Cylinder in Crossflow
Introduced by Tencer et al. in A Tailored Convolutional Neural Network for Nonlinear Manifold Learning of Computational Physics Data using Unstructured Spatial Discretizations
Cylinder in Crossflow is a synthetic dataset that involves unsteady laminar flow past a cylinder that generates vortex shedding pattern known as a von Kármán vortex street. The governing equations for this system are the incompressible Navier-Stokes equations. The cylinder has a diameter of 1 and the free stream velocity is 1. The kinematic viscosity $\nu$ is varied such that the Reynolds number is between 100 and 400. Symmetry boundary conditions are applied at the top and bottom edges of the domain and an open pressure boundary condition is applied at the outlet. Solutions are generated on the unstructured mesh of 6384 quad elements.
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