fluidsim

Automate high-performance CFD simulations and analysis in Python.

1|Updated Apr 4, 2026
One-click install
npx skills add https://github.com/m0at/claudemd --skill fluidsim-m0at
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: fluidsim
Source: https://github.com/m0at/claudemd/tree/main/skills/fluidsim
Command: npx skills add https://github.com/m0at/claudemd --skill fluidsim-m0at

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

FluidSim provides a robust Python framework to run, configure, and analyze high-performance computational fluid dynamics simulations, including Navier-Stokes and related geophysical flows, with built-in HPC support and comprehensive post-processing.

Core Features & Use Cases

  • Object-oriented CFD framework with multiple solvers for 2D/3D NS, shallow water, and stratified flows
  • High-performance execution via compiled components, MPI parallelization, and FFT-based pseudospectral methods
  • End-to-end workflow: parameter configuration, simulation execution, and rich output analysis
  • Interactive visualization and post-processing to derive insights from simulation data

Quick Start

Install FluidSim and run a small example to generate outputs for inspection.

Frequently Asked Questions about fluidsim

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run Navier-Stokes simulations in Python using pseudospectral methods?

You can run Navier-Stokes simulations in Python by configuring solver parameters and executing the simulation through an object-oriented framework. This approach uses FFT-based pseudospectral methods for high-performance fluid dynamics analysis.

Can I use MPI parallelization for high-performance CFD simulations in Python?

Yes, MPI parallelization is supported for high-performance CFD simulations in Python. The framework enables distributed execution of 2D/3D Navier-Stokes and stratified geophysical flows, allowing scalable computation on HPC infrastructure.

What's the best way to automate parameter sweeps for shallow-water flow models?

Automating parameter sweeps for shallow-water flow models is handled through configurable solver selection and strict parameter handling. The framework raises AttributeError on typos, ensuring parameter configurations are validated before simulation execution.

Does this CFD framework support post-processing and interactive visualization of simulation data?

Yes, the CFD framework supports post-processing and interactive visualization of simulation data. It provides an end-to-end workflow from parameter configuration to rich output analysis, enabling you to derive insights directly from the simulation results.

How do I configure 2D and 3D stratified geophysical flows in a Python CFD environment?

Configuring 2D and 3D stratified geophysical flows in a Python CFD environment involves selecting the appropriate solver and defining parameters in YAML frontmatter. The framework supports multiple solvers for these specific geophysical flow types.

What happens if I make a typo in the configuration parameters for a fluid dynamics simulation?

If you make a typo in the configuration parameters for a fluid dynamics simulation, the framework enforces strict parameter handling and raises an AttributeError. This prevents silent errors and ensures only valid parameters are processed.