigate the individual effect of alumina and silica on the reduction

• Obtain enough reduction degree of pellets at low temperature below 1473K (1200oC)

• Discover the optimum reaction condition (temperature, compositions) for carbon

composite pellet

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Chemical composition

Fig.2 A schematic representation of the experiment

Thermocouple

Stainless

Steel Rod

Gas Inlet Alumina

Rod

Graphite

Tray

Alumina

Substrate

Carbon

Composite Pellet Mullite Tube Quartz

Window

Heating element

MoSi2

CCD

Camera

Date/Time

Generator IR Gas Analyzer

Effect of CaO-SiO2-Al2O3 ternary system

T = 1500oC (1773K)

Silica-rich oxide

Blast furnace slag

Alumina-rich oxide

wt% CaO

20

40

60

80

80 60 20

20

40

SiO2

CaO 40

80

60

Al2O3

A

B

C

Fig.1 Phase diagram of CaO-SiO2-Al2O3 oxide system

A schematic apparatus

Sample specification

Diameter & Weight 10mm & 1.0 - 1.2g

Fe2O3 / C 5.66

Oxides amounts 10wt% of pellet weight

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A. Silica-rich oxide system

C. Alumina-rich oxide system

B. Blast furnace slag system

In-situ visual image Optical microscopic image

120 sec. 300 sec.

30 sec. 120 sec.

30 sec. 120 sec.

30 sec.

300 sec.

300 sec.

2 mm

2 mm 2 mm 2 mm

2 mm 2 mm

2 mm 2 mm 2 mm

In-situ & Microscopic study

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25 30 35 40 45 50

30sec

0sec

120sec

Fe2O

3 Fe free C

Inte

nsity

2 theta

25 30 35 40 45 50

30sec

0sec

120sec

Fe2O

3 Fe free C

Inte

nsity

2 theta

25 30 35 40 45 50

30sec

0sec

120sec

Fe2O

3 Fe free C

Inte

nsity

2 theta

X-Ray Diffraction analysis

Reaction rates (Infrared gas analysis)

0 60 120 1800.0

0.2

0.4

0.6

0.8

1.0

Sample A

Sample B

Sample C

Fra

ctio

n re

acte

d, f

Time (s)

A. Silica-rich oxide system C. Alumina-rich oxide system B. Blast furnace slag system

Fig.3 Reacted fraction of carbon composite pellet at 1773K(1500oC)

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Specimen Top plate

Bottom plate

Mechanical property & Optimum carbon contents

10% 15% 20%

Carbon contents (wt%)

Completely

shattered

Not shattered

Shapes of pellets

Fig.4 Compressive strength of pellet after reduction

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Table 2. Chemical composition of pellets

Sample

Composition of oxides Total Weight (g)

CaO Fe2O3 Al2O3 SiO2

1273K

(1000oC)

1373K

(1100oC)

1473K

(1200oC)

CF2 15 85 - - 1.3659 1.4884 0.935

CF2-5A 14.25 80.75 5 - 1.0548 1.0159 0.973

CF2-10A 13.5 76.5 10 - 1.1444 0.9346 0.945

CF2-15A 12.75 72.25 15 - 1.1000 0.8796 0.965

CF2-5S 14.25 80.75 - 5 1.0096 0.9704 0.984

CF2-10S 13.5 76.5 - 10 0.8765 1.0520 0.943

CF2-15S 12.75 72.25 - 15 0.8531 0.8207 0.991

CaO ≥ 99.0%

SiO2 ~99%, 0.5-10µm

Al2O3 99.7%, 10µm

Fe2O3 ≥ 99%, <5µm

Graphite Flakes

Table 3. Chemical details (Supplied by Sigma-Aldrich Australia)

Influence of Alumina and Silica on the reduction

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Temperature 1000-1200oC

Reaction Time 30 min.

Gas atmosphere Argon gas flow (1L / min.)

Crucible Alumina

Experimental equipment

Fig.6 Thermo Gravimetric Analyser (TGA)

Reaction conditions

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Temperature dependence

0 600 1200 1800 2400 3000 36000

20

40

60

80

100

GR-L (Graphite) - 1473K (1200OC)

CB-1 (Coke) - 1273K (1000OC)

Jeremy and Veena

CF2-1473K (1200oC)

CF2-1373K (1100oC)

CF2-1273K (1000oC)

Reduction d

egre

e (

%)

Time (sec.)

Fig.7 Temperature dependences of reduction degree for CF2

sample compared to previous research

Thermodynamic & kinetic study

0 100 200 300 400 500 6000.55

0.60

0.65

0.70

0.75

0.80

0.85

0.90

0.95

#1 CF2

#2 CF2 Al2O

3 5wt%

#3 CF2 Al2O

310wt%

#4 CF2 Al2O

315wt%

#5 CF2 SiO2 5wt%

#6 CF2 SiO210wt%

#7 CF2 SiO215wt%

Wei

ght (

g)

Time (sec.)

Fig. 8 - Effect of Al2O3 and SiO2 on the weight loss

of carbon composite pellets during reduction at 1200oC

Weight loss

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Thermodynamic & kinetic study

Reduction degree Uniform international reduction

1. 𝐑𝐚𝐭𝐞 𝐞𝐪𝐮𝐚𝐭𝐢𝐨𝐧: 𝐥𝐧 𝟏 − 𝐗 = −𝒌 ∙ 𝐭

E. T. Turkdogan and J. V. Vinters: Meta//, Mater. Trans. B, 1972

Fig.9 Reduction degree of pellets at 1200oC Fig.10 –ln(1-X) plot with time at 1200oC

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Surface area change New reaction kinetic model Boudouard reaction

2. 𝐥𝐧 𝟏 − 𝐗 = −𝒌 ∙ 𝑷𝑪𝑶𝟐− 𝑷𝑪𝑶𝟐

𝒆𝒒.𝐭

Jeremy and Veena; ISIJ International, 2003

4. 𝐍𝐞𝐰 𝐤𝐢𝐧𝐞𝐭𝐢𝐜 model of reaction:

𝐥𝐧(𝟏 − 𝐗) = −𝒌 ∙ 𝑺 ∙ (𝑷𝑪𝑶𝟐− 𝑷𝑪𝑶𝟐

𝒆𝒒.) 𝐭

𝟑. 𝐑𝐞𝐚𝐜𝐭𝐢𝐨𝐧 𝐫𝐚𝐭𝐞 ∝ 𝐒𝐮𝐫𝐟𝐚𝐜𝐞 𝐚𝐫𝐞𝐚

Fig.11 –ln(PCO/PCO2) with time at 1200oC Fig.12 Surface area change of samples Fig.13 –ln(1-X)/S*(PCO2/PCO2eq) with time at 1200oC

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20 30 40 50 60 70 80 90

Inte

nsi

ty

RD 80%

RD 30%

RD 5%

CaO Fe2O

3 Fe

2 theta

CF2 (1473K)

20 30 40 50 60 70 80 90

Inte

nsi

ty

RD 80%

RD 30%

RD 5%

CaAl2O

4 Fe

2O

3 Fe

2 theta

CF2-15A (1473K)

20 30 40 50 60 70 80 90

Inte

nsi

ty

RD 80%

RD 30%

RD 5%

Fe2SiO

4 Fe

2O

3 Fe

2 theta

CF2-15S (1473K)

X-ray Diffraction (XRD) results

20.0kV 10.4mmⅹ1.00k BSECOMP

Fe

fayalite

fayalite

20.0kV 10.6mmⅹ500 BSECOMP

Fe CaO∙Al2O3

& 2CaO∙Al2O3

Fe

Fe

☓: Fe2O3 : Fe ●: CaO △: CaAl2O4 ◆: Fe2SiO4

SEM / EDX results

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Conclusions

A study on the effect of CaO-Al2O3-SiO2 ternary oxide system at 1500oC

• Silica-rich pellet was disintegrated due to the violent reaction, while alumina-rich pellets maintained

denser internal structure through overall reduction process.

• Silica-rich systems formulated fayalite phase which have delayed solid-gas reaction, while alumina

rich system did not show any critical change in morphology due to its low solubility to iron oxide.

An investigation on the individual effect of alumina and silica at 1200oC

• While silica slows down the overall reaction, alumina increases reaction rate

• Alumina content supports the pellet to maintain large surface area due to its high melting temp.

• Development of new kinetic model for carbon composite pellets

𝒍𝒏(𝟏 − 𝐗) = −𝒌 ∙ 𝑺 ∙ (𝑷𝑪𝑶𝟐− 𝑷𝑪𝑶𝟐

𝒆𝒒.) 𝒕

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Thank you for attention

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