Extending convolutional neural networks to finite-volume meshes for fine-scale reconstruction of wall-bounded turbulence

Standard convolutional neural networks for turbulence super-resolution are restricted to uniform structured grids, preventing their direct application to the non-uniform and non-orthogonal meshes commonly used in wall-bounded flows and complex geometries. We introduce a finite-volume convolution uni