fluidsim

You can run high-performance CFD simulations in Python by configuring pseudospectral FFT solvers to execute 2D and 3D Navier-Stokes flow calculations. This framework supports MPI parallelization for HPC environments and provides end-to-end workflows from parameterization to results visualization.

Yes, you can use Python to post-process CFD outputs and plot energy spectra. The framework includes rich post-processing utilities designed for analyzing simulation results, enabling you to calculate spatial means and visualize spectral data directly.

The best way to simulate stratified and shallow-water flows for geophysical applications is using a Python-based pseudospectral solver framework. It specifically supports these flow types alongside standard Navier-Stokes, allowing you to configure parameters and execute high-performance simulations.

Yes, MPI parallelization works seamlessly with Python-based pseudospectral FFT solvers for HPC environments. The framework is optimized for high-performance computing, allowing you to tune parallel execution to efficiently scale your fluid dynamics simulations.

To configure a 2D ns2d simulation with a 256x256 grid in Python, you set the grid resolution, define viscosity parameters, and specify the end time. The framework handles the pseudospectral calculations and allows you to plot the resulting energy spectrum upon completion.