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fluidsim

Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.

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name fluidsim description Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis. license CeCILL FREE SOFTWARE LICENSE AGREEMENT metadata {"skill-author":"K-Dense Inc."} FluidSim Routing Boundary Use this skill only for FluidSim or explicit CFD workflows such as Navier-Stokes, turbulence, shallow-water, stratified-flow, or pseudospectral fluid simulations. Do not use it for CSS fluid layouts, responsive design, generic Python simulation, generic PDE solving, or non-FluidSim numerical physics work. 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
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