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A Data-Driven Approach to Refine the Partially Stirred Reactor Closure for Turbulent Premixed Flames
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In
Special Issue: Machine Learning for Fluids / Issue Editors: Paola Cinnella, Ricardo Vinuesa
In
Flow, turbulence and combustion 115(3), Seiten/Artikel-Nr.:1235-1260
2025
Online
DOI: 10.18154/RWTH-2025-00611
DOI: 10.1007/s10494-024-00626-3
URL: https://publications.rwth-aachen.de/record/1002659/files/1002659.pdf
Einrichtungen
Thematische Einordnung (Klassifikation)
DDC: 600
OpenAccess: 
PDF
Dokumenttyp
Journal Article/Contribution to a book
Format
online, print
Sprache
English
Anmerkung
Peer reviewed article
Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-85217379114
WOS Core Collection: WOS:001392655200001
Interne Identnummern
RWTH-2025-00611
Datensatz-ID: 1002659
Beteiligte Länder
Belgium, France, Germany, UK
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; Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; DEAL Springer ; Essential Science Indicators ; IF < 5 ; JCR ; Nationallizenz
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