Machine Learning for Combustion Chemistry

T. Echekki*, A. Farooq, M. Ihme, S. M. Sarathy

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

5 Scopus citations

Abstract

Machine learning provides a set of new tools for the analysis, reduction and acceleration of combustion chemistry. The implementation of such tools is not new. However, with the emerging techniques of deep learning, renewed interest in implementing machine learning is fast growing. In this chapter, we illustrate applications of machine learning in understanding chemistry, learning reaction rates and reaction mechanisms and in accelerating chemistry integration.

Original languageEnglish (US)
Title of host publicationLecture Notes in Energy
PublisherSpringer Science and Business Media Deutschland GmbH
Pages117-147
Number of pages31
DOIs
StatePublished - 2023

Publication series

NameLecture Notes in Energy
Volume44
ISSN (Print)2195-1284
ISSN (Electronic)2195-1292

ASJC Scopus subject areas

  • General Energy

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