fluidsim

You can run CFD simulations in Python by configuring a hierarchical Parameters object and selecting pseudospectral solvers for 2D/3D Navier-Stokes, shallow water, or stratified flows. FluidSim provides this framework to execute and analyze complex periodic domain flows.

Yes, MPI parallelization is supported for high-performance fluid dynamics simulations in Python. FluidSim integrates MPI to enable scalable execution of pseudospectral solvers, allowing researchers to run large-scale parameter sweeps and performance tests efficiently.

Spectral solver execution requires a Python 3.9+ environment, compatible FFT libraries, and optional MPI configurations. You create a typed hierarchical Parameters object to safely configure the simulation before running and post-processing the output fields.

To analyze a 2D turbulence experiment, you configure the ns2d solver with a noise initial field, execute the simulation, and use post-processing tools to evaluate energy spectra and vorticity fields. This workflow is directly supported by the pseudospectral framework.

Pseudospectral solvers provide high-fidelity results for periodic domains by computing spatial derivatives in Fourier space, unlike traditional finite difference methods. This approach offers high accuracy for fluid turbulence simulations while maintaining Python accessibility and MPI scalability.

Python-based pseudospectral CFD solvers are primarily limited to periodic domain boundaries and require specific FFT libraries plus Python 3.9+. Users must also navigate a hierarchical Parameters object for safe, typed configuration to avoid runtime errors during complex flow execution.