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A genetic algorithm with decimal coding for the estimation of kinetic and energetic parameters

Authors
Journal
Chemometrics and Intelligent Laboratory Systems
0169-7439
Publisher
Elsevier
Publication Date
Volume
50
Issue
1
Identifiers
DOI: 10.1016/s0169-7439(99)00057-x
Keywords
  • Genetic Algorithm
  • Kinetic Parameter Estimation
  • Saponification Of Ethyl Acetate
  • Calorimetric Reactor
Disciplines
  • Chemistry
  • Computer Science
  • Mathematics

Abstract

Abstract A hybrid estimation method is proposed to estimate simultaneously the kinetic and energetic parameters of chemical models. This method combines a genetic algorithm with a local convergence method, the former generating initialisation points for the latter. The method is applied to a real complex chemical system: the saponification of ethyl acetate at a concentration of 1 mol l −1. The reaction is carried out in a calorimetric reactor which determines experimental profiles of power delivered or absorbed by the reaction mass. A model, based on mass and energy balances in the reaction mass, including the kinetic and energetic parameters of the reaction, allows to calculate the power profile. The comparison between the experimental and calculated profiles gives the criterion to minimise. The parameters of the model are successfully determined. The hybrid method determines more efficiently and more rapidly the solution of the problem than a set of several estimations with a local convergence method.

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