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 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