
FluidSim
FreeEfficiently manage computational fluid dynamics simulations.
Free · Opens the source repo
What FluidSim does
FluidSim provides a structured framework for conducting computational fluid dynamics (CFD) simulations, particularly for periodic Cartesian pseudospectral methods. This skill is designed for researchers and engineers who require precise control over simulation parameters, solver selection, and output analysis. With FluidSim, users can define state equations, boundary conditions, and initial conditions, ensuring that all aspects of the simulation are meticulously planned and executed.
The workflow begins with the formulation of the problem, including the selection of a verified solver and the creation of a detailed JSON plan that outlines computational resource requirements. FluidSim emphasizes the importance of validation and diagnostics, offering tools to generate dry-run scripts and pilot simulations to inspect budgets and convergence behavior. Users can refine their grid and time step independently, ensuring that the simulation meets conservation and budget criteria before preparing for full-scale MPI jobs.
FluidSim also includes features for output analysis and restart compatibility, allowing for efficient handling of simulation results. The skill supports various solvers, including ns2d and ns3d, and provides a robust API for importing and manipulating simulation parameters. This makes FluidSim suitable for both novice and experienced users who need a reliable tool for CFD simulations, ensuring that they can achieve accurate and reliable results in their research or engineering projects.
When to use it
Use FluidSim when you need to conduct CFD simulations with precise control over parameters and solvers, especially in a high-performance computing (HPC) environment.
When not to use it
FluidSim may not be suitable for simple fluid dynamics problems or for users who do not require detailed parameter control and validation processes.
What you can build with it
Academic Research
Researchers can utilize FluidSim to conduct detailed CFD studies, ensuring that all simulation parameters are rigorously defined and validated.
Engineering Simulations
Engineers can apply FluidSim to model complex fluid dynamics scenarios, leveraging its capabilities for solver selection and output diagnostics.
High-Performance Computing
FluidSim is ideal for users working in HPC environments, providing tools for resource estimation and MPI job preparation.
How to install FluidSim
View source1. Install with the skills CLI
npx skills add k-dense-ai/scientific-agent-skills/fluidsim --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by k-dense-aiFluidSim
Use FluidSim 0.9.0 as a framework for Python-defined numerical solvers, especially periodic Cartesian pseudospectral CFD. Upstream FluidSim is CeCILL-2.1; the MIT frontmatter license applies only to this skill.
This skill does not treat a completed run, a stable time step, a smooth plot, or a closed program exit as evidence of numerical convergence or physical validity.
Required workflow
- State equations, units or nondimensionalization, geometry, boundaries, initial conditions, forcing, observables, and acceptance criteria.
- Select a verified solver and inspect its generated default parameters.
- Create a strict JSON plan with explicit CPU, RAM, disk, wall-time, output-file, timestep, CFL, resolution, and dealiasing bounds.
- Run the bundled validator and resource estimator.
- Generate and review a dry-run script. It does nothing unless executed with an explicit config-ID acknowledgement.
- Run one tiny serial pilot. Inspect budgets, divergence/constraints, spectral tails, CFL/time-step history, and output growth.
- Refine grid and time step independently. Check conservation/budget residuals and observable sensitivity.
- Only then prepare a site-specific MPI job. Never submit or launch MPI automatically.
- Preserve config, script,
uv.lock, package/platform/backend versions, logs, output inventory, checksums, and restart lineage.
Stop if physical assumptions, units, boundary conditions, forcing semantics, resolution criteria, resource limits, or acceptance criteria are missing.
Version and installation
As verified on 2026-07-23:
- Latest stable PyPI release:
fluidsim==0.9.0(2025-12-04). - Package metadata requires Python
>=3.11and lists Python 3.11–3.14. - Pseudospectral parameter creation needs FluidFFT; bare
fluidsimimported in the smoke test, butns2d.create_default_params()failed until thefftextra was installed. - Current companion versions tested here:
fluidfft==0.4.5andpyFFTW==0.15.1.
Prefer a project lock:
uv init --python 3.11
uv add "fluidsim[fft]==0.9.0" "fluidfft==0.4.5" "pyFFTW==0.15.1"
uv lock
uv sync --frozen
For an isolated disposable environment:
uv venv --python 3.11
uv pip install "fluidsim[fft]==0.9.0" "fluidfft==0.4.5" "pyFFTW==0.15.1"
The project lock is the reproducibility record; direct pins alone do not freeze all transitive artifacts. Do not reuse a lock across incompatible platforms or MPI ABIs.
MPI is optional and native:
uv add "mpi4py==4.1.2" "fluidfft-mpi-with-fftw==0.0.1" "fluidfft-fftwmpi==0.0.1"
uv lock
Those packages still require a compatible MPI runtime and FFTW development libraries. The optional native plugins are:
fluidfft-fftw==0.0.1: sequentialfft2d.with_fftw1d,fft2d.with_fftw2d,fft3d.with_fftw3d.fluidfft-mpi-with-fftw==0.0.1: MPIfft2d.mpi_with_fftw1d,fft3d.mpi_with_fftw1d.fluidfft-fftwmpi==0.0.1: MPI-enabled FFTWfft2d.mpi_with_fftwmpi2d,fft3d.mpi_with_fftwmpi3d.fluidfft-p3dfft==0.0.1:fft3d.mpi_with_p3dfft; requires P3DFFT.- FluidFFT also declares PFFT and P3DFFT extras; audit and pin their native stacks for the target cluster.
FluidFFT documents cuFFT historically, but FluidFFT 0.4.5 declares no CUDA extra or installed GPU plugin in its package metadata, and its CUDA installation page is unfinished. Do not claim GPU acceleration or install an unrelated CUDA wheel as a FluidSim backend. Treat GPU work as source-level experimental integration requiring separate validation.
See installation for system dependencies, MPI ABI, HDF5-MPI, backend discovery, and verification.
API snapshot
Use direct, versioned imports:
from fluidsim.solvers.ns2d.solver import Simul
params = Simul.create_default_params()
params.oper.nx = params.oper.ny = 32
params.oper.Lx = params.oper.Ly = 2 * 3.141592653589793
params.oper.coef_dealiasing = 2 / 3
params.time_stepping.USE_CFL = True
params.time_stepping.cfl_coef = 0.5
params.time_stepping.deltat0 = 0.001
params.time_stepping.deltat_max = 0.01
params.time_stepping.t_end = 0.1
params.time_stepping.max_elapsed = "00:05:00"
params.init_fields.type = "noise"
params.init_fields.noise.velo_max = 0.01
params.output.HAS_TO_SAVE = False
params.output.ONLINE_PLOT_OK = False
Important 0.9 corrections:
- CFL field:
params.time_stepping.cfl_coef, notCFL. - Time-correlated forcing:
params.forcing.tcrandom.time_correlation, not a flattcrandom_time_correlation. - NS2D default initial types include
constant,noise,jet,dipole,from_file,from_simul, andin_script; do not invent a universal list for every solver. - Output state files default to
state_phys_t*.nc; spectra usespectra1D.h5/spectra2D.h5; scalar means are solver-dependentspatial_means.txtor JSON-lines. params.output.sub_directoryis relative underFLUIDSIM_PATH.
ParamContainer rejects undeclared attributes. Always generate defaults from the
selected Simul class and inspect them before changing values. See
parameters.
Solvers
Primary Cartesian CFD keys and imports:
from fluidsim.solvers.ns2d.solver import Simul # ns2d
from fluidsim.solvers.ns2d.bouss.solver import Simul # ns2d.bouss
from fluidsim.solvers.ns2d.strat.solver import Simul # ns2d.strat
from fluidsim.solvers.ns3d.solver import Simul # ns3d
from fluidsim.solvers.ns3d.bouss.solver import Simul # ns3d.bouss
from fluidsim.solvers.ns3d.strat.solver import Simul # ns3d.strat
The 0.9 registry also includes plate2d, sw1l variants, waves2d, 1D models,
0D models, spherical solvers, and framework adapters. Availability in the
registry does not make a solver appropriate for a scientific question. Verify
equations, variables, geometry, boundaries, and diagnostics in the solver
source. See solvers.
Forcing and time advancement
Forcing is solver-specific. A current normalized random example is:
params.forcing.enable = True
params.forcing.type = "tcrandom"
params.forcing.forcing_rate = 1.0
params.forcing.nkmin_forcing = 4
params.forcing.nkmax_forcing = 5
params.forcing.tcrandom.time_correlation = "based_on_forcing_rate"
Record the forced variable, normalization definition, wave-number band, random seed/state, injection target, and measured injection. FluidSim 0.9 saves state parameters for restart; 0.8.6 fixed time-correlated forcing restart behavior.
Available pseudospectral schemes include Euler/RK2 phase-shift variants,
RK2_trapezoid, and RK4. A named order does not establish accuracy. Check CFL,
fast-wave/diffusive limits, deltat_max, and time-step refinement. See
advanced features.
Outputs, loading, and restart
For read-only analysis:
from fluidsim import load_sim_for_plot
sim = load_sim_for_plot("run-directory", hide_stdout=True)
sim.output.spatial_means.plot()
sim.output.spectra.plot1d()
sim.output.phys_fields.plot(time=1.0)
load_sim_for_plot uses a coarse operator and disables saving/online plotting.
For a state-bearing object:
from fluidsim import load_state_phys_file
sim = load_state_phys_file("run-directory", t_approx="last")
For a controlled restart, prefer load_for_restart or first run
fluidsim-restart --only-check. Do not use --modify-params with untrusted text:
the upstream CLI executes Python code supplied to that option. This skill's
generator never emits it. Verify solver, grid/domain, state variables, versions,
forcing state, checksum, target time, output destination, and resource bounds.
Resolution changes require the dedicated reviewed workflow, not a silent grid
edit. See simulation workflow and
output analysis.
Scientific acceptance gate
Before interpreting results, require:
- Explicit dimensional units or a complete nondimensionalization map.
- Correct equations, periodic geometry/boundaries, initial state, forcing, and diagnostic definitions.
- Resolution and dealiasing evidence: spectra/tails, resolved gradients, and solver-appropriate small-scale criteria.
- Timestep evidence: CFL history, fastest-wave and dissipative limits, and smaller-step comparison.
- Conservation and budget checks including forcing, dissipation, transfers, and residuals.
- Grid/time refinement with uncertainty or sensitivity for reported observables.
- Comparison to an analytical solution, manufactured solution, benchmark, or independently reproduced result where appropriate.
- Complete provenance and restart lineage.
Never label a run “DNS,” “converged,” “validated,” “steady,” or “physically correct” from parameter values or plots alone.
Bundled local tools
All tools emit strict JSON, reject URLs/traversal/symlinks, enforce hard bounds, use no network or subprocess, and never launch a simulation:
python3 scripts/solver_config_validator.py --example
python3 scripts/solver_config_validator.py --config config.json
python3 scripts/grid_resource_estimator.py --config config.json
python3 scripts/simulation_dry_run.py --config config.json --output run.py
python3 scripts/output_inventory.py --path run-directory
python3 scripts/budget_summary.py --path run-directory
python3 scripts/restart_compatibility.py --source state.nc --target-config config.json
The HDF5 tools lazily require h5py, inspect bounded metadata/hyperslabs, and
never follow external links or load full field arrays.
References
- Installation and FFT/MPI backends
- Solver registry and selection
- Simulation, pilot, and restart workflow
- Verified parameter surface
- Output, plotting, and budget analysis
- Forcing, operators, MPI, and migrations
Dated upstream basis
Verified 2026-07-23 against PyPI 0.9.0, FluidSim 0.9 docs, release notes, official source mirror, FluidFFT 0.4.5 docs, and the primary FluidSim (DOI 10.5334/jors.239) and FluidFFT (DOI 10.5334/jors.238) papers. API claims use official docs/source; method/performance claims in the references are scoped to the cited primary papers and their benchmark setups.
Frequently asked questions about FluidSim
Similar skills
Spring Boot Testing
Master testing techniques for Spring Boot 4 applications.
GitHub Issues
Manage GitHub issues efficiently with MCP tools.
Geofeed Tuner
Optimize your IP geolocation feeds in CSV format.
Batch Files
Master Windows batch scripting for automation and task management.
Adobe Illustrator Scripting
Automate your Illustrator workflows with ExtendScript.
Plugin Structure
Create and organize Claude Code plugins effectively.
