During the EGU2023 conference, when I presented a high-performance MPM (Material Point Method) solver, I was asked, "How do you discretize the computational model for the MPM?" I didn't have a clear answer (I didn't even consider it a problem) because the models were relatively simple and could be generated directly using some straightforward functions. However, as computational models gradually became more complex and diverse, I began to realize that this was indeed a very good question. The preprocessing for MPM should not be a computationally intensive task; it should be fast enough. Yet, I couldn't find a "plug-and-play" generalized code for this purpose. Some literatures have contributed to this issue, and I built upon their work to create a comprehensive and refined julia package.
No parallelization, no problem—5,334,808 particles from an STL file (998,137 triangles) in just 0.6 s.
Intel(R) Core(TM) i9-10900K CPU @ 3.70GHz
Just type ] in Julia's REPL:
julia> ]
(@1.11) Pkg> add MaterialPointGenerator- Structured (regular) coordinates
- Support complicated 2/3D models
- Particle generation from a Digital Elevation Model (DEM) file
- Automatically interpolate DEM files with support for shape trimming
- Attach attributions to the particles
- SLBL and boundary selector interface
| 3D phoenix and dragon | DEM with thickness | complex 2D |
|---|---|---|
2D landslide profile with geological structure (nid) |
|---|
| 3D DEM with material ID | Profile |
|---|---|
| SLBL |
|---|
This project is sponserd by Risk Group | Université de Lausanne and China Scholarship Council [中国国家留学基金管理委员会].