K-Dense-AI/scientific-agent-skills

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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See how to use itView GitHub source
npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill "skills/fluidsim"

Quick start

Start using it in three steps

Install it or open the source, trigger it with a clear task, then follow the source workflow.

1

Install the Skill

npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill "skills/fluidsim"
2

Describe the task

Use fluidsim to help me with: [describe your task]. Before you begin, tell me what input you need, the steps you will follow, and the expected output.

3

Follow the workflow

5 key workflow steps, examples, and cautions are distilled below.

Continue to the workflow

Direct answers

Answers to review before you install

What is 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.

Who should use fluidsim?

It is relevant to workflows involving Engineering, Operations, Research, Python.

How do you install fluidsim?

SkillSignal detected this source-specific command: npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill "skills/fluidsim". Inspect the repository and command before running it.

Which Agent platforms does it support?

The upstream source does not declare a dedicated Agent platform.

What permissions or risks should you review?

Static analysis detected exec-script signals. Review the cited source lines before installing; these signals are not a security audit.

What are the current evidence limits?

This page combines upstream documentation with deterministic repository, quality, and static-risk signals. It is not described as a manual test or security review.

SkillSignal brief

Decide whether it fits your work first

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.

Useful in these contexts

Not yet included in a workflow collection

Core capabilities

EngineeringOperationsResearchPython

Distilled from the source

Understand this Skill in one minute

About 5 min · 11 sections

Core workflow

  1. 1

    State equations, units or nondimensionalization, geometry, boundaries,

  2. 2

    Select a verified solver and inspect its generated default parameters.

  3. 3

    Create a strict JSON plan with explicit CPU, RAM, disk, wall-time, output-file,

  4. 4

    Run the bundled validator and resource estimator.

  5. 5

    Generate and review a dry-run script. It does nothing unless executed with an

Repository stars
31,966
Repository forks
3,175
Quality
93/100
Source repository last pushed

Quality breakdown

Based on traceable docs and repository signals; stars are not treated as quality.

93/100
Documentation30/30
Specificity20/25
Maintenance20/20
Trust signals23/25

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View original Skill.mdThis page is parsed directly from the repository SKILL.md without editorial rewriting. Collected: Jul 28, 2026 · about 5 min

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

  1. State equations, units or nondimensionalization, geometry, boundaries, initial conditions, forcing, observables, and acceptance criteria.
  2. Select a verified solver and inspect its generated default parameters.
  3. Create a strict JSON plan with explicit CPU, RAM, disk, wall-time, output-file, timestep, CFL, resolution, and dealiasing bounds.
  4. Run the bundled validator and resource estimator.
  5. Generate and review a dry-run script. It does nothing unless executed with an explicit config-ID acknowledgement.
  6. Run one tiny serial pilot. Inspect budgets, divergence/constraints, spectral tails, CFL/time-step history, and output growth.
  7. Refine grid and time step independently. Check conservation/budget residuals and observable sensitivity.
  8. Only then prepare a site-specific MPI job. Never submit or launch MPI automatically.
  9. 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

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.

Skill path
skills/fluidsim/SKILL.md
Commit SHA
e7ac42510774
Repository license
MIT
Data collected