The importance of the two-phase flow model relies upon the correct simulation of specific problems in which the passive tracer model fails; however, the mathematical and numerical models need to be improved in order to reproduce fluid-solid particle interactions of greater complexity. Such is the case with regard to simulating erosion patterns suffered upon horizontal granular beds by means of a vertical water jet as shown here. Moreover, sequential platforms have proven to be insufficient in providing the required computational power needed to obtain fast and detailed simulations. In this paper, a fully parallel algorithm for a two-dimensional x/z two-phase Eulerian approach is presented and applied for the numerical solution of the erosion of sediment beds. The parallelization is designed by a row and column block domain decomposition technique using a distributed memory platform with Message Passing Interface (MPI). Arising from the numerical method, a Poisson problem for the pressure is solved at each time step. The discretization results in a non-symmetric variable-coefficient linear system which is solved using several parallel Successive Over-Relaxation (SOR) algorithms, including partitioning and coloring methods. The specification of the optimal relaxation parameter to achieve efficiency is found numerically. Results show that SOR methods achieve faster convergence rates and the simulation time achieves an order similar to that required for the typical, widely-used Bi-Conjugate Gradient Stabilized (Bi-CGSTAB) method. The performances of the algorithms are evaluated in terms of speedup and efficiency. The results indicate that the parallel code significantly improves the results of the sequential calculation in general. (C) 2018 Elsevier Ltd. All rights reserved.
机构:
Tianjin Univ, State Key Lab Hydraul Engn Intelligent Construct &, Tianjin 300072, Peoples R China
Tianjin Univ, Sch Civil Engn, Tianjin 300072, Peoples R ChinaTianjin Univ, State Key Lab Hydraul Engn Intelligent Construct &, Tianjin 300072, Peoples R China
Ma, Li-ping
Lian, Ji-jian
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Tianjin Univ, State Key Lab Hydraul Engn Intelligent Construct &, Tianjin 300072, Peoples R China
Tianjin Univ, Sch Civil Engn, Tianjin 300072, Peoples R ChinaTianjin Univ, State Key Lab Hydraul Engn Intelligent Construct &, Tianjin 300072, Peoples R China
Lian, Ji-jian
Liu, Dong-ming
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Tianjin Univ, State Key Lab Hydraul Engn Intelligent Construct &, Tianjin 300072, Peoples R China
Tianjin Univ, Sch Civil Engn, Tianjin 300072, Peoples R China
Sichuan Univ, State Key Lab Hydraul & Mt River Engn, Chengdu 610065, Peoples R ChinaTianjin Univ, State Key Lab Hydraul Engn Intelligent Construct &, Tianjin 300072, Peoples R China
机构:
Beijing Computat Sci Res Ctr, Appl & Computat Math Div, Beijing, Peoples R China
Hong Kong Univ Sci & Technol, Dept Math, Hong Kong, Peoples R ChinaBeijing Computat Sci Res Ctr, Appl & Computat Math Div, Beijing, Peoples R China
Li, Xiang
Du, Qiang
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Columbia Univ, Dept Appl Phys & Appl Math, New York, NY 10027 USA
Columbia Univ, Data Sci Inst, New York, NY 10027 USABeijing Computat Sci Res Ctr, Appl & Computat Math Div, Beijing, Peoples R China
Du, Qiang
Wang, Xiao-Ping
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Hong Kong Univ Sci & Technol, Dept Math, Hong Kong, Peoples R ChinaBeijing Computat Sci Res Ctr, Appl & Computat Math Div, Beijing, Peoples R China