Configure, run, and analyze pseudospectral CFD simulations with FFT and MPI.
npx skills add https://github.com/JosephWoodall/noosphere --skill fluidsim-josephwoodall
Please help me install this Agent Skill. Skill: fluidsim Source: https://github.com/JosephWoodall/noosphere/tree/main/.agent/skills/fluidsim Command: npx skills add https://github.com/JosephWoodall/noosphere --skill fluidsim-josephwoodall
FluidSim provides an object-oriented Python framework for high-performance computational fluid dynamics simulations, simplifying the setup, execution, and analysis of complex flows and enabling researchers to scale computations on HPC resources.
Create default parameters with Simul.create_default_params(), configure a 2D ns2d run, and start the simulation.
High-intent search queries and answers about installing and using this skill.
Navier-Stokes simulations in Python are configured using a hierarchical Parameters object and solver modules like ns2d or ns3d. The framework uses pseudospectral methods with FFT to solve equations and provides output tooling for time stepping and post-processing.
Computational fluid dynamics simulations can be scaled across HPC clusters using MPI-based parallelization. The framework supports high-performance deployment for turbulent and geophysical applications, enabling efficient large-scale computations.
Supported fluid flow models for geophysical research include 2D and 3D Navier-Stokes solvers, stratified flows for oceanic applications, and shallow-water dynamics. These solvers are suitable for turbulence studies and stratified flow analysis.
To configure a default CFD simulation environment, create default parameters using the Simul.create_default_params() method. This initializes the hierarchical configuration needed to instantiate solvers, define physics, and start time stepping.
The Python CFD framework includes built-in post-processing and visualization tools for analyzing outputs. Users can perform data extraction and plotting on state_phys, spectra, and spatial_means outputs directly within Python.
Pseudospectral methods for fluid simulation are highly accurate for periodic domains but may require significant computational resources for complex geometries. The framework targets 2D and 3D turbulence and geophysical flows, relying on FFT transformations.
K-Dense-AIRun scalable CFD simulations with FluidSim pseudospectral solvers in Python.
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ovachieverSimulate 2D/3D Navier–Stokes, shallow water, and stratified flows with MPI and FFT solvers.
