A framework for running computational fluid dynamics simulations in Python with performance comparable to Fortran or C++. You get solvers for 2D/3D Navier-Stokes, shallow water equations, and stratified flows, all using pseudospectral methods with FFT. The workflow is straightforward: configure parameters via dot notation, instantiate a solver, run the simulation, then analyze outputs with built-in plotting for velocity fields, spectra, and spatial means. It supports MPI parallelization for large runs and includes forcing models to maintain turbulence. Good for turbulence studies, vortex dynamics, or geophysical flows where you want the interactivity of Python without sacrificing numerical performance. The parameter objects catch typos with AttributeError, which prevents silent configuration bugs.

skills.sh installs
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GitHub stars
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last updated
Aug 21, 2026

Install

$ npx -y skills add k-dense-ai/scientific-agent-skills --skill fluidsim --agent claude-code

Installs into .claude/skills of the current project.

Files

FluidSim

Use FluidSim 0.9.0 as a framework for Python-defined numerical solvers, especially periodic Cartesian pseudospectral CFD. Upstream FluidSim is CeCILL-2.1; the MIT frontmatter license applies only to this skill.

This skill does not treat a completed run, a stable time step, a smooth plot, or a closed program exit as evidence of numerical convergence or physical validity.

Required workflow

Sponsors

Details

Repository
github.com/k-dense-ai/scientific-agent-skills
Categories
Git & Pull Requests, Code Review & Quality, AI & Agent Building, Productivity & Planning
First seen
Jun 3, 2026

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