A scalable parallel computing SPH framework for predictions of geophysical granular flows

被引:59
|
作者
Yang, Edward [1 ,2 ]
Bui, Ha H. [1 ,2 ]
De Sterck, Hans [4 ]
Nguyen, Giang D. [3 ]
Bouazza, Abdelmalek [2 ]
机构
[1] Monash Univ, Monash Computat Geomech MCG Lab, Melbourne, Vic, Australia
[2] Monash Univ, Dept Civil Engn, Melbourne, Vic, Australia
[3] Univ Adelaide, Sch Civil Environm & Min Engn, Adelaide, SA, Australia
[4] Univ Waterloo, Dept Appl Math, Waterloo, ON, Canada
基金
加拿大自然科学与工程研究理事会; 澳大利亚研究理事会;
关键词
Parallel computing; Message Passing Interface (MPI); Smoothed Particle Hydrodynamics (SPH); Granular flows; Geophysical flows; SMOOTHED PARTICLE HYDRODYNAMICS; SLOPE STABILITY ANALYSIS; FINITE-ELEMENT-ANALYSIS; FREE-SURFACE FLOWS; LARGE-DEFORMATION; COLUMN COLLAPSE; SIMULATION; MODEL; LANDSLIDES; BOUNDARY;
D O I
10.1016/j.compgeo.2020.103474
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper presents a parallel computing Smoothed Particle Hydrodynamics (SPH) framework for geophysical granular flows scalable on large CPU clusters. The framework is accomplished by adopting a Message Passing Interface (MPI) approach with domain partitioning strategy. The Orthogonal Recursive Bisection (ORB) technique is utilised to subdivide the computational domain. The ORB algorithm is implemented such that any number of MPI processes can be used instead of being limited to powers of two. To avoid global communications in the particle distribution process, a diffusion-based distribution algorithm is implemented and demonstrated to be much faster than global communication approaches when distributing particles to non-neighbouring processes. The proposed parallel scheme achieves 95% weak scaling efficiency and up to 900 times strong scaling speedup on 1024 CPU cores. The parallel scheme enables previously unfeasible simulations to be carried out and here we apply it to the investigation of the granular column collapse experiment under full three-dimensional, axisymmetric conditions for aspect ratios up to 30, not attempted previously using numerical techniques in the literature. Enabled by the parallel scheme, the simulations use up to 11.7 million SPH particles. The investigation is conducted using two popular constitutive models commonly used in modelling of granular flows: the elasto-plastic model with Drucker-Prager yield criterion and the mu(I) rheological model. While very good agreement with experimental data has been reported for both models for small and intermediate aspect ratios, the large-scale simulations conducted for large aspect ratios show that the Drucker-Prager model tends to overpredict final deposit height, and the mu(I) model under-predicts it. Furthermore, due to the capability of the parallel scheme to model the 3D axisymmetric column collapse at higher resolutions, we demonstrate that the elasto-plastic approach is capable of capturing arching effects in the stress profile, whereas the it (I) model cannot.
引用
收藏
页数:22
相关论文
共 50 条
  • [21] JOSEPHINE: A parallel SPH code for free-surface flows
    Cherfils, J. M.
    Pinon, G.
    Rivoalen, E.
    COMPUTER PHYSICS COMMUNICATIONS, 2012, 183 (07) : 1468 - 1480
  • [22] The application of parallel computing to data processing in geophysical methods
    Wang, Xue
    Jin, Hao
    2008 PROCEEDINGS OF INFORMATION TECHNOLOGY AND ENVIRONMENTAL SYSTEM SCIENCES: ITESS 2008, VOL 2, 2008, : 512 - 515
  • [23] The application of parallel computing to data processing in geophysical methods
    Xue, Wang
    Hao, Jin
    ITESS: 2008 PROCEEDINGS OF INFORMATION TECHNOLOGY AND ENVIRONMENTAL SYSTEM SCIENCES, PT 1, 2008, : 667 - 671
  • [24] TowardsVerified Scalable Parallel Computing with Coqand Spark
    Loulergue, Frederic
    Philippe, Jolan
    PROCEEDINGS OF THE 25TH ACM INTERNATIONAL WORKSHOP ON FORMAL TECHNIQUES FOR JAVA-LIKE PROGRAMS, FTFJP 2023, 2023, : 11 - 17
  • [25] A scalable parallel computing method for autonomous platoons
    Wu, Qing
    Ge, Xiaohua
    Han, Qing-Long
    Cole, Colin
    Spiryagin, Maksym
    VEHICLE SYSTEM DYNAMICS, 2024, 62 (09) : 2283 - 2303
  • [26] Personalized Linguistic Information: A Framework of Granular Computing
    Cabrerizo, F. J.
    Morente-Molinera, J. A.
    Alonso, S.
    Urena, R.
    Herrera-Viedma, E.
    PROCEEDINGS OF THE 11TH CONFERENCE OF THE EUROPEAN SOCIETY FOR FUZZY LOGIC AND TECHNOLOGY (EUSFLAT 2019), 2019, 1 : 297 - 304
  • [27] A New Parallel Framework of SPH-SWE for Dam Break Simulation Based on OpenMP
    Wu, Yushuai
    Tian, Lirong
    Rubinato, Matteo
    Gu, Shenglong
    Yu, Teng
    Xu, Zhongliang
    Cao, Peng
    Wang, Xuhao
    Zhao, Qinxia
    WATER, 2020, 12 (05)
  • [28] SPH-Based Numerical Study on the Influence of Baffle Height and Inclination on the Interaction between Granular Flows and Baffles
    Cheng, Hualin
    Zhang, Bei
    Huang, Yu
    WATER, 2022, 14 (19)
  • [29] THE DESIGN OF AN OPERATING SYSTEM FOR A SCALABLE PARALLEL COMPUTING ENGINE
    AUSTIN, P
    MURRAY, K
    WELLINGS, A
    SOFTWARE-PRACTICE & EXPERIENCE, 1991, 21 (10) : 989 - 1013
  • [30] Combined scheduling and mapping for scalable computing with parallel tasks
    Duemmler, Joerg
    Rauber, Thomas
    Ruenger, Gudula
    SCIENTIFIC PROGRAMMING, 2012, 20 (01) : 45 - 67