Khojasteh Ali Rahimi, Laizet Sylvain, Heitz Dominique, Yang Yin
INRAE, OPAALE, 17 avenue de Cucillé, Rennes 35044, France.
Turbulence Simulation Group, Department of Aeronautics, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom.
Data Brief. 2021 Dec 16;40:107725. doi: 10.1016/j.dib.2021.107725. eCollection 2022 Feb.
The dataset contains Eulerian velocity and pressure fields, and Lagrangian particle trajectories of the wake flow downstream of a smooth cylinder at a Reynolds number equal to 3900. An open source Direct Numerical Simulation (DNS) flow solver named Incompact3d was used to calculate the Eulerian field around the cylinder. The synthetic Lagrangian tracer particles were transported using a fourth-order Runge-Kutta scheme in time and trilinear interpolations in space. Trajectories of roughly 200,000 particles for two 3D sub-domains are available to the public. This dataset can be used as a test case for tracking algorithm assessment, exploring the Lagrangian physics, statistic analyses, machine learning, and data assimilation interests.
该数据集包含欧拉速度场和压力场，以及雷诺数等于3900时光滑圆柱体下游尾流的拉格朗日粒子轨迹。使用一个名为Incompact3d的开源直接数值模拟（DNS）流动求解器来计算圆柱体周围的欧拉场。合成拉格朗日示踪粒子在时间上采用四阶龙格-库塔格式、在空间上采用三线性插值进行传输。两个3D子域中大约200,000个粒子的轨迹可供公众使用。该数据集可作为跟踪算法评估、探索拉格朗日物理、统计分析、机器学习和数据同化研究的测试案例。
