An artificial intelligence optimization of NOx conversion efficiency under dual catalytic mechanism reaction based on multi-objective gray wolf algorithm

In the era of industry 4.0, artificial intelligence (AI) offers new perspectives for researching the complex sustainable chemical reactions in selective catalytic reduction (SCR). This aims to further improve the utilization and efficiency of SCR. In this study, a fuzzy gray relational analysis coup...

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Bibliographic Details
Published in:Fuel processing technology Vol. 268; p. 108182
Main Authors: Zhang, Zhiqing, He, Zicheng, Wang, Yuguo, Jiang, Feng, Zhong, Weihuang, Zhang, Bin, Ye, Yanshuai, Yin, Zibin, Tan, Dongli
Format: Journal Article
Language:English
Published: Elsevier B.V 01.04.2025
Elsevier
Subjects:
algorithms
ammonia
Artificial intelligence
Canis lupus
catalytic activity
denitrification
Diesel engine
fuels
heat transfer
industry
Machine learning
Multi-objective optimization
neural networks
reaction mechanisms
Selective catalytic reduction
Diesel engine
Multi-objective optimization
Selective catalytic reduction
Artificial intelligence
Machine learning
ISSN:0378-3820
Online Access:Get full text
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Summary:In the era of industry 4.0, artificial intelligence (AI) offers new perspectives for researching the complex sustainable chemical reactions in selective catalytic reduction (SCR). This aims to further improve the utilization and efficiency of SCR. In this study, a fuzzy gray relational analysis coupled with random forest (RF) and back propagation artificial neural network (BP-ANN) model was developed. This model was trained based on the Langmuir-Hinshelwood and Eley-Rideal coupled mechanism for SCR reaction mechanism, and had good fitting effect on the heat transfer rate, catalytic efficiency and ammonia (NH3) slip rate of the catalytic reaction under loading conditions. And this was used as a guiding method to direct the multi-objective gray wolf optimization algorithm to optimize the basic parameters. The optimization results showed that the NH3 slip rate of the SCR was slightly improved and the denitrification efficiency was increased up to 28 % under different loads, which had guiding significance for the lightweighting and thermal control of industrial equipment. •AI model is employed to investigate complex NOx conversiton for multi-objective optimization.•Langmuir-Hinshelwood and Eley-Rideal are coupled for SCR reaction mechanism.•The multi-objective gray wolf optimization algorithm is developed and optimized.
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ISSN:0378-3820
DOI:10.1016/j.fuproc.2025.108182