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20.02.2006 12nd year CROPGEN meeting, 6th February, Vienna I DI Alexandra Wolfsberger

University of Natural Resources andApplied Life Science, ViennaUniversität für Bodenkultur WienWP7 Biokinetic Data,

Modelling and Control

2nd year CROPGEN meeting, 6th February 2006, ViennaAlexandra WolfsbergerUniversity of Natural Resources and Applied Life Science,ViennaDepartment of BiotechnologyInstitute for Applied Microbiology


University of Natural Resources andApplied Life Science, ViennaUniversität für Bodenkultur Wien

ContentContent

•Objectives

•Anaerobic Digestions Models

•Anaerobic Digestion Model No.1

•Advantages & Disadvantages

•Parameter

•Implementation, Extensions and Adaptation

•Virtual Laboratory

•Summary & Conclusion



ObjectivesObjectives

•Further development of an existing Anaerobic Digestion Model

•Implementation of this model in a web-based Virtual Laboratory (VL)

•Basis of the VL is the Anaerobic Digestion Model No.1 (Batstone et al., 2002)

•Creation of a Decision Support System

•Identification of process-control strategies and fermentation mixtures



Anaerobic Digestion ModelsAnaerobic Digestion Models

•Hydrolysis controlled Anaerobic Digestion (Jain et al., 1991)

•Model for Dynamic Simulation of Complex Substrates - Focusing onAmmonia inhibition (Angelidaki et al., 1993)

•Simulation Model <Methane> (Vavilin et al., 1993)

•Comprehensive Model of Anaerobic Bioconversion of Complex substrates(Angelidaki et al., 1998)

•Model for Meso- and Thermophilic Anaerobic Sewage Sludge(Siegrist et al., 2002)

•Anaerobic Digestion Model No.1 (ADM1) (Batstone et al., 2002)



Anaerobic Digestion model No.1Anaerobic Digestion model No.1(ADM1)(ADM1)

Pa r t i c ul a t e s ( i nc l udi ng i na c t i ve bi oma s s )Pa r t i c ul a t e s ( i nc l udi ng i na c t i ve bi oma s s )

Me t ha ne , Me t ha ne , Ca r bon Di oxi deCa r bon Di oxi de

Hydr oge nHydr oge nAc e t a t eAc e t a t e

Pr opi ona t ePr opi ona t e But yr a t e , But yr a t e , Va l e r a t eVa l e r a t e

Long c ha i n Long c ha i n f a t t y a c i dsf a t t y a c i ds

Suga r sSuga r s Ami no a c i dsAmi no a c i ds

Li pi dsLi pi dsPr ot e i nsPr ot e i nsCa r bohydr a t e s Ca r bohydr a t e s I ne r t s I ne r t s ( s ol ubl e ( s ol ubl e a nd pa r t i c ul a r )a nd pa r t i c ul a r )

Pa r t i c ul a t e s ( i nc l udi ng i na c t i ve bi oma s s )Pa r t i c ul a t e s ( i nc l udi ng i na c t i ve bi oma s s )






Li pi dsLi pi dsPr ot e i nsPr ot e i nsCa r bohydr a t e s Ca r bohydr a t e s I ne r t s I ne r t s ( s ol ubl e ( s ol ubl e a nd pa r t i c ul a r )a nd pa r t i c ul a r )

Li pi dsLi pi dsPr ot e i nsPr ot e i nsCa r bohydr a t e s Ca r bohydr a t e s I ne r t s I ne r t s ( s ol ubl e ( s ol ubl e a nd pa r t i c ul a r )a nd pa r t i c ul a r ) •Model is structured in several steps

characterising the biochemicalprocesses

•DAE: 26 dynamic state variables19 biochemical kineticprocesses3 gas-liquid transfer kineticprocesses

•DE: 32 dynamic state variables6 acid base kineticprocesses

•Implementation in a CSTR



Anaerobic Digestion model No.1Anaerobic Digestion model No.1

•First unified model

•Unified Nomenclature and Kinetics

•Basis for further model approaches

•Describes Process Details

•Lower overall data amount compared to Neuronal Networks

AdvantagesAdvantages



•Need to understand the model

•The model is simplifying the AD process

•No validation of biological parameters

•No information on the effect of inhibitory compounds

•No information on the effect on kinetics in differenttemperature ranges

•Requirement of detailed substrate definition

•The COD flow is rather complex

Anaerobic Digestion model No.1Anaerobic Digestion model No.1DisadvantagesDisadvantages




•Solid Precipitation

•Homoacetogenesis

•Acetate Oxidation

•Lang Chain Fatty Acids Inhibition

•Weak Acid and Fatty Acid Inhibition

•Denitrification

•Sulphate Reduction and Sulphide Inhibition

•Glucose Fermentation

Exclusions from the ADM1Exclusions from the ADM1




•Parameters quoted in the ADM1have a high range of margin

•Parameters suggested from theTask group are suitable for sewagesludge

•Not suitable for energy crops

ParameterParameter

Min Maxkdis 0,25 1 [d-1]khyd,ch 0,041 106 [d-1]khyd,pr 0,0096 10 [d-1]khyd,li 0,0096 10 [d-1]km,su 4 5067 [kgcodkgcod

-1d-1]km,aa 0,5033 53 [kgcodkgcod

-1d-1]km,fa 0,6 363 [kgcodkgcod

-1d-1]




•CaCO3 precipitation and the potential of anaerobic digestionin the thermophilic temperature range (Batstone et al., 2003)

•Modelling of two-stage anaerobic digestion using the IWA Anaerobic DigestionModel No. 1 (ADM1) (Blumenstaat and Keller, 2004)

•ADM1 based virtual plant for the validation of a controller [TELEMAC](Mailleret et al, 2004)

•Benchmark study Modelling Sulphate Reduction using NN and ADM1(Strik et al., 2004)

•Application of the Adm1 model to advanced anaerobic digestion (Parker, 2005)

First International Workshop on the IWA Anaerobic Digestion Model No.1 (ADM1),2nd – 4th September 2005 in Lyngby, Denmark

Implementations, Extensions and Adaptations of theImplementations, Extensions and Adaptations of themodelmodel



Adaptation of the ADM1Adaptation of the ADM1

Pa r t i c ul a t e s ( i nc l udi ng i na c t i ve b i oma s s )Pa r t i c ul a t e s ( i nc l udi ng i na c t i ve bi oma s s )


Sul phur Di oxi de , Sul phur Di oxi de , Ca r bon Di oxi deCa r bon Di oxi de





Li pi dsLi pi dsPr ot e i nsPr ot e i nsCa r bohydr a t e s Ca r bohydr a t e s f a s tf a s t

Ca r bohydr a t e s Ca r bohydr a t e s s l ows l ow

I ne r t s I ne r t s ( s o l ubl e ( s ol ubl e a nd pa r t i c ul a r )a nd pa r t i c u l a r )

Pa r t i c ul a t e s ( i nc l udi ng i na c t i ve b i oma s s )Pa r t i c ul a t e s ( i nc l udi ng i na c t i ve bi oma s s )


Sul phur Di oxi de , Sul phur Di oxi de , Ca r bon Di oxi deCa r bon Di oxi de





Li pi dsLi pi dsPr ot e i nsPr ot e i nsCa r bohydr a t e s Ca r bohydr a t e s f a s tf a s t

Ca r bohydr a t e s Ca r bohydr a t e s s l ows l ow

I ne r t s I ne r t s ( s o l ubl e ( s ol ubl e a nd pa r t i c ul a r )a nd pa r t i c u l a r )



Laboratory ExperimentsLaboratory ExperimentsLab-scale anaerobic Lab-scale anaerobic CSTRsCSTRs



Anaerobic Digestion model No.1Anaerobic Digestion model No.1Model ResultsModel Results

R adjusted= 0.717



Virtual LaboratoryVirtual LaboratoryStructureStructure

European-wide database on crop species

Add of a Save optionSimulated results for anaerobic digestion in form of Figures and Data matrices (Print

option)

ADM1

based model

Choice of Substrate and Mixture of

Substrates

Choice of reactor and plant type

Input of measured

crop and input data

Choice of reactor specific data

Input of measured reactor data

Possibility to change Parameter

Change of model Parameter for the model from project partners and own research

European-wide database on crop species

Add of a Save optionSimulated results for anaerobic digestion in form of Figures and Data matrices (Print

option)

ADM1

based model

Choice of Substrate and Mixture of

Substrates

Choice of reactor and plant type

Input of measured

crop and input data

Choice of reactor specific data

Input of measured reactor data

Possibility to change Parameter

Change of model Parameter for the model from project partners and own research



Virtual LaboratoryVirtual LaboratoryScreenshot 1Screenshot 1



Virtual LaboratoryVirtual LaboratoryScreenshot 2Screenshot 2



Summary & ConclusionSummary & Conclusion

•Since 60s large amount of different AD models

•ADM1 as first unified model

•Adaptation of the model

•Required parameters and measurement

•Adapted ADM1 as basis for a Virtual Laboratory

•2 Versions of the VL (Simple and Advanced)

•Mathematical model as basis for a control tool



Thank you for your attention.



University of Natural Resources and AppliedLife Science, ViennaUniversität für Bodenkultur Wien

Institute for Applied Microbiology (IAM)Alexandra WolfsbergerPeter Holubar

Gregor Mendel-Straße 33, A-1180 WienTel.: +43 1 47654-4416, Fax: +43 1 [email protected]@boku.ac.at , www.boku.ac.at

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