ORCID Profile
0000-0002-3410-3935
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Publisher: Elsevier BV
Date: 02-2023
Publisher: Springer Science and Business Media LLC
Date: 24-02-2021
Publisher: Elsevier BV
Date: 08-2020
Publisher: Elsevier BV
Date: 12-2021
Publisher: Elsevier BV
Date: 09-2022
Publisher: Wiley
Date: 12-07-2019
DOI: 10.1002/NAG.2951
Publisher: Wiley
Date: 21-03-2022
DOI: 10.1002/NME.6963
Abstract: This study presents a scalable three‐dimensional (3D) multiscale framework for continuum‐discrete modeling of granular materials. The proposed framework features rigorous coupling of a continuum‐based material point method (MPM) and a discrete approach discrete element method (DEM) to enable cross‐scale modeling of boundary value problems pertaining to granular media. It employs MPM to solve the governing equations of a macroscopic continuum domain for a boundary value problem that may undergo large deformation. The required loading‐path‐dependent constitutive responses at each material point of the MPM are provided by a DEM solution based on grain‐scale contact‐based discrete simulations that receive macroscopic information at the specific material point as boundary conditions. This hierarchical coupling enables direct dialogs between the macro and micro scales of granular media while fully harnessing the predictive advantages of both MPM and DEM at the two scales. An effective, scalable parallel scheme is further developed, based on the flat message passing interface (MPI) model, to address the computational cost of the proposed framework for 3D large‐scale simulations. We demonstrate that the proposed parallel scheme may offer up to 32X and 40X speedup in strong and weak scaling tests, respectively, significantly empowering the numerical performance and predictive capability of the proposed framework. The 3D parallelized multiscale framework is validated by an element test and a column collapse problem, before being applied to simulate the intrusion of a solid object. The multiscale simulation successfully captures the characteristic response of intrusion as postulated by the modified Archimedes' law theory. The progressive development of the stagnant zone during the intrusion is further examined from a cross‐scale perspective.
Publisher: Wiley
Date: 23-10-2022
DOI: 10.1002/NME.7139
Abstract: Neighbor searching is an essential and computationally heavy step in particle‐based numerical methods such as discrete element method (DEM), molecular dynamics, peridynamics, and smooth particle hydrodynamics. This article presents a novel approach to accelerate particle‐based simulations by leveraging ray tracing (RT) cores in addition to CUDA cores on RTX GPUs. The neighbor search problem is first numerically converted into a general ray tracing problem so that it can be possible to utilize the hardware acceleration of RT cores. A new, general‐purpose RT‐based neighbor search algorithm is then proposed and benchmarked with a prevailing cell‐based one. As a showcase, both algorithms are implemented into a GPU‐based DEM code for simulating large‐scale granular problems including packing, column collapse and debris flow. The overall simulation performance is examined with varying problem sizes and GPU specs. It demonstrates that the RT‐based simulations are 10%–60% faster than the cell‐based ones, depending on the simulated problems and GPU specs. This study offers a new recipe for next‐generation high‐performance computing of large‐scale engineering problems using particle‐based numerical methods.
Publisher: Elsevier BV
Date: 02-2021
Publisher: Wiley
Date: 07-10-2020
DOI: 10.1002/NME.6549
Publisher: Elsevier BV
Date: 02-2021
Publisher: American Physical Society (APS)
Date: 22-01-2020
Publisher: Springer Science and Business Media LLC
Date: 09-08-2022
Publisher: Springer Science and Business Media LLC
Date: 10-08-2023
No related grants have been discovered for Shiwei Zhao.