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Pseudo-Particle Modeling(PPM)is a particle method proposed by Ge and Li in 1996[Ge,W.,&Li,J. (1996).Pseudo-particle approach to hydrodynamics of particle–fluid systems.In M.Kwauk&J.Li(Eds.), Proceedings of the 5th international conference on circulating fluidized bed(pp.260–265).Beijing:Science Press]and has been used to explore the microscopic mechanism in complex particle–fluid systems.But as a particle method,high computational cost remains a main obstacle for its large-scale application; therefore,parallel implementation of this method is highly desirable.Parallelization of two-dimensional PPM was carried out by spatial decomposition in this paper.The time costs of the major functions in the program were analyzed and the program was then optimized for higher efficiency by dynamic load balancing and resetting of particle arrays.Finally,simulation on a gas–solid fluidized bed with 102,400 solid particles and 1.8×107 pseudo-particles was performed successfully with this code,indicating its scalability in future applications.
Pseudo-Particle Modeling (PPM) is a particle method proposed by Ge and Li in 1996 [Ge, W., & Li, J. (1996). Pseudo- particle approach to hydrodynamics of particle-fluid systems. In M. Kwauk & J. Li (Eds.), Proceedings of the 5th international conference on circulating fluidized bed (pp. 260-265). Beijing: Science Press] and has been used to explore the microscopic mechanism in complex particle-fluid systems. Be as a particle method, high computational cost remains a major obstacle for its large-scale application; therefore, parallel implementation of this method is highly desirable. Parallelization of two-dimensional PPM was carried out by spatial decomposition in this paper. time costs of the major functions in the program were then optimized for higher efficiency by dynamic load balancing and resetting of particle arrays. Finally, simulation on a gas-solid fluidized bed with 102,400 solid particles and 1.8 × 107 pseudo-particles was performed successfully with this code, indicating its scalability in future applications.