mfem
dolfinx
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mfem | dolfinx | |
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7 | 18 | |
1,537 | 656 | |
3.6% | 5.9% | |
9.9 | 9.6 | |
8 days ago | 1 day ago | |
C++ | C++ | |
BSD 3-clause "New" or "Revised" License | GNU Lesser General Public License v3.0 only |
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mfem
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rodin alternatives - mfem and FreeFem-sources
7 projects | 8 Mar 2023
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Generate MFEM initial mesh file using WELSIM
MFEM (mfem.org) is one of the most active open-source partial differential equation (PDE) solver projects in recent years. Although this open source package is positioned as a lightweight and scalable C++ library, it provides higher-order finite element spaces, supports mixed elements, discontinuous Galerkin elements, isogeometric analysis methods, and more. In particular, it has great advantages in high-performance computing, not only supports message passing interface (MPI) parallelism and shared memory parallelism (OpenMP), but also has good strength in GPU parallel computing. The built-in post-processing program GLVis can easily read and display the result files. The BSD-3 license is also extremely friendly to developers. Recently, MFEM supports Python programming, which makes the library more convenient for various types of researchers.
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Open source / part time research in the world of HPC?
If you are looking for something more numerically intensive, check out MFEM: https://mfem.org. Lots of examples in the gallery there; lots of cool higher order curved meshes and physics problems to play with. Probably a higher learning curve than some of your other options.
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How is it working at Idaho National Lab?
If you're interested in a FEM framework designed by computer scientists and mathematicians, MFEM has treated me well. Maybe just something to compare to.
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Intact Solutions is hiring a Software Engineer
We currently have several solvers of our own, as well as interfacing with MPI capable solvers via mfem. We are currently a pre and post processor for several NASTRAN based solvers using our meshing free method.
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What are some best open source FEA solvers that one can test their new element implementation in?
MFEM
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Does anyone have open source C++ projects that I can try contributing to?
I’m working on MFEM. It is a Finite Element Method (FEM) library. Some of the work would require knowledge of the FEM but there’s a lot of stuff like implementing operators in vector classes that you could do too!
dolfinx
- What's your main programming language?
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rodin alternatives - mfem and FreeFem-sources
7 projects | 8 Mar 2023
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Learn PDE constrained optimization
One thing that is a pain when learning this stuff is that actually performing the optimization requires a good understanding of the numerical discretization of PDEs. Finite elements are a natural choice because it is very easy to characterize the adjoint with this formulation. There are some good free tools that you can use to actually learn and do some computations yourself. The first is hIPPYlib (paper, code), which is built on top of FEniCS (link), for which there are many good tutorials. Beware trying to install this on Windows though. You will need to work in Docker or in Ubuntu via Windows Linux Subsystem.
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Open source FEA tools instead of ANSYS Workbench and APDL
If you're ok with coding, fenics is a solid place to start. Also if you're comfortable with coding, openfoam is FVM, rather than FEM, but it can handle solidmechanics.
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Eighty Years of the Finite Element Method: Birth, Evolution, and Future
> FEniCs made FEM so easy
https://fenicsproject.org/
Indeed, was blown away when I saw it for the first time over a decade ago, compared to the convoluted C++ FEM libraries I had seen before that.
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Best Python package(s) to solve PDEs numerically?
Have you looked at FEniCS? Pretty much everything else I'm aware of is probably overkill (e.g., MOOSE in C++, HYPRE's Python bindings, etc.)
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Open-source FEA software
FEniCSx is quite good.
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The Julia language has a number of correctness flaws
You mean Python? For many research tasks it's fine. High level libraries let you define your computation in a minimal amount of code. FEniCS is a great example of this - underneath it compiles the abstracted high level stuff to calls to low-level libraries that do the heavy lifting. For many applications you can just write vectorized code with Numpy that performs well, or use Numba to JIT what you can't vectorize. For some tasks, however, you need interfaces that don't exist in the high level libraries, and that was the case for me.
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What's a good book to learn to numerically solve ODEs and PDEs in python?
I just came across FEniCSX. I’m not sure if it’s what you want but here’s the description:
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Okay, let's end this Tabs vs Space debate once and for all
Fenics: Very popular finite element framework “UseTab: Never” https://github.com/FEniCS/dolfinx/blob/main/.clang-format
What are some alternatives?
moose - Multiphysics Object Oriented Simulation Environment
Gridap.jl - Grid-based approximation of partial differential equations in Julia
sparselizard - C++ FEM library | user-friendly | multi-physics | hp-adaptive | HPC
taichi - Productive, portable, and performant GPU programming in Python.
elmerfem - Official git repository of Elmer FEM software
ModelingToolkit.jl - An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
nekRS - our next generation fast and scalable CFD code
pykokkos - Performance portable parallel programming in Python.
FEM - ⚡🧠A finite element Python implementation
libmesh - libMesh github repository
slurm - Slurm: A Highly Scalable Workload Manager
FreeFem-sources - FreeFEM source code