Literature DB >> 22653035

Identification in an anaerobic batch system: global sensitivity analysis, multi-start strategy and optimization criterion selection.

Andres Donoso-Bravo1, Johan Mailier, Gonzalo Ruiz-Filippi, Alain Vande Wouwer.   

Abstract

Several mathematical models have been developed in anaerobic digestion systems and a variety of methods have been used for parameter estimation and model validation. However, structural and parametric identifiability questions are relatively seldom addressed in the reported AD modeling studies. This paper presents a 3-step procedure for the reliable estimation of a set of kinetic and stoichiometric parameters in a simplified model of the anaerobic digestion process. This procedure includes the application of global sensitivity analysis, which allows to evaluate the interaction among the identified parameters, multi-start strategy that gives a picture of the possible local minima and the selection of optimization criteria or cost functions. This procedure is applied to the experimental data collected from a lab-scale sequencing batch reactor. Two kinetic parameters and two stoichiometric coefficients are estimated and their accuracy was also determined. The classical least-squares cost function appears to be the best choice in this case study.

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Year:  2012        PMID: 22653035     DOI: 10.1007/s00449-012-0758-5

Source DB:  PubMed          Journal:  Bioprocess Biosyst Eng        ISSN: 1615-7591            Impact factor:   3.210


  2 in total

1.  Identifiability of tissue material parameters from uniaxial tests using multi-start optimization.

Authors:  Babak N Safa; Michael H Santare; C Ross Ethier; Dawn M Elliott
Journal:  Acta Biomater       Date:  2021-01-11       Impact factor: 8.947

2.  Assessment and parameter identification of simplified models to describe the kinetics of semi-continuous biomethane production from anaerobic digestion of green and food waste.

Authors:  Raymond O Owhondah; Mark Walker; Lin Ma; Bill Nimmo; Derek B Ingham; Davide Poggio; Mohamed Pourkashanian
Journal:  Bioprocess Biosyst Eng       Date:  2016-03-09       Impact factor: 3.210

  2 in total

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