A fully automatic and robust hybrid Reynolds-averaged Navier-Stokes/large eddy simulation approach based on the Menter shear stress transport k-ω model
A robust hybrid Reynolds-Averaged Navier-Stokes (RANS)/Large Eddy Simulation (LES) strategy is proposed for a treatment of attached turbulent boundary layers with the RANS Menter Shear Stress Transport (SST) k-omega model irrespective of the grid density and pressure gradient and a quick RANS/LES switching after separation which is automatic, i.e., without shielding-related meshing constraints for the user. This formulation of Zonal Detached Eddy Simulation (ZDES) mode 2 (2020) initially based on the Spalart-Allmaras RANS model relies on local flow quantities providing a RANS shielding identified as a critical limitation of most popular RANS/LES models. The flow sensors are adapted for the SST context and calibrated on RANS boundary-layer-equation solutions over a wide Reynolds-number and pressure-gradient range approaching flow separation and on full Navier-Stokes RANS solutions with separations. The Reynolds-invariant protection includes the outer part of the boundary layer profile, crucial in adverse pressure gradients but ignored by older protection functions such as fd of Delayed Detached Eddy Simulation (DDES) (2006). The shielding resistance to infinite mesh refinement is demonstrated in a flat-plate boundary layer. A second test case involving a backward-facing step shows that the enhanced protection has no detrimental impact on the quick RANS/LES switching thanks to the efficient detection of separation and reinforced destruction of eddy viscosity in gray areas. This indicates that the proposed ZDES mode 2 (2020) Menter SST k-omega achieves safe and automatic RANS shielding of attached boundary layers and efficient RANS/LES switching in massive flow separations, paving the way for its application.
机构:
Chinese Acad Sci, Inst Mech, LNM, Beijing 100190, Peoples R China
Univ Chinese Acad Sci, Sch Engn Sci, Beijing 10049, Peoples R ChinaChinese Acad Sci, Inst Mech, LNM, Beijing 100190, Peoples R China
Liu, Yi
Zhou, Zhiteng
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Chinese Acad Sci, Inst Mech, LNM, Beijing 100190, Peoples R China
Univ Chinese Acad Sci, Sch Engn Sci, Beijing 10049, Peoples R ChinaChinese Acad Sci, Inst Mech, LNM, Beijing 100190, Peoples R China
Zhou, Zhiteng
Zhu, Lixing
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机构:
Chinese Acad Sci, Inst Mech, LNM, Beijing 100190, Peoples R China
Univ Chinese Acad Sci, Sch Engn Sci, Beijing 10049, Peoples R ChinaChinese Acad Sci, Inst Mech, LNM, Beijing 100190, Peoples R China
Zhu, Lixing
Wang, Shizhao
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机构:
Chinese Acad Sci, Inst Mech, LNM, Beijing 100190, Peoples R China
Univ Chinese Acad Sci, Sch Engn Sci, Beijing 10049, Peoples R ChinaChinese Acad Sci, Inst Mech, LNM, Beijing 100190, Peoples R China
机构:
NASA, John H Glenn Res Ctr Lewis Field, Nozzle Branch, Cleveland, OH 44135 USANASA, John H Glenn Res Ctr Lewis Field, Nozzle Branch, Cleveland, OH 44135 USA
Georgiadis, NJ
Alexander, JID
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机构:NASA, John H Glenn Res Ctr Lewis Field, Nozzle Branch, Cleveland, OH 44135 USA
Alexander, JID
Reshotko, E
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机构:NASA, John H Glenn Res Ctr Lewis Field, Nozzle Branch, Cleveland, OH 44135 USA
机构:
NASA Langley Res Ctr, Hyperson Air Breathing Prop Branch, Hampton, VA 23681 USAN Carolina State Univ, Dept Mech & Aerosp Engn, Raleigh, NC 27695 USA
机构:
Univ Oxford, Dept Engn Sci, Oxford OX1 3PJ, England
Univ Calif San Diego, Ctr Energy Res, La Jolla, CA 92093 USAUniv Oxford, Dept Engn Sci, Oxford OX1 3PJ, England
机构:
Mississippi State Univ, Ctr Adv Vehicular Syst, Mississippi State, MS 39762 USAMississippi State Univ, Dept Mech Engn, Mississippi State, MS 39762 USA
Shushan, S.
Walters, D. K.
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Mississippi State Univ, Dept Mech Engn, Mississippi State, MS 39762 USAMississippi State Univ, Dept Mech Engn, Mississippi State, MS 39762 USA