Data-driven model for Lagrangian evolution of velocity gradients in incompressible turbulent flows

被引:2
作者
Das, Rishita [1 ,2 ]
Girimaji, Sharath S. [3 ]
机构
[1] Indian Inst Sci, Dept Aerosp Engn, Bengaluru 560012, Karnataka, India
[2] Texas A&M Univ, Dept Aerosp Engn, College Stn, TX 77843 USA
[3] Texas A&M Univ, Dept Ocean Engn, College Stn, TX 77843 USA
关键词
turbulence modelling; intermittency; isotropic turbulence; DIRECT NUMERICAL SIMULATIONS; REYNOLDS-NUMBER DEPENDENCE; RESTRICTED EULER EQUATION; DYNAMICS; DISSIPATION; STATISTICS; VORTICITY; FLUID; SHEAR; PHENOMENOLOGY;
D O I
10.1017/jfm.2024.235
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
Velocity gradient tensor, Aij = partial derivative u(i)/partial derivative x(j), in a turbulence flow field is modelled by separating the treatment of intermittent magnitude (A = root A(ij)A(ij)) from that of the more universal normalised velocity gradient tensor, b(ij) = A(ij)/A. The boundedness and compactness of the b(ij)-space along with its universal dynamics allow for the development of models that are reasonably insensitive to Reynolds number. The near-lognormality of the magnitude A is then exploited to derive a model based on a modified Ornstein-Uhlenbeck process. These models are developed using data-driven strategies employing high-fidelity forced isotropic turbulence data sets. A posteriori model results agree well with direct numerical simulation data over a wide range of velocity-gradient features and Reynolds numbers.
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页数:39
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