pyCALC-RANS
pyCALC-RANS with EARSM which was improved using Machine Learning (Neural Network) pyCALC-RANS has now been extended with PINN (Physical-Informed-Neural-Network) for improving the k-omega turbulence model pyCALC-RANS is a 2D finite volume code. It is fully vectorized (i.e. no for loops). The solution procedure is based on the pressure-correction method (SIMPLEC). Two methods for discretizing the convection terms are available, second-order central differencing and a hybrid scheme of first-order upwind and second-order central differencing. The discretized equations are solved with Pythons sparse matrix solvers. The standard k-omega model is implented. pyCALC-RANS has now been extended with EARSM (Explicit Algebraic Reynolds Stress turbulence Model) which has been improved using Neural Network. To run the Neural Network code and the EARSM, please read the README file.
Department of Mechanics and Maritime Sciences Division of Fluid Dynamice |