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HEMLAB Algorithm Applied to 4th AIAA CFD High Lift Prediction Workshop

  • Istanbul Technical University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

5 Atıf (Scopus)

Özet

The NASA High-Lift Common Research Model (CRM-HL) has been investigated using the HEMLAB algorithm in order to numerically predict stall characteristics at high angle of attacks. The numerical method is based on a vertex based finite volume method on hybrid meshes using the quad-and half-edge data structures. In order to improve numerical accuracy, the pyAMG anisotropic mesh adaptation library from INRIA is integrated in order to improve mesh resolution near the high gradient regions. The resulting algebraic equations due to the compressible Navier-Stokes and the one equation Spallart-Allmaras turbulence equations are solved in a monolithic manner using the restricted additive Schwarz precon-ditioner combined with the FGMRES Krylov subspace algorithm within the PETSc library. The numerical simulations are carried out around the NASA High-Lift Common Research Model at pre-and post-stall angles of attack. The numerical dissipation effects are observed to be critical for the accuracy of the resulting aerodynamic loads at high angles of attack. The results with the anisotropic mesh refinement indicate relatively good agreement with the committee experimental results.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıAIAA AVIATION 2022 Forum
YayınlayanAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Basılı)9781624106354
DOI'lar
Yayın durumuYayınlandı - 2022
EtkinlikAIAA AVIATION 2022 Forum - Chicago, United States
Süre: 27 Haz 20221 Tem 2022

Yayın serisi

AdıAIAA AVIATION 2022 Forum

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???event.eventtypes.event.conference???AIAA AVIATION 2022 Forum
Ülke/BölgeUnited States
ŞehirChicago
Periyot27/06/221/07/22

Bibliyografik not

Publisher Copyright:
© 2022, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

Finansman

The authors also gratefully acknowledge the use of the computing resources provided by the National Center for High Performance Computing of Turkey (UYBHM) under grant number 10752009, and the computing facilities at TUBITAK ULAKBIM, High Performance and Grid Computing Center. The authors also acknowledge the use of the PRACE – Partnership for Advanced Computing in Europe (DECI-16) resources through the Computing Centre of the Slovak Academy of Sciences supercomputing infrastructure acquired in project ITMS 26230120002 and 26210120002 (Slovak infrastructure for high-performance computing) supported by the Research & Development Operational Programme funded by the ERDF.

FinansörlerFinansör numarası
National Center for High Performance Computing of Turkey
UYBHM10752009
Türkiye Bilimsel ve Teknolojik Araştırma KurumuDECI-16
European Regional Development Fund

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