Vibe-Skills fluidsim
Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.
git clone https://github.com/foryourhealth111-pixel/Vibe-Skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/foryourhealth111-pixel/Vibe-Skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/bundled/skills/fluidsim" ~/.claude/skills/foryourhealth111-pixel-vibe-skills-fluidsim && rm -rf "$T"
bundled/skills/fluidsim/SKILL.mdFluidSim
Overview
FluidSim is an object-oriented Python framework for high-performance computational fluid dynamics (CFD) simulations. It provides solvers for periodic-domain equations using pseudospectral methods with FFT, delivering performance comparable to Fortran/C++ while maintaining Python's ease of use.
Key strengths:
- Multiple solvers: 2D/3D Navier-Stokes, shallow water, stratified flows
- High performance: Pythran/Transonic compilation, MPI parallelization
- Complete workflow: Parameter configuration, simulation execution, output analysis
- Interactive analysis: Python-based post-processing and visualization
Core Capabilities
1. Installation and Setup
Install fluidsim using uv with appropriate feature flags:
# Basic installation uv uv pip install fluidsim # With FFT support (required for most solvers) uv uv pip install "fluidsim[fft]" # With MPI for parallel computing uv uv pip install "fluidsim[fft,mpi]"
Set environment variables for output directories (optional):
export FLUIDSIM_PATH=/path/to/simulation/outputs export FLUIDDYN_PATH_SCRATCH=/path/to/working/directory
No API keys or authentication required.
See
references/installation.md for complete installation instructions and environment configuration.
2. Running Simulations
Standard workflow consists of five steps:
Step 1: Import solver
from fluidsim.solvers.ns2d.solver import Simul
Step 2: Create and configure parameters
params = Simul.create_default_params() params.oper.nx = params.oper.ny = 256 params.oper.Lx = params.oper.Ly = 2 * 3.14159 params.nu_2 = 1e-3 params.time_stepping.t_end = 10.0 params.init_fields.type = "noise"
Step 3: Instantiate simulation
sim = Simul(params)
Step 4: Execute
sim.time_stepping.start()
Step 5: Analyze results
sim.output.phys_fields.plot("vorticity") sim.output.spatial_means.plot()
See
references/simulation_workflow.md for complete examples, restarting simulations, and cluster deployment.
3. Available Solvers
Choose solver based on physical problem:
2D Navier-Stokes (
ns2d): 2D turbulence, vortex dynamics
from fluidsim.solvers.ns2d.solver import Simul
3D Navier-Stokes (
ns3d): 3D turbulence, realistic flows
from fluidsim.solvers.ns3d.solver import Simul
Stratified flows (
ns2d.strat, ns3d.strat): Oceanic/atmospheric flows
from fluidsim.solvers.ns2d.strat.solver import Simul params.N = 1.0 # Brunt-Väisälä frequency
Shallow water (
sw1l): Geophysical flows, rotating systems
from fluidsim.solvers.sw1l.solver import Simul params.f = 1.0 # Coriolis parameter
See
references/solvers.md for complete solver list and selection guidance.
4. Parameter Configuration
Parameters are organized hierarchically and accessed via dot notation:
Domain and resolution:
params.oper.nx = 256 # grid points params.oper.Lx = 2 * pi # domain size
Physical parameters:
params.nu_2 = 1e-3 # viscosity params.nu_4 = 0 # hyperviscosity (optional)
Time stepping:
params.time_stepping.t_end = 10.0 params.time_stepping.USE_CFL = True # adaptive time step params.time_stepping.CFL = 0.5
Initial conditions:
params.init_fields.type = "noise" # or "dipole", "vortex", "from_file", "in_script"
Output settings:
params.output.periods_save.phys_fields = 1.0 # save every 1.0 time units params.output.periods_save.spectra = 0.5 params.output.periods_save.spatial_means = 0.1
The Parameters object raises
AttributeError for typos, preventing silent configuration errors.
See
references/parameters.md for comprehensive parameter documentation.
5. Output and Analysis
FluidSim produces multiple output types automatically saved during simulation:
Physical fields: Velocity, vorticity in HDF5 format
sim.output.phys_fields.plot("vorticity") sim.output.phys_fields.plot("vx")
Spatial means: Time series of volume-averaged quantities
sim.output.spatial_means.plot()
Spectra: Energy and enstrophy spectra
sim.output.spectra.plot1d() sim.output.spectra.plot2d()
Load previous simulations:
from fluidsim import load_sim_for_plot sim = load_sim_for_plot("simulation_dir") sim.output.phys_fields.plot()
Advanced visualization: Open
.h5 files in ParaView or VisIt for 3D visualization.
See
references/output_analysis.md for detailed analysis workflows, parametric study analysis, and data export.
6. Advanced Features
Custom forcing: Maintain turbulence or drive specific dynamics
params.forcing.enable = True params.forcing.type = "tcrandom" # time-correlated random forcing params.forcing.forcing_rate = 1.0
Custom initial conditions: Define fields in script
params.init_fields.type = "in_script" sim = Simul(params) X, Y = sim.oper.get_XY_loc() vx = sim.state.state_phys.get_var("vx") vx[:] = sin(X) * cos(Y) sim.time_stepping.start()
MPI parallelization: Run on multiple processors
mpirun -np 8 python simulation_script.py
Parametric studies: Run multiple simulations with different parameters
for nu in [1e-3, 5e-4, 1e-4]: params = Simul.create_default_params() params.nu_2 = nu params.output.sub_directory = f"nu{nu}" sim = Simul(params) sim.time_stepping.start()
See
references/advanced_features.md for forcing types, custom solvers, cluster submission, and performance optimization.
Common Use Cases
2D Turbulence Study
from fluidsim.solvers.ns2d.solver import Simul from math import pi params = Simul.create_default_params() params.oper.nx = params.oper.ny = 512 params.oper.Lx = params.oper.Ly = 2 * pi params.nu_2 = 1e-4 params.time_stepping.t_end = 50.0 params.time_stepping.USE_CFL = True params.init_fields.type = "noise" params.output.periods_save.phys_fields = 5.0 params.output.periods_save.spectra = 1.0 sim = Simul(params) sim.time_stepping.start() # Analyze energy cascade sim.output.spectra.plot1d(tmin=30.0, tmax=50.0)
Stratified Flow Simulation
from fluidsim.solvers.ns2d.strat.solver import Simul params = Simul.create_default_params() params.oper.nx = params.oper.ny = 256 params.N = 2.0 # stratification strength params.nu_2 = 5e-4 params.time_stepping.t_end = 20.0 # Initialize with dense layer params.init_fields.type = "in_script" sim = Simul(params) X, Y = sim.oper.get_XY_loc() b = sim.state.state_phys.get_var("b") b[:] = exp(-((X - 3.14)**2 + (Y - 3.14)**2) / 0.5) sim.state.statephys_from_statespect() sim.time_stepping.start() sim.output.phys_fields.plot("b")
High-Resolution 3D Simulation with MPI
from fluidsim.solvers.ns3d.solver import Simul params = Simul.create_default_params() params.oper.nx = params.oper.ny = params.oper.nz = 512 params.nu_2 = 1e-5 params.time_stepping.t_end = 10.0 params.init_fields.type = "noise" sim = Simul(params) sim.time_stepping.start()
Run with:
mpirun -np 64 python script.py
Taylor-Green Vortex Validation
from fluidsim.solvers.ns2d.solver import Simul import numpy as np from math import pi params = Simul.create_default_params() params.oper.nx = params.oper.ny = 128 params.oper.Lx = params.oper.Ly = 2 * pi params.nu_2 = 1e-3 params.time_stepping.t_end = 10.0 params.init_fields.type = "in_script" sim = Simul(params) X, Y = sim.oper.get_XY_loc() vx = sim.state.state_phys.get_var("vx") vy = sim.state.state_phys.get_var("vy") vx[:] = np.sin(X) * np.cos(Y) vy[:] = -np.cos(X) * np.sin(Y) sim.state.statephys_from_statespect() sim.time_stepping.start() # Validate energy decay df = sim.output.spatial_means.load() # Compare with analytical solution
Quick Reference
Import solver:
from fluidsim.solvers.ns2d.solver import Simul
Create parameters:
params = Simul.create_default_params()
Set resolution:
params.oper.nx = params.oper.ny = 256
Set viscosity:
params.nu_2 = 1e-3
Set end time:
params.time_stepping.t_end = 10.0
Run simulation:
sim = Simul(params); sim.time_stepping.start()
Plot results:
sim.output.phys_fields.plot("vorticity")
Load simulation:
sim = load_sim_for_plot("path/to/sim")
Resources
Documentation: https://fluidsim.readthedocs.io/
Reference files:
: Complete installation instructionsreferences/installation.md
: Available solvers and selection guidereferences/solvers.md
: Detailed workflow examplesreferences/simulation_workflow.md
: Comprehensive parameter documentationreferences/parameters.md
: Output types and analysis methodsreferences/output_analysis.md
: Forcing, MPI, parametric studies, custom solversreferences/advanced_features.md