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Simulation of Solid Particle Interactions Including Segregated Lamination by Using MPS Method

Kyung Sung Kim1, Moo-Hyun Kim2,*, Hakun Jang3, Hee Chen Cho4

1 Tongmyong University, Busan, Republic of Korea.
2 Texas A&M University, College Station, TX, U.S.A.
3 Texas A&M University, College Station, TX, U.S.A.
4 Mississippi State University, MS, U.S.A.

* Corresponding Author: Moo-Hyun Kim. Email: email.

Computer Modeling in Engineering & Sciences 2018, 116(1), 11-29. https://doi.org/10.31614/cmes.2018.00199

Abstract

A new MPS (Moving Particle Semi-implicit) method is developed to simulate the behaviors and interactions of multiple fine solid particles as a continuum. As fluid particles are affected by viscosity, so solid particles are affected by friction. The solid particle dynamics for landslides, dumping, and gravity sorting etc. which can be difficult to simulate using conventional MPS methods, are modeled in this paper using the developed multi-solid-particle MPS method that benefits from drawing comparisons with the corresponding fluid particle behaviors. The present MPS results for dumping solid particles are verified against the corresponding DEM (Discrete Element Method) results. The shape and angle of repose for solid particles are shown to be highly dependent on the friction coefficient between grains. The peculiar phenomenon of segregated lamination (gravity sorting) among grains of different densities has been successfully reproduced using the multi-solid-particle MPS method. Lamination quality is found to be dependent on the densities and frictional coefficients of the constituent particles. The behavior of heterogeneous mixtures of multiple solid and liquid particles are also compared and discussed. This newly developed tool offers a window into the physical dynamics of sedimentology that the broader geoscience community might benefit from.

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Cite This Article

Kim, K. S., Kim, M., Jang, H., Cho, H. C. (2018). Simulation of Solid Particle Interactions Including Segregated Lamination by Using MPS Method. CMES-Computer Modeling in Engineering & Sciences, 116(1), 11–29. https://doi.org/10.31614/cmes.2018.00199



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