γ-Reθt-CF转捩模型在Spalart-Allmaras湍流模型中的推广及验证

doi:10.7527/S1000-6893.2016.0205

流体力学与飞行力学

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γ-Re_θt-CF转捩模型在Spalart-Allmaras湍流模型中的推广及验证

鞠胜军, 阎超, 叶志飞

北京航空航天大学航空科学与工程学院, 北京 100083

收稿日期:2016-04-28 修回日期:2016-06-25 出版日期:2017-04-15 发布日期:2016-07-18
通讯作者: 阎超 E-mail:yanchao@buaa.edu.cn

Genevalization and validation of γ-Re_θt-CF transition modeling in combination with Spalart-Allmaras turbulence model

JU Shengjun, YAN Chao, YE Zhifei

School of Aeronautic Science and Engineering, Beihang University, Beijing 100083, China

Received:2016-04-28 Revised:2016-06-25 Online:2017-04-15 Published:2016-07-18

摘要/Abstract

摘要：

横流（CF）不稳定性是三维流动中诱发转捩的一项非常重要的因素，考虑到γ-Re_θt-CF转捩模型对流向Tollmien-Schlichting波和横流波不稳定性引起转捩的判定均是完全基于当地变量，且Spalart-Allmaras（SA）湍流模型计算效率高，因而将γ-Re_θt-CF转捩模型与SA湍流模型相结合，并将其引入开源Standford University Unstructured（SU²）计算流体力学分析平台。为了考察和验证模型的预测精度，分别使用原始γ-Re_θt模型和γ-Re_θt-CF-SA模型，对NLF（2）-0415后掠翼型和标准6：1椭球模型进行了转捩预测数值模拟。算例结果表明，γ-Re_θt-CF-SA模型的计算结果与试验数据吻合程度远远优于原始γ-Re_θt模型，γ-Re_θt-CF-SA模型能正确地预测出三维流动中的横流不稳定性引起转捩的现象。

关键词: 转捩模型, 横流不稳定性, 基于当地变量, 动量厚度, 间歇因子

Abstract:

One of the major 3D transition mechanisms is transition due to crossflow (CF) instability. The γ-Re_θt-CF transition model is a local correlation-based approach for prediction of transition caused either by Tollmien-Schlichting steamwise instability or crossflow instability. In order to improve the efficiency, γ-Re_θt-CF-SA model is coupled with the one-equation Spalart-Allmaras (SA) turbulence model, and is then implemented in open-source Standford University Unstructured (SU²), a platform for computational fluid dynamics analyses. In order to validate and assess prediction accuracy of new model, a series of transition flows are simulated including NLF(2)-0415 swept airfoil and 6:1 prolate spheroid standard model. Computation results using γ-Re_θt-CF-SA model are in good agreement with available experimental data, far superior to those using original γ-Re_θt model. Model proposed can effectively predict location of crossflow instability transition.

Key words: transition model, crossflow instability, local correlation-based, momentum thickness, intermittency

中图分类号:

V221.3

鞠胜军, 阎超, 叶志飞. γ-Re_θt-CF转捩模型在Spalart-Allmaras湍流模型中的推广及验证[J]. 航空学报, 2017, 38(4): 120383-120383.

JU Shengjun, YAN Chao, YE Zhifei. Genevalization and validation of γ-Re_θt-CF transition modeling in combination with Spalart-Allmaras turbulence model[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2017, 38(4): 120383-120383.

参考文献

[1] 朱自强, 吴宗成, 丁举春. 层流流动控制技术及应用[J]. 航空学报, 2011, 32(5):765-784. ZHU Z Q, WU Z C, DING J C. Laminar flow control tech-nology and application[J]. Acta Aeronoutica et Astronautica Sinica, 2011, 32(5):765-784 (in Chinese).
[2] LI X L, FU D X, MA Y W. Direct numerical simulation of hypersonic boundary layer transition over a blunt cone with a small angle of attack[J]. Physics of Fluids, 2010, 22(1):90-105.
[3] ANTONIOS M, LUCA B, PHIPIPP S.DNS and LES of estimation and control of transition in boundary layers subject[J]. International Journal of Heat and Fluid Flow 2008, 29(2):841-855.
[4] SU C H, ZHOU H. Transition prediction of a hypersonic boundary layer over a cone at small angle of attack-with the improvement of e^N method[J]. Science in China Series G:Physics, Mechanics & Astronomy, 2009, 52(1):115-123.
[5] MICHEL R. Etude de la transition sur les profilsd'aile:Report 1/1578A 192[R]. ONERA, 1952.
[6] MARK D, MICHEL B. Viscous-inviscid analysis of transonic and low reynolds number airfoils[J]. AIAA Journal 1986, 25(10):1347-1355.
[7] CODER J G, MAUGHMER M D. A CFD-compatible transition model using an amplification factor transport equation[C]//Grapevine Texas 51st AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition. Reston:AIAA, 2013.
[8] 王亮, 符松. 一种适用于超音速边界层的湍流转捩模式[J]. 力学学报, 2009, 41(2):162-168. WANG L, FU S. A new transition/turbulence model for the flow transition in supersonic boundary layer[J]. Chinese Journal of Theoretical and Applied Mechanics, 2009, 41(2):162-168 (in Chinese).
[9] LANGTRY R B, MENTER F R. Transition modeling for general CFD applications in aeronautics:AIAA-2005-0522[R]. Reston:AIAA, 2005.
[10] SHIVAJI M, JAMES D B. Application of the correlation-based γ-Re_θt transition model to Spalart-Allmaras turbulence model:AIAA-2011-3979[R]. Reston:AIAA, 2011.
[11] JEONG H S, SOO H P. Modeling and prediction of the crossflow transition using transition transport equations:AIAA-2015-3160[R]. Reston:AIAA, 2015.
[12] COMELIA G, ANDREAS K. Extension of the γ-Re_θt model for prediction of crossflow transition:AIAA-2014-1269[R]. Reston:AIAA, 2014.
[13] MEDIDA S, BAEDER J D.A new crossflow transition onset criterion for RANS turbulence models[C]//Grapevine Texas 51st AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition. Reston:AIAA, 2013.
[14] SEYFERT C, KRUMBEIN. A correlation-based transition turbulent modeling for three-dimensional aerodynamic configurations:AIAA-2012-0448[R]. Reston:AIAA, 2012.
[15] 徐家宽, 白俊强, 乔磊, 等. 横流不稳定性转捩预测模型[J]. 航空学报, 2015, 36(6):1814-1822. XU J K, BAI J Q, QIAO L, et al. Transition model for predicting crossflow instabilities[J]. Acta Aeronoutica et Astronautica Sinica, 2015, 36(6):1814-1822 (in Chinese).
[16] ROBIN B, LANGTRY, KAUSTAV S, et al. Extending the γ-Re_θt local correlation based transition model for crossflow effects:AIAA-2015-2474[R]. Reston:AIAA, 2015.
[17] RADEZTSKY R H, REIBERT M S, SARIC W S, et al. Effect of micron-sized roughness on transition in swept-wing flows:AIAA-1993-0076[R]. Reston:AIAA, 1993.
[18] DAGENHART J R, SARIC W S. Crossflow stability and transition experiments in swept-wing flow:TP 1999-209344[R]. Washington, D.C.:NASA, 1999.
[19] KREPLIN H P, VOLLMERS H, MEIER H U. Wall shear stress measurements on an inclined prolate spheroid in the DFVLR 3 m×3 m low speed wind tunnel:Report IB 22-84 A 33[R]. G ttingen:DFVLR-AVA, 1985.
[20] KRIMMELBEIN N, KRUMBEIN A. Automatic transition prediction for three-dimensional configurations with focuson industrial application[J]. AIAA Journal of Aircraft, 2011, 48(6):1878-1887.

E-mail：hkxb@buaa.edu.cn

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

γ-Re_θt-CF转捩模型在Spalart-Allmaras湍流模型中的推广及验证

Genevalization and validation of γ-Re_θt-CF transition modeling in combination with Spalart-Allmaras turbulence model

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γ-Reθt-CF转捩模型在Spalart-Allmaras湍流模型中的推广及验证

Genevalization and validation of γ-Reθt-CF transition modeling in combination with Spalart-Allmaras turbulence model

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γ-Re_θt-CF转捩模型在Spalart-Allmaras湍流模型中的推广及验证

Genevalization and validation of γ-Re_θt-CF transition modeling in combination with Spalart-Allmaras turbulence model