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A Taichi implementation of various SPH based methods, including WCSPH, PCISPH, DFSPH.

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SPH_Taichi

A Taichi implementation of Smooth Particle Hydrodynamics (SPH) simulator. Taichi is a productive & portable programming language for high-performance, sparse & differentiable computing. The 2D case below can be run and rendered efficiently on a laptop thanks to Taichi.

Features

Currently, the following features have been implemented:

  • Weakly Compressible SPH (WCSPH)[1]
  • Predictive-Corrective Incompressible SPH (PCISPH)[2]
  • Divergence free SPH (DFSPH)[3]

Taichi Version: 0.6.10

Example

  • Demo (PCISPH, 4.5k particles)

Run python scene.py

Demos for the other two methods: python scene.py --method WCSPH or python scene.py --method DFSPH

Reference

  1. M. Becker and M. Teschner (2007). "Weakly compressible SPH for free surface flows". In:Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation. Eurographics Association, pp. 209–217.
  2. B. Solenthaler and R. Pajarola (2009). “Predictive-corrective incompressible SPH”. In: ACM SIGGRAPH 2009 papers, pp. 1–6.
  3. J. Bender, D. Koschier (2015) Divergence-free smoothed particle hydrodynamics[C]//Proceedings of the 14th ACM SIGGRAPH/Eurographics symposium on computer animation. ACM, 2015: 147-155.

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A Taichi implementation of various SPH based methods, including WCSPH, PCISPH, DFSPH.

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