Data-driven prediction of flame temperature and pollutant emission in distributed combustion

•Machine learning modeling was investigated in lean distributed combustion regime.•Flame temperature and pollutants were predicted using artificial neural network.•Effect of different learning rate on model training was studied.•Current model showed very well prediction in swirl combustion and distr...

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Bibliographic Details
Published in:	Applied energy Vol. 310; p. 118502
Main Authors:	Roy, Rishi, Gupta, Ashwani K.
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 15.03.2022
Subjects:	air flow algorithms Artificial neural network Bayesian theory carbon dioxide combustion data collection Distributed combustion Emission and flame temperature prediction energy Learning rate methane neural networks pollutants prediction Swirl burner temperature Artificial neural network Emission and flame temperature prediction Swirl burner Learning rate Distributed combustion
ISSN:	0306-2619, 1872-9118
Online Access:	Get full text
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