fluidsim
Run CFD simulations with Python-based FluidSim
Also available from: davila7
FluidSim brings high-performance computational fluid dynamics to Python. Run Navier-Stokes simulations, analyze turbulence, and visualize results with simple Python commands. No complex Fortran or C++ setup required.
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Using "fluidsim". Run a 2D turbulence simulation and show me the energy spectrum
Expected outcome:
- Created 2D Navier-Stokes simulation with 256x256 grid
- Running for 10 time units with viscosity 1e-3
- Generated energy spectrum showing -5/3 slope in inertial range
- Saved vorticity field visualization at t=10.0
- Simulation completed successfully - energy decay rate: 0.95
Using "fluidsim". Configure a stratified flow simulation for internal gravity waves
Expected outcome:
- Initialized ns2d.strat solver with Brunt-VΓ€isΓ€lΓ€ frequency N=2.0
- Set up 256x256 grid with domain size 2pi x 2pi
- Created dense layer initial condition with Gaussian profile
- Running for 20 time units with adaptive CFL time stepping
- Configured output periods for buoyancy and velocity fields
Security Audit
SafeAll 330 static findings are false positives. The scanner incorrectly flagged markdown documentation code blocks as shell commands. The skill is a legitimate scientific computing framework for computational fluid dynamics with no security risks. All detected patterns are documentation examples showing Python code for simulations.
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What You Can Build
Study 2D turbulence energy cascades
Simulate forced 2D turbulence to observe inverse energy cascade and forward enstrophy cascade phenomena
Model stratified atmospheric flows
Simulate density-stratified flows to study internal gravity waves and atmospheric dynamics
Analyze geophysical vortex dynamics
Use shallow water equations to model ocean eddies and rotating basin dynamics
Try These Prompts
Create a 2D Navier-Stokes simulation with 256x256 grid, run for 10 time units with noise initialization and save vorticity plots
Set up a stratified 2D simulation with Brunt-VΓ€isΓ€lΓ€ frequency N=2.0, configure for 20 time units, and initialize with a dense layer
Configure a 512x512x512 3D Navier-Stokes simulation with MPI support, set viscosity to 1e-5, and enable spectra output
Initialize Taylor-Green vortex in 2D, run simulation, and compare energy decay with analytical solution
Best Practices
- Use powers of 2 for grid resolution (128, 256, 512) for optimal FFT performance
- Enable CFL condition with CFL=0.5 for stable adaptive time stepping
- Save physical fields sparingly to manage disk space, use spatial means for time series
- Test with lower resolution first before scaling to production runs
Avoid
- Do not use arbitrary grid sizes - stick to powers of 2 for FFT efficiency
- Avoid setting fixed time steps without CFL checking for turbulent flows
- Do not save every time step - use appropriate output periods to manage data volume
Frequently Asked Questions
Why are my simulations unstable?
How do I choose the right solver?
What is the maximum resolution I can run?
How do I restart a simulation?
Can I run this on my laptop?
Why use pseudospectral methods?
Developer Details
Author
K-Dense-AILicense
CeCILL FREE SOFTWARE LICENSE AGREEMENT
Repository
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/fluidsimRef
main
File structure
π references/
π advanced_features.md
π installation.md
π output_analysis.md
π parameters.md
π solvers.md
π SKILL.md