We have also been able to use supercomputers of CIMENT/GRICAD, CINES/GENCI (grant 2018-A0040107567) and the Swedish National Infrastructure for Computing (SNIC). The source code is hosted at Bitbucket as a Mercurial repository /fluiddyn/fluidsim and the documentation generated using Sphinx can be read online at .įunding statement: This project has indirectly benefited from funding from the foundation Simone et Cino Del Duca de l’Institut de France, the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No 647018-WATU and Euhit consortium) and the Swedish Research Council (Vetenskapsrådet): 2013-5191. Three similar pseudo-spectral CFD codes based on Python (Dedalus, SpectralDNS) and Fortran (NS3D) are presented and qualitatively and quantitatively compared to fluidsim. Simulations can be used to communicate complex processes and relationships in a safe and accessible way. Let’s run a small simulation with this script: from math import pi from import Simul params Simul.createdefaultparams() 'examplesrestart' nh 24 Lh 2 pi deltax Lh / nh params.nu8. We investigate the performance and scalability of fluidsim in a state of the art HPC cluster. However, this metapaper shall dwell only on the implementation and performance of its pseudo-spectral solvers, in particular the two- and three-dimensional Navier-Stokes solvers. Currently, fluidsim includes solvers for a variety of physical problems using different numerical methods (including finite-difference methods).
You can rate examples to help us improve the quality of examples. These are the top rated real world C++ (Cpp) examples of FluidSim::runSim extracted from open source projects. The implementation details including optimization methods, modular organization of features and object-oriented approach of using classes to implement solvers are also briefly explained. C++ (Cpp) FluidSim::runSim - 1 examples found. The present article describes the design aspects of fluidsim, which includes use of Python as the main language focus on the ease of use, reuse and maintenance of the code without compromising performance. Solvers in fluidsim are scalable, High-Performance Computing (HPC) codes which are powered under the hood by the rich, scientific Python ecosystem and the Application Programming Interfaces (API) provided by fluiddyn and fluidfft packages. Some examples illustrate the utilization of this approach and the gain that can be observed over standard simulation tools. It is developed as a part of FluidDyn project, an effort to promote open-source and open-science collaboration within fluid mechanics community and intended for both educational as well as research purposes. xmf file with the command line tool fluidsim-create-xml-description.
xmf files which describe how the physical fields are stored in the hdf5 / netcdf fluidsim files. The Python package fluidsim is introduced in this article as an extensible framework for Computational Fluid Mechanics (CFD) solvers. For serious 3D representations, it is easy to use specialized software like Paraview or Visit.