Machine Learning and Its Application to Reacting Flows

This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flows. These two fields, ML and turbulent combustion, have large bo...

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Pubblicato in:Lecture Notes in Energy
Enti autori: Swaminathan, Nedunchezhian, Parente, Alessandro
Natura: Livro
Lingua:Inglês
Pubblicazione: Springer Nature 2023
Soggetti:
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THF Fossil fuel technologies
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGM Materials science::TGMB Engineering thermodynamics
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
thema EDItEUR::P Mathematics and Science::PH Physics::PHH Thermodynamics and heat
Machine Learning
Combustion Simulations
Combustion Modelling
Big Data Analysis
Dimensionality reduction
Reduced-order modelling
Neural Networks
Turbulent Combustion
Physics-based modelling
Data-driven modelling
Deep learning
Thermoacoustics and its modelling
Reactive molecular dynamics
Simulations of reacting flows
Accesso online:https://directory.doabooks.org/handle/20.500.12854/96208
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