Automating the generation of detailed kinetic models for halocarbon combustion with the Reaction Mechanism Generator
Automating the generation of detailed kinetic models for halocarbon combustion with the Reaction Mechanism Generator
复制标题
使用反应机制生成器自动生成卤化碳燃烧的详细动力学模型
DOI:
10.1016/j.proci.2022.07.204
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发表时间:
2023
影响因子:
3.4
通讯作者:
West, Richard H.
中科院分区:
文献类型:
--
作者:
Farina, David S.;Sirumalla, Sai Krishna;West, Richard H.
Originally developed to predict the chemical kinetics of hydrocarbon combustion via automated generation of detailed reaction mechanisms, Reaction Mechanism Generator (RMG) contains extensive thermokinetic data for C, H, O chemisty, and has more recently been expanded to nitrogen and sulfur. In this work, we present the addition of halogen (fluorine, chlorine, and bromine) chemisty to RMG to enable automated generation of detailed kinetic models for halocarbon combustion. RMG’s existing reaction templates are updated to include halogens, and 11 new reactions families are created specific to halogen chemistry. Notably, kinetics for more than 1000 elementary reactions are calculated via ab inito methods and transition state theory, and these kinetic data are combined with kinetics from literature sources to train rate rule decision tree estimators. Additionally, halogen groups are added to RMG’s statistical mechanics database, enabling model generation with RMG’s pressure dependence module and automated computation of microcanonical rate constants for unimolecular networks. Halogen groups are also incorporated in RMG’s transport database to provide estimated parameters for the Lennard-Jones potential, important for transport-dependent simulations including laminar flame speeds. To demonstrate RMG’s capability for predicting halocarbon combustion, RMG is used to build a flame suppression model for 2-BTP (CH 2= CBrCF 3) in methane flames. The laminar flame speeds of RMG’s 2-BTP model show good agreement with a published model under a variety of reaction conditions. Automating the generation of detailed kinetic models for halocarbon combustion will facilitate the exploration of previously unexplored reaction pathways, thereby accelerating the development of greener refrigerants and suppressants, as well as advancing the field of automated mechanism generation.
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DOI:
--
发表时间:
2018
期刊:
影响因子:
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作者:
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通讯作者:
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DOI:
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发表时间:
2019
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2016
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2016
期刊:
影响因子:
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作者:
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影响因子:
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作者:
Farina, David S., Jr.;Sirumalla, Sai Krishna;West, Richard H.
通讯作者:
West, Richard H.