Published in

Elsevier, Computers and Chemical Engineering, (58), p. 269-277

DOI: 10.1016/j.compchemeng.2013.07.013

Links

Tools

Export citation

Search in Google Scholar

Model selection and parameter estimation for chemical reactions using global model structure

Journal article published in 2013 by L. G. M. de Souza, H. Haida, D. Thévenin, A. Seidel Morgenstern, G. Janiga ORCID
This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Green circle
Preprint: archiving allowed
Red circle
Postprint: archiving forbidden
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

In complex reaction systems, such as those found in heterogeneous catalytic reactions, several alternative kinetic models are usually considered in an effort to describe reaction kinetics. The number of plausible mechanisms can be very large, even for systems with a small number of reactions and components. Usually, only a restricted number of models are investigated in detail, since the evaluation of a large number of complex models is extremely time-consuming. In this work, a methodology is described, which allows performing efficiently a global search within all plausible models and parameter sets using the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The developed methodology is applied to the parameter estimation and model optimization of the partial oxidation of ethane reaction network. The present approach allows the reliable investigation of a considerable number of models mechanisms in an automatic manner and in a short computational time. It appears to be a very effective way to optimize complex reaction mechanisms.