Predictive data-driven model based on generative adversarial network for premixed turbulence-combustion regimes. Grenga, T., Nista, L., Schumann, C., Karimi, A., N., Scialabba, G., Attili, A., & Pitsch, H. Combustion Science and Technology, 195(15):3923-3946, Taylor & Francis, 2023.
bibtex   
@article{
 title = {Predictive data-driven model based on generative adversarial network for premixed turbulence-combustion regimes},
 type = {article},
 year = {2023},
 pages = {3923-3946},
 volume = {195},
 publisher = {Taylor & Francis},
 id = {4ff412db-a039-33f9-b4bb-b4b9fc929a7e},
 created = {2024-02-20T06:34:10.688Z},
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 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2024-02-20T06:34:10.688Z},
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 starred = {false},
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 hidden = {false},
 source_type = {article},
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 bibtype = {article},
 author = {Grenga, Temistocle and Nista, Ludovico and Schumann, Christoph and Karimi, Amir Noughabi and Scialabba, Gandolfo and Attili, Antonio and Pitsch, Heinz},
 journal = {Combustion Science and Technology},
 number = {15}
}

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