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.
$ Installer
git clone https://github.com/davila7/claude-code-templates /tmp/claude-code-templates && cp -r /tmp/claude-code-templates/cli-tool/components/skills/scientific/fluidsim ~/.claude/skills/claude-code-templates// tip: Run this command in your terminal to install the skill
name: fluidsim description: 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.
FluidSim
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:
references/installation.md: Complete installation instructionsreferences/solvers.md: Available solvers and selection guidereferences/simulation_workflow.md: Detailed workflow examplesreferences/parameters.md: Comprehensive parameter documentationreferences/output_analysis.md: Output types and analysis methodsreferences/advanced_features.md: Forcing, MPI, parametric studies, custom solvers
Repository
