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A fluid simulation system based on the MPS method

André Luiz Buarque Vieira e Silva, Caio José dos Santos Brito, Francisco Paulo Magalhães Simões, Veronica Teichrieb
Voxar Labs – Centro de Informatica, Universidade Federal de Pernambuco, Recife/PE 50740-560, Brazil
arXiv:2105.01677 [physics.comp-ph], (4 May 2021)

@article{Buarque_Vieira_e_Silva_2021,

   title={A fluid simulation system based on the MPS method},

   volume={258},

   ISSN={0010-4655},

   url={http://dx.doi.org/10.1016/j.cpc.2020.107572},

   DOI={10.1016/j.cpc.2020.107572},

   journal={Computer Physics Communications},

   publisher={Elsevier BV},

   author={Buarque Vieira-e-Silva, André Luiz and dos Santos Brito, Caio José and Magalhães Simões, Francisco Paulo and Teichrieb, Veronica},

   year={2021},

   month={Jan},

   pages={107572}

}

Fluid flow simulation is a highly active area with applications in a wide range of engineering problems and interactive systems. Meshless methods like the Moving Particle Semi-implicit (MPS) are a great alternative to deal efficiently with large deformations and free-surface flow. However, mesh-based approaches can achieve higher numerical precision than particle-based techniques with a performance cost. This paper presents a numerically stable and parallelized system that benefits from advances in the literature and parallel computing to obtain an adaptable MPS method. The proposed technique can simulate liquids using different approaches, such as two ways to calculate the particles’ pressure, turbulent flow, and multiphase interaction. The method is evaluated under traditional test cases presenting comparable results to recent techniques. This work integrates the previously mentioned advances into a single solution, which can switch on improvements, such as better momentum conservation and less spurious pressure oscillations, through a graphical interface. The code is entirely open-source under the GPLv3 free software license. The GPU-accelerated code reached speedups ranging from 3 to 43 times, depending on the total number of particles. The simulation runs at one fps for a case with approximately 200,000 particles.
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