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

IF 1.6 4区 工程技术 Q3 ENGINEERING, CHEMICAL Chemical Engineering & Technology Pub Date : 2025-01-14 DOI:10.1002/ceat.202400199
Hongxin Wang, Oskar Haidn, Mehdi Abbasi, Aizhan Nugymanova, Jaroslaw Shvab, Nadezda Slavinskaya
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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.

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开发优化甲醇氧化的遗传算法工具
本文提出了一种基于遗传算法的甲醇(CH3OH)氧化化学动力学模型自动优化工具。对反应模型中40个重要反应的54个参数进行了优化。在激波管中测量的点火延迟时间,在塞流反应器中测量的浓度分布,以及层流火焰速度用于模型验证。与初始模型的结果相比,优化后的模型对实验目标的预测能力有了显著提高。在本研究中开发的遗传工具已被证明是有效的优化详细的化学动力学模型。
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来源期刊
Chemical Engineering & Technology
Chemical Engineering & Technology 工程技术-工程:化工
CiteScore
3.80
自引率
4.80%
发文量
315
审稿时长
5.5 months
期刊介绍: This is the journal for chemical engineers looking for first-hand information in all areas of chemical and process engineering. Chemical Engineering & Technology is: Competent with contributions written and refereed by outstanding professionals from around the world. Essential because it is an international forum for the exchange of ideas and experiences. Topical because its articles treat the very latest developments in the field.
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