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Optimization of ammonia/methane mixture combustion kinetic model based on Artificial Neural Network

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成果类型:
期刊论文
作者:
Huang, Zhangjun;Dai, Pengfei;Xu, Chenghui;Tian, Hong;Sun, Liutao;...
通讯作者:
Li, XZ
作者机构:
[Li, Xinzhuo; Tian, Hong; Sun, Liutao; Dai, Pengfei; Xu, Chenghui; Huang, Zhangjun; Li, XZ] Changsha Univ Sci & Technol, Sch Energy & Power Engn, Changsha 410114, Peoples R China.
通讯机构:
[Li, XZ ] C
Changsha Univ Sci & Technol, Sch Energy & Power Engn, Changsha 410114, Peoples R China.
语种:
英文
关键词:
Ammonia/methane mixture combustion;Mechanism reduction;Mechanism optimization;Artificial Neural Network;NO x emissions
期刊:
Applied Thermal Engineering
ISSN:
1359-4311
年:
2025
卷:
264
页码:
125484
基金类别:
Natural Science Foundation of Hunan Province [2024JJ6031]
机构署名:
本校为第一且通讯机构
院系归属:
能源与动力工程学院
摘要:
The application of ammonia/methane (NH 3 /CH 4 ) blended fuels in gas turbines has received considerable attention, and the development of their combustors requires the implementation of more precise and compact reaction mechanisms. In this work, we propose a new optimization mechanism for ammonia/methane and comprehensively verify the performance of the optimization mechanism. A detailed chemical mechanism with 65 species and 466 reactions (Detailed-Mech) was first assembled using models from the literature. A directed relation graph with error propagation (DRGEP) and computational singular p...

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