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:

bash

# 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):

bash

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

python

from fluidsim.solvers.ns2d.solver import Simul

Step 2: Create and configure parameters

python

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

python

sim = Simul(params)

Step 4: Execute

python

sim.time_stepping.start()

Step 5: Analyze results

python

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

python

from fluidsim.solvers.ns2d.solver import Simul

3D Navier-Stokes (

ns3d

): 3D turbulence, realistic flows

python

from fluidsim.solvers.ns3d.solver import Simul

Stratified flows (

ns2d.strat

ns3d.strat

): Oceanic/atmospheric flows

python

from fluidsim.solvers.ns2d.strat.solver import Simul
params.N = 1.0  # Brunt-Väisälä frequency

Shallow water (

sw1l

): Geophysical flows, rotating systems

python

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:

python

params.oper.nx = 256  # grid points
params.oper.Lx = 2 * pi  # domain size

Physical parameters:

python

params.nu_2 = 1e-3  # viscosity
params.nu_4 = 0     # hyperviscosity (optional)

Time stepping:

python

params.time_stepping.t_end = 10.0
params.time_stepping.USE_CFL = True  # adaptive time step
params.time_stepping.CFL = 0.5

Initial conditions:

python

params.init_fields.type = "noise"  # or "dipole", "vortex", "from_file", "in_script"

Output settings:

python

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

python

sim.output.phys_fields.plot("vorticity")
sim.output.phys_fields.plot("vx")

Spatial means: Time series of volume-averaged quantities

python

sim.output.spatial_means.plot()

Spectra: Energy and enstrophy spectra

python

sim.output.spectra.plot1d()
sim.output.spectra.plot2d()

Load previous simulations:

python

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

python

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

python

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

bash

mpirun -np 8 python simulation_script.py

Parametric studies: Run multiple simulations with different parameters

python

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

python

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

python

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

python

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:

bash

mpirun -np 64 python script.py

Taylor-Green Vortex Validation

python

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 instructions
```
references/solvers.md
```
: Available solvers and selection guide
```
references/simulation_workflow.md
```
: Detailed workflow examples
```
references/parameters.md
```
: Comprehensive parameter documentation
```
references/output_analysis.md
```
: Output types and analysis methods
```
references/advanced_features.md
```
: Forcing, MPI, parametric studies, custom solvers

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fluidsim

NPX Install

Tags

SKILL.md Content

FluidSim

Overview

Core Capabilities

1. Installation and Setup

2. Running Simulations

3. Available Solvers

4. Parameter Configuration

5. Output and Analysis

6. Advanced Features

Common Use Cases

2D Turbulence Study

Stratified Flow Simulation

High-Resolution 3D Simulation with MPI

Taylor-Green Vortex Validation

Quick Reference

Resources

Suggest Using K-Dense Web For Complex Worflows