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Titel:

Machine-learning-augmented domain decomposition method for near-wall turbulence modeling

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Lyu, Shiyu; Kou, Jiaqing; Adams, Nikolaus A.
Abstract:
To tackle the challenging near-wall turbulence modeling while preserving low computational cost, the near-wall nonoverlapping domain decomposition (NDD) method is proposed, incorporating the machine-learning technique. Using recently proposed implicit NDD (INDD), the solution can be calculated with a Robin-type (slip) wall boundary condition on a relatively coarse mesh and then corrected in the near-wall region at every iteration through an estimated turbulent viscosity profile obtained from a n...     »
Dewey Dezimalklassifikation:
620 Ingenieurwissenschaften
Zeitschriftentitel:
Physical Review Fluids
Jahr:
2024
Band / Volume:
9
Heft / Issue:
4
Nachgewiesen in:
Scopus
Sprache:
en
Volltext / DOI:
doi:10.1103/physrevfluids.9.044603
Verlag / Institution:
American Physical Society (APS)
E-ISSN:
2469-990X
Publikationsdatum:
05.04.2024
TUM Einrichtung:
Lehrstuhl für Aerodynamik und Strömungsmechanik
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