ORCID Profile
0000-0001-8747-8952
Current Organisations
The Hong Kong Polytechnic University
,
Hong Kong University of Science and Technology
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Publisher: American Society of Civil Engineers (ASCE)
Date: 09-2021
Publisher: Elsevier BV
Date: 02-2023
Publisher: Springer International Publishing
Date: 2021
Publisher: Wiley
Date: 03-2019
DOI: 10.1002/NAG.2921
Publisher: Elsevier BV
Date: 09-2022
Publisher: Wiley
Date: 23-03-2021
DOI: 10.1002/NAG.3207
Abstract: In this paper, a new formulation of material point method (MPM) to model coupled soil deformation and pore fluid flow problems is presented within the framework of the theory of porous media. The saturated porous medium is assumed to be consisting of incompressible pore fluid and deformable soil skeleton made up of incompressible solid grains. The main difference of the proposed MPM algorithm is the implicit treatment of pore‐water pressure which satisfies its incompressibility internal constraint. The resulting solid‐fluid coupled equations are solved by using a splitting algorithm based on the Chorin's projection method. The splitting algorithm helps to mitigate numerical instabilities at the incompressibility limit when equal‐order interpolation functions are used. The key strengths of the proposed semi‐implicit coupled MPM formulation is its capability to reduce pressure oscillations as well as to increase the time step size, which is independent of the fluid incremental strain level and the soil permeability. The proposed semi‐implicit MPM is validated by comparing the numerical results with the analytical solutions of several numerical tests, including 1D and 2D plane‐strain consolidation problems. To demonstrate the capability of the proposed method in simulating practical engineering problems involving large deformations, a hydraulic process leading to slope failure is studied, and the numerical result is validated by the monitored data.
Publisher: Elsevier BV
Date: 09-2021
Publisher: Elsevier BV
Date: 2024
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: 07-10-2020
DOI: 10.1002/NME.6549
Publisher: Springer Science and Business Media LLC
Date: 13-04-2020
Publisher: Springer International Publishing
Date: 2018
Publisher: Elsevier BV
Date: 10-2020
No related grants have been discovered for Weijian Liang.