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Application of machine learning for filtered density function closure in MILD combustion

  • Published:2021-03 Issue: Volume:225 Page:160-179
  • ISSN:0010-2180
  • Container-title:Combustion and Flame
  • language:en
  • Short-container-title:Combustion and Flame

Author:

Chen Zhi X.ORCID,Iavarone Salvatore,Ghiasi Golnoush,Kannan Veeraraghavan,D’Alessio Giuseppe,Parente Alessandro,Swaminathan Nedunchezhian

Funder

Mitsubishi Heavy Industries

Institut national de la recherche scientifique

Fondation Philippe Wiener - Maurice Anspach

European Research Council

Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture

Publisher

Elsevier BV

Subject

General Physics and Astronomy,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering,General Chemistry

Reference63 articles.

1. Flameless oxidation to reduce thermal no-formation;Wünning;Prog. Energy Combust. Sci.,1997

2. Mild Combustion;Cavaliere;Prog. Energy Combust. Sci.,2004

3. Physical Insights on MILD Combustion From DNS;Swaminathan;Front. Mech. Eng.,2019

4. Flameless combustion and its potential towards gas turbines;Perpignan;Prog. Energy Combust. Sci.,2018

5. Characteristics of the reaction zone in a combustor operating at mild combustion;Özdemir;Exp. Fluids,2001

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