Skip to main navigation Skip to search Skip to main content

Development of a Genetic Algorithm Tool for the Optimization of the Methanol Oxidation

  • Hongxin Wang
  • , Oskar Haidn
  • , Mehdi Abbasi
  • , Aizhan Nugymanova
  • , Jaroslaw Shvab
  • , Nadezda Slavinskaya
  • Technical University of Munich
  • University of Tehran
  • Al-Farabi Kazakh National University
  • Gesellschaft fur Anlagen-und Reaktorsicherheit GmbH

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

This work presents an automatic optimization tool using the genetic algorithm (GA) for the chemical kinetic model of methanol (CH3OH) oxidation. A total of 54 parameters of 40 important reactions of the reaction model have been optimized. Ignition delay times measured in shock tubes, concentration profiles measured in plug flow reactors, and laminar flame speeds were used for the model validation. Compared to the results of the initial model, the optimized model exhibits a significantly improved predictive capability for the experimental targets. The GA tool developed in this study has been proven effective for optimizing detailed chemical kinetics models.

Original languageEnglish
Article numbere202400199
JournalChemical Engineering and Technology
Volume48
Issue number2
DOIs
StatePublished - Feb 2025

Keywords

  • Reaction mechanism
  • genetic algorithm
  • methanol
  • optimization

Fingerprint

Dive into the research topics of 'Development of a Genetic Algorithm Tool for the Optimization of the Methanol Oxidation'. Together they form a unique fingerprint.

Cite this