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Fluidsim

k-dense-ai/fluidsim

Plan, configure, inspect, restart, and analyze bounded FluidSim computational-fluid-dynamics simulations with explicit numerical-validity and HPC safety checks. Use for FluidSim solver selection, parameter review, FFT/MPI setup, output diagnostics, or restart compatibility.

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Install

one command, takes just this skill from the repository
npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill fluidsim

The instruction itself

11 sections, as written by the author

FluidSim

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 >=3.11 and lists Python 3.11–3.14.
  • Pseudospectral parameter creation needs FluidFFT; bare fluidsim imported in

the smoke test, but ns2d.create_default_params() failed until the fft extra

was installed.

  • Current companion versions tested here: fluidfft==0.4.5 and

pyFFTW==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: sequential

fft2d.with_fftw1d, fft2d.with_fftw2d, fft3d.with_fftw3d.

  • fluidfft-mpi-with-fftw==0.0.1: MPI

fft2d.mpi_with_fftw1d, fft3d.mpi_with_fftw1d.

  • fluidfft-fftwmpi==0.0.1: MPI-enabled FFTW

fft2d.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, not CFL.
  • Time-correlated forcing:

params.forcing.tcrandom.time_correlation, not a flat

tcrandom_time_correlation.

  • NS2D default initial types include constant, noise, jet, dipole,

from_file, from_simul, and in_script; do not invent a universal list for

every solver.

  • Output state files default to state_phys_t*.nc; spectra use

spectra1D.h5/spectra2D.h5; scalar means are solver-dependent

spatial_means.txt or JSON-lines.

  • params.output.sub_directory is relative under FLUIDSIM_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.

How to use it

Copy the folder

Take k-dense-ai/fluidsim from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference pip, uv. Without those the skill loads but fails at the first command.