High resolution dataset for flow past arbitrary bodies

This dataset comprises the high-resolution (768 x 512) flowfields for incompressible flow past arbitrarily shaped bodies at low Reynolds number (100, approx.) obtained using FoamExtend based immersed boundary method. The dataset is divided into 3 parts viz. (a) Training dataset containing 50 experiments having 100 frames each (27.5 GB, approx), (b) testing datset containing 50 additional experiments having 300 frames each (82.5 GB, approx), and (c) total dataset (i.e., 100 experiemnts) having 1500 frames each (825 GB, approx). Part (a) forms the training dataset used to train the differentiable physics-assisted neural network (DPNN) whereas part (b) forms the testing dataset for the trained DPNN based model. Finally, part (c) serves as additional dataset for further validation and benchmarking. The dataset only includes the stastically stable velocity flowfields (i.e., time 150s onwards spaced at 0.1s) along with shape mask. The 100 experiments comprises of 100 different geometric configurations (i.e, arbitrary bodies placed in an equilateral triangle position), each at a unique spacing ratio. In addition, the coordinates of the underlying bodies are also provided separately.