Description

A DNS decaying homogeneous isotropic turbulence simulation is developed by Wang et al. and runs on Tensor Processing Unit (TPU) platform. The Computational Fluid Dynamics (CFD) framework is employed to solve the variable-density Navier-Stokes equation under a low-Mach approximation. The governing equations are discretized using a finite-difference method on a collocated structured mesh within a cubic computational domain with a side length of 10.24 m. The discretization involves a total of N = 2048 grid points in each direction, resulting in a homogeneous grid spacing of Δ = 5 × 10 ^-3 m. The simulation is initialized with specific turbulence parameters, including an initial Reynolds number Re _λ = 309, initial turbulent kinetic energy k₀ = 24.42 m²/s², and initial ratios of Taylor length scale λ₀/L = 7.49 × 10^-3 and integral length scale l₀/L = 2.84 × 10^-1. Here, λ and l represent the Taylor length scale and integral length scale, respectively. These initial condition set the stage for investigating the temporal evolution and decay characteristics of homogeneous isotropic turbulence within the computational domain.

Quick Info

• Contributors: Qing Wang, Shantanu Shahane, Yifan Chen
• N_x = 2040, N_y = 2040, N_z = 2048, N_ɸ = 4
• DOI
• .bib

Links to different cases

ID	Conditions	Size (GB)	Links
0	TKE = 25.8844, ε = 65.7053	120	KaggleV, KaggleP info.jsonV, info.jsonP
1	TKE = 21.2626, ε = 39.3486	120	KaggleV, KaggleP info.jsonV, info.jsonP
2	TKE = 17.1823, ε = 37.9396	120	KaggleV, KaggleP info.jsonV, info.jsonP
3	TKE = 13.7007, ε = 30.2196	120	KaggleV, KaggleP info.jsonV, info.jsonP
4	TKE = 9.3180, ε = 16.4062	120	KaggleV, KaggleP info.jsonV, info.jsonP
5	TKE = 5.8251, ε = 7.4214	120	KaggleV, KaggleP info.jsonV, info.jsonP
6	TKE = 3.4790, ε = 3.2468	120	KaggleV, KaggleP info.jsonV, info.jsonP
7	TKE = 1.9369, ε = 1.2832	120	KaggleV, KaggleP info.jsonV, info.jsonP
8	TKE = 1.0627, ε = 0.5080	120	KaggleV, KaggleP info.jsonV, info.jsonP
9	TKE = 0.6658, ε = 0.2389	120	KaggleV, KaggleP info.jsonV, info.jsonP
10	TKE = 0.4521, ε = 0.1295	120	KaggleV, KaggleP info.jsonV, info.jsonP
11	TKE = 0.3339, ε = 0.0789	120	KaggleV, KaggleP info.jsonV, info.jsonP
12	TKE = 0.2596 ε = 0.0518	120	KaggleV, KaggleP info.jsonV, info.jsonP
13	TKE = 0.2119, ε = 0.0375	120	KaggleV, KaggleP info.jsonV, info.jsonP
14	TKE = 0.1765, ε = 0.0283	120	KaggleV, KaggleP info.jsonV, info.jsonP
15	TKE = 0.1488, ε = 0.0215	120	KaggleV, KaggleP info.jsonV, info.jsonP
16	TKE = 0.1268, ε = 0.0167	120	KaggleV, KaggleP info.jsonV, info.jsonP
17	TKE = 0.1090, ε = 0.0131	120	KaggleV, KaggleP info.jsonV, info.jsonP
18	TKE = 0.0953, ε = 0.0107	120	KaggleV, KaggleP info.jsonV, info.jsonP
19	TKE = 0.0843, ε = 0.0089	120	KaggleV, KaggleP info.jsonV, info.jsonP