polymathic-ai/shear_flow

该数据集描述了二维周期不可压缩剪切流的特性，包括1120个模拟（28个PDE参数乘以40个初始条件）。数据集包含200个时间步长的128×256图像，其中有示踪剂（标量场）、压力（标量场）和速度（矢量场）。该数据集是在单精度下使用7个具有64个CPU核心的节点生成的，每个节点并行运行32个任务。数据集的挑战在于剪切流的非线性特性，这对于预测不同雷诺数和施密特数下的剪切流行为至关重要。

This dataset describes the characteristics of 2D periodic incompressible shear flow, including 1120 simulations (28 PDE parameters times 40 initial conditions). The dataset contains 200 time-steps of 128x256 images, which include tracer (scalar field), pressure (scalar field), and velocity (vector field). The dataset was generated using single precision on 7 nodes with 64 CPU cores each, running 32 tasks in parallel per node. The challenge of the dataset lies in the non-linear nature of shear flow, which is essential for predicting the behavior of shear flow under different Reynolds and Schmidt numbers.