Application of Genetic Algorithm to Chemical Kinetics:  Systematic Determination of Reaction Mechanism and Rate Coefficients for a Complex Reaction Network

2001 ◽  
Vol 105 (16) ◽  
pp. 4052-4058 ◽  
Author(s):  
Masa Tsuchiya ◽  
John Ross
Keyword(s):  
Genetic Algorithm ◽  
Reaction Mechanism ◽  
Chemical Kinetics ◽  
Reaction Network ◽  
Rate Coefficients ◽  
Complex Reaction ◽  
Systematic Determination

Determination of Complex Reaction Mechanisms

2006 ◽  
Author(s):  
John Ross ◽  
Igor Schreiber ◽  
Marcel O. Vlad
Keyword(s):  
Reaction Mechanism ◽  
Reaction Mechanisms ◽  
Reaction Pathway ◽  
Chemical Species ◽  
Rate Coefficients ◽  
Chemical System ◽  
Evolutionary Development ◽  
Complex Reaction ◽  
Oscillatory Reactions

In a chemical system with many chemical species several questions can be asked: what species react with other species: in what temporal order: and with what results? These questions have been asked for over one hundred years about simple and complex chemical systems, and the answers constitute the macroscopic reaction mechanism. In Determination of Complex Reaction Mechanisms authors John Ross, Igor Schreiber, and Marcel Vlad present several systematic approaches for obtaining information on the causal connectivity of chemical species, on correlations of chemical species, on the reaction pathway, and on the reaction mechanism. Basic pulse theory is demonstrated and tested in an experiment on glycolysis. In a second approach, measurements on time series of concentrations are used to construct correlation functions and a theory is developed which shows that from these functions information may be inferred on the reaction pathway, the reaction mechanism, and the centers of control in that mechanism. A third approach is based on application of genetic algorithm methods to the study of the evolutionary development of a reaction mechanism, to the attainment given goals in a mechanism, and to the determination of a reaction mechanism and rate coefficients by comparison with experiment. Responses of non-linear systems to pulses or other perturbations are analyzed, and mechanisms of oscillatory reactions are presented in detail. The concluding chapters give an introduction to bioinformatics and statistical methods for determining reaction mechanisms.

Toward a systematic determination of complex reaction mechanisms

1993 ◽  
Vol 97 (26) ◽  
pp. 6776-6787 ◽  
Author(s):  
Tim Chevalier ◽  
Igor Schreiber ◽  
John Ross
Keyword(s):  
Reaction Mechanisms ◽  
Complex Reaction ◽  
Systematic Determination

Artificial Force Induced Reaction Method for Systematic Determination of Complex Reaction Mechanisms

2016 ◽  
Vol 16 (5) ◽  
pp. 2349-2363 ◽  
Author(s):  
W. M. C. Sameera ◽  
Akhilesh Kumar Sharma ◽  
Satoshi Maeda ◽  
Keiji Morokuma
Keyword(s):  
Reaction Mechanisms ◽  
Complex Reaction ◽  
Reaction Method ◽  
Systematic Determination ◽  
Induced Reaction

A Novel Approach to the Optimisation of Reaction Rate Parameters for Methane Combustion Using Multi-Objective Genetic Algorithms

2003 ◽  
Author(s):  
L. Elliott ◽  
D. B. Ingham ◽  
A. G. Kyne ◽  
N. S. Mera ◽  
M. Pourkashanian ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Reaction Mechanism ◽  
Reaction Rate ◽  
Flame Structure ◽  
Simulated Data ◽  
Methane Combustion ◽  
Rate Coefficients ◽  
Inversion Process ◽  
Multi Objective ◽  
Novel Approach

This study uses a multi-objective genetic algorithm to determine new reaction rate parameters (A’s, β’s and Ea’s in the non-Arrhenius expressions) for the combustion of a methane/air mixture. The multi-objective structure of the genetic algorithm employed allows for the incorporation of both perfectly stirred reactor and laminar premixed flames data in the inversion process, thus enabling a greater confidence in the predictive capabilities of the reaction mechanisms obtained. Various inversion procedures based on reduced sets of data are investigated and tested on methane/air combustion in order to generate efficient inversion schemes for future investigations concerning complex hydrocarbon fuels. The inversion algorithms developed are first tested on numerically simulated data. In addition, the increased flexibility offered by this novel multi-objective GA has now, for the first time, allowed experimental data to be incorporated into our reaction mechanism development. A GA optimised methane air reaction mechanism is presented which offers a remarkable improvement over a previously validated starting mechanism in modelling the flame structure in a stoichiometric methane-air premixed flame (http://www.leeds.ac.uk/ERRI/research/res.html). In addition, the mechanism outperforms the predictions of more detailed schemes and is still capable of modelling combustion phenomena that were not part of the optimisation process. Therefore, the results of this study demonstrate that the genetic algorithm inversion process promises the ability to assess combustion behaviour for fuels where the reaction rate coefficients are not known with any confidence and, subsequently, accurately predict emission characteristics, stable species concentrations and flame characterisation. Such predictive capabilities will be of paramount importance within the gas turbine industry.

scholarly journals Application of the genetic algorithm method in the problem of chemical kinetics of the oxidative regeneration process

2021 ◽  
Vol 2131 (2) ◽  
pp. 022007
Author(s):  
O V Dubinets ◽  
I M Gubaidullin ◽  
R M Uzyanbaev ◽  
M K Vovdenko ◽  
I G Lapshin
Keyword(s):  
Experimental Data ◽  
Genetic Algorithm ◽  
Chemical Kinetics ◽  
Laboratory Installation ◽  
Complex Chemical ◽  
Oxidative Regeneration ◽  
Genetic Algorithm Method ◽  
Complex Chemical Reactions ◽  
Kinetics Of

Abstract Annotation. One of the main problems in chemical kinetics is the establishment of the mechanisms of complex chemical reactions. The inverse problem of chemical kinetics is understood as the determination of the dependence of the concentration of the participating components on the basis of experimental data obtained from a laboratory installation for the oxidative regeneration of coked catalysts. One of the main methods used in inverse problems the genetic algorithm. The algorithms considered in the article make it possible to determine the values of the rate constants of the considered chemical stages.

A Novel Approach to the Optimization of Reaction Rate Parameters for Methane Combustion Using Multi-Objective Genetic Algorithms

2004 ◽  
Vol 126 (3) ◽  
pp. 455-464 ◽  
Author(s):  
L. Elliott ◽  
D. B. Ingham ◽  
A. G. Kyne ◽  
N. S. Mera ◽  
M. Pourkashanian ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Reaction Mechanism ◽  
Reaction Rate ◽  
Flame Structure ◽  
Simulated Data ◽  
Methane Combustion ◽  
Premixed Flame ◽  
Rate Coefficients ◽  
Inversion Process ◽  
Multi Objective

This study uses a multi-objective genetic algorithm to determine new reaction rate parameters (A’s, β’s and Ea’s in the non-Arrhenius expressions) for the combustion of a methane/air mixture. The multi-objective structure of the genetic algorithm employed allows for the incorporation of both perfectly stirred reactor and laminar premixed flame data in the inversion process, thus enabling a greater confidence in the predictive capabilities of the reaction mechanisms obtained. Various inversion procedures based on reduced sets of data are investigated and tested on methane/air combustion in order to generate efficient inversion schemes for future investigations concerning complex hydrocarbon fuels. The inversion algorithms developed are first tested on numerically simulated data. In addition, the increased flexibility offered by this novel multi-objective GA has now, for the first time, allowed experimental data to be incorporated into our reaction mechanism development. A GA optimized methane-air reaction mechanism is presented which offers a remarkable improvement over a previously validated starting mechanism in modeling the flame structure in a stoichiometric methane-air premixed flame (http://www.personal.leeds.ac.uk/∼fuensm/project/mech.html). In addition, the mechanism outperforms the predictions of more detailed schemes and is still capable of modeling combustion phenomena that were not part of the optimization process. Therefore, the results of this study demonstrate that the genetic algorithm inversion process promises the ability to assess combustion behavior for fuels where the reaction rate coefficients are not known with any confidence and, subsequently, accurately predict emission characteristics, stable species concentrations and flame characterization. Such predictive capabilities will be of paramount importance within the gas turbine industry.

OPTIMIZATION OF A SURROGATE REDUCED AVIATION FUEL-AIR REACTION MECHANISM USING A GENETIC ALGORITHM

Clean Air ◽  
2007 ◽  
Vol 8 (1) ◽  
pp. 1-24
Author(s):  
M. Pourkashanian ◽  
N. S. Mera ◽  
Lionel Elliott ◽  
C. W. Wilson ◽  
Derek B. Ingham ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Reaction Mechanism ◽  
Aviation Fuel
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