fluidsim

To simulate turbulence using pseudospectral methods in Python, you can configure a solver with parameters like grid size and end time, then execute time stepping to solve the Navier-Stokes equations with FFT acceleration. This approach yields physical fields and spectra for analysis.

The best way to run high-performance CFD simulations for geophysical flows is using a Python framework with MPI-enabled execution and compilation-optimized kernels. This provides scalable performance for solving shallow-water and stratified flows across HPC environments.

Yes, you can use this framework to solve shallow water and stratified flow equations. It includes pseudospectral solvers specifically designed for these geophysical flows, utilizing FFT acceleration to compute high-fidelity simulations and output physical statistics.

Yes, you need MPI and FFT libraries to run scalable Navier-Stokes solvers. The framework requires Python and FFT libraries to configure parameters, while MPI enables HPC-enabled execution and compilation-optimized kernels for scalable parametric explorations.

To configure parameters and post-process outputs for turbulence studies, you create a solver with default settings, adjust variables like nx, ny, and t_end, and start the simulation. The integrated workflow then processes physical fields, spectra, and statistics.