What solvers are included in FluidSim?

FluidSim includes specialized solvers for 2D and 3D Navier-Stokes equations, shallow water equations (sw1l), and stratified flows (ns2d.strat/ns3d.strat).

How do I visualize the simulation results?

FluidSim provides built-in Python methods to plot physical fields, spectra, and spatial means. Results are saved in HDF5 format, which can also be opened in external tools like ParaView.

Can I define custom initial conditions?

Absolutely. FluidSim allows you to define initial fields 'in-script', giving you full control over the mathematical initialization of your fluid state.

Does using Python make the simulations slow?

No, FluidSim uses compilation tools like Pythran and Transonic along with optimized FFT libraries to achieve execution speeds comparable to low-level languages like Fortran and C++.

Can I run FluidSim simulations on a cluster?

Yes, FluidSim is designed for high-performance computing and supports MPI parallelization, allowing it to scale across multiple processors and nodes.

FluidSim CFD Simulator

Name: FluidSim CFD Simulator
Author: Activer007

byActiver007

데이터 과학 및 ML

Simulates high-performance computational fluid dynamics using Python-based pseudospectral methods and MPI support.

소개

FluidSim is a comprehensive object-oriented framework designed for high-performance computational fluid dynamics (CFD) simulations. It enables researchers and engineers to run complex simulations—including 2D/3D Navier-Stokes, shallow water, and stratified flows—directly from Python with performance levels comparable to Fortran or C++. By leveraging pseudospectral methods, FFT, and MPI parallelization, FluidSim handles everything from initial parameter configuration and execution to advanced post-processing and interactive visualization, making it an essential tool for studying turbulence, vortex dynamics, and geophysical flows.

주요 기능

Robust hierarchical parameter management with built-in error checking
Interactive Python-based post-processing and data visualization tools
High-performance computing via MPI parallelization and Pythran/Transonic compilation
Pseudospectral methods using Fast Fourier Transforms (FFT) for periodic domains
0 GitHub stars
Multi-solver support for 2D/3D Navier-Stokes, shallow water, and stratified flows

사용 사례

Modeling geophysical flows such as oceanic stratification and atmospheric systems
Conducting large-scale parametric studies on high-performance computing clusters
Analyzing energy cascades and vortex dynamics in 2D and 3D turbulence

소개

주요 기능

Robust hierarchical parameter management with built-in error checking
Interactive Python-based post-processing and data visualization tools
High-performance computing via MPI parallelization and Pythran/Transonic compilation
Pseudospectral methods using Fast Fourier Transforms (FFT) for periodic domains
0 GitHub stars
Multi-solver support for 2D/3D Navier-Stokes, shallow water, and stratified flows

사용 사례

Modeling geophysical flows such as oceanic stratification and atmospheric systems
Conducting large-scale parametric studies on high-performance computing clusters
Analyzing energy cascades and vortex dynamics in 2D and 3D turbulence