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Multi-layer analytic solution for k-ωmodel equations via a symmetry approach
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作者 Fan TANG weitao bi Zhensu SHE 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI CSCD 2023年第2期289-306,共18页
Despite being one of the oldest and most widely-used turbulence models in engineering computational fluid dynamics(CFD),the k-ωmodel has not been fully understood theoretically because of its high nonlinearity and co... Despite being one of the oldest and most widely-used turbulence models in engineering computational fluid dynamics(CFD),the k-ωmodel has not been fully understood theoretically because of its high nonlinearity and complex model parameter setting.Here,a multi-layer analytic expression is postulated for two lengths(stress and kinetic energy lengths),yielding an analytic solution for the k-ωmodel equations in pipe flow.Approximate local balance equations are analyzed to determine the key parameters in the solution,which are shown to be rather close to the empirically-measured values from the numerical solution of the Wilcox k-ωmodel,and hence the analytic construction is fully validated.The results provide clear evidence that the k-ωmodel sets in it a multilayer structure,which is similar to but different,in some insignificant details,from the Navier-Stokes(N-S)turbulence.This finding explains why the k-ωmodel is so popular,especially in computing the near-wall flow.Finally,the analysis is extended to a newlyrefined k-ωmodel called the structural ensemble dynamics(SED)k-ωmodel,showing that the SED k-ωmodel has improved the multi-layer structure in the outer flow but preserved the setting of the k-ωmodel in the inner region. 展开更多
关键词 turbulence model k-ωmodel structural ensemble dynamics(SED) multilayer structure SYMMETRY
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神经网络增强SED-SL建模应用于翼型绕流湍流计算
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作者 黄文霄 刘溢浪 +2 位作者 毕卫涛 高毅卓 陈军 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2024年第3期72-86,共15页
本文采用SED-SL-RBF的新型建模方法,利用有限NACA机翼的空气动力学数据增强了SED-SL(壁湍流的结构系综动力学-应力长)模型,构建了机翼上湍流边界层的多层结构(MLS),并利用机器学习从实验数据中重建模型参数.该方法应用于九种不同类型的N... 本文采用SED-SL-RBF的新型建模方法,利用有限NACA机翼的空气动力学数据增强了SED-SL(壁湍流的结构系综动力学-应力长)模型,构建了机翼上湍流边界层的多层结构(MLS),并利用机器学习从实验数据中重建模型参数.该方法应用于九种不同类型的NACA机翼上的湍流,具有广泛的雷诺数和攻角范围.研究采用RBF(径向基函数)神经网络重建模型参数(l^(∞)_(0)和y^(∞)_(buf)),并将其应用于SED-SL的CFD数值计算.相较Menter SST湍流模型,SED-SL-RBF模型提升了在同样几何形状和流动条件下升力和阻力系数的预测精度.预测升力系数C_(L)的精确度超过了95%,而预测阻力系数C_(D)的误差则小于6 count.神经网络增强的SED-SL模型对压力场的预测精度也非常高.NACA 2421的MLS参数表现出不随攻角变化的相似性,并可视其为由雷诺数刻画的函数.该结果表明,NACA2421的MLS参数与失速前的攻角大小无关.该相似行为为模拟各种物理条件下的机翼流动提供了一种可行的方案.未来期望整合数据以揭示模型参数方面的模型内在差异,从而将SED-SL-RBF模型的适用性扩展到更广泛的流动场景. 展开更多
关键词 Structural ensemble dynamics RANS model Turbulent boundary layer Machine learning Neural network
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Accurately predicting hypersonic transitional flow on cone via a symmetry approach
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作者 weitao bi Kexin ZHENG +1 位作者 Zhou WEI Zhensu SHE 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2023年第7期337-347,共11页
A new algebraic transition model is proposed based on a Structural Ensemble Dynamics(SED)theory of wall turbulence,for accurately predicting the hypersonic flow heat transfer on cone.The model defines the eddy viscosi... A new algebraic transition model is proposed based on a Structural Ensemble Dynamics(SED)theory of wall turbulence,for accurately predicting the hypersonic flow heat transfer on cone.The model defines the eddy viscosity in terms of a two-dimensional multi-regime distribution of a Stress Length(SL)function,and hence is named as SED-SL.This paper presents clear evidence of precise predictions of transition onset location and peak heat flux of a wide range of hypersonic Transitional Boundary Layers(TrBL)around straight cone at zero incidence,to an unprecedented accuracy as validated by over 70 measurements for varying five crucial influential factors(Mach number,temperature ratio,cone half angle,nose Reynolds number and noise level).The results demonstrate the universality of the postulated multi-regime similarity structure,in characterizing not only the spatial non-uniform distribution of the eddy viscosity in hypersonic TrBL on cone,but also the dependence of the transition onset location on the five influential factors.The latter yields a novel correlation formula for transition center Reynolds number which takes similar functional form as the SL function within the symmetry approach.It is concluded that the SED-SL model simulates TrBL around cone with uniformly high accuracy,and then points out to an optimistic alternative way to construct hypersonic transition model. 展开更多
关键词 CONES Heat flux Hypersonic boundary layers Transition flow Turbulence models
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β-distribution for Reynolds stress and turbulent heat flux in relaxation turbulent boundary layer of compression ramp
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作者 YanChao Hu weitao bi +1 位作者 ShiYao Li ZhenSu She 《Science China(Physics,Mechanics & Astronomy)》 SCIE EI CAS CSCD 2017年第12期36-44,共9页
A challenge in the study of turbulent boundary layers(TBLs) is to understand the non-equilibrium relaxation process after separation and reattachment due to shock-wave/boundary-layer interaction. The classical boundar... A challenge in the study of turbulent boundary layers(TBLs) is to understand the non-equilibrium relaxation process after separation and reattachment due to shock-wave/boundary-layer interaction. The classical boundary layer theory cannot deal with the strong adverse pressure gradient, and hence, the computational modeling of this process remains inaccurate. Here, we report the direct numerical simulation results of the relaxation TBL behind a compression ramp, which reveal the presence of intense large-scale eddies, with significantly enhanced Reynolds stress and turbulent heat flux. A crucial finding is that the wall-normal profiles of the excess Reynolds stress and turbulent heat flux obey a β-distribution, which is a product of two power laws with respect to the wall-normal distances from the wall and from the boundary layer edge. In addition, the streamwise decays of the excess Reynolds stress and turbulent heat flux also exhibit power laws with respect to the streamwise distance from the corner of the compression ramp. These results suggest that the relaxation TBL obeys the dilation symmetry, which is a specific form of self-organization in this complex non-equilibrium flow. The β-distribution yields important hints for the development of a turbulence model. 展开更多
关键词 compression ramp relaxation turbulent boundary layer Reynolds stress β-distribution symmetry
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