SPH-DEM coupling method based on GPU and its application to the landslide tsunami. Part I: method and validation

Zhou, Qian; Xu, Wenjie; Dong, Xue-Yang

doi:10.1007/s11440-021-01388-2

Cited by 21 publications

(6 citation statements)

References 57 publications

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“…A principal type of discrete approach is called Discrete Element Method (DEM), which describes every particle in a system using Newton’s equations of motion . DEM-based simulation has been recognized as an effective method to study the fundamentals of granular materials and assess the performance of industrial processes. − …”

Section: Methodsmentioning

confidence: 99%

Integrating Graph Neural Network-Based Surrogate Modeling with Inverse Design for Granular Flows

Jiang,

Byrne,

Glassey

et al. 2024

Ind. Eng. Chem. Res.

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Granular flows are central to a wide range of natural phenomena and industrial processes such as landslides, industrial mixing, and material handling and present intricate particle dynamics challenges. This study introduces a novel approach utilizing a Graph Neural Network-based Simulator (GNS) integrated with an inverse design for optimizing Discrete Element Method (DEM) parameters in granular flow simulations. The GNS model, trained on data sets generated from high-fidelity DEM simulations, exhibits enhanced predictive accuracy and generalization capabilities across various materials and granular collapse scenarios. Methodologically, the study contrasts the GNS approach with conventional Design of Experiment (DoE) methods, highlighting its enhanced computational efficiency and dynamic optimization capacity for complex parameter interactions in granular flows. The results demonstrate the GNS method superiority over the DoE in terms of computational speed and handling intricate parameter relationships. This work offers an advancement in computational techniques for granular flow studies, showing the potential of using differential simulations for realistic problems.

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Section: Methodsmentioning

confidence: 99%

Integrating Graph Neural Network-Based Surrogate Modeling with Inverse Design for Granular Flows

Jiang,

Byrne,

Glassey

et al. 2024

Ind. Eng. Chem. Res.

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“…The completed momentum conservation equation of the material particles can be obtained by substituting Equation (13) into Equation (9). The boundary particles take part in the computation of the momentum equation like soil particles.…”

Section: Boundary Particle Methodsmentioning

confidence: 99%

“…Smoothed particle hydrodynamics (SPH) is a truly meshless method becoming popular in recent years because it can easily handle large deformation, moving boundaries, and material interfaces. It was successfully applied to some challenging geotechnical problems, for example, large deformation, 10,11,13 granular flows, [14][15][16][17] shear band, 18,19 and dynamic soil-fluid coupling. [20][21][22] The above applications show that SPH is a capable method.…”

Section: Introductionmentioning

confidence: 99%

Regularized SPH model for soil–structure interaction with generalized frictional boundary

Wang¹,

Wu²,

Peng

2023

Num Anal Meth Geomechanics

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This paper proposes a regularized smoothed particle hydrodynamics (SPH) scheme to solve the problems of tensile instability and stress noise in largedeformation soil-structure interaction. Particle shifting and stress regularization are combined to maintain uniform stresses and particle distributions. A generalized frictional boundary condition is presented to model soil-structure interfaces with abitrary friction coefficients. A modified particle shifting technique is developed to regularize particles near the frictional boundaries. Furthermore, GPU acceleration algorithm is adopted to improve the efficiency. The proposed scheme is compared with the conventional SPH methods using numerical examples, including the collapse of three-dimensional granular column, the collapse of the cohesive soil, and pipe penetrates into soft clay. The comparison indicates that the proposed regularized SPH model can give highly accurate results for large-deformation soil-structure interaction problems with arbitrary friction coefficient.

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“…According to the concept of resolved coupling, DEM particles are driven by the pressure and viscous force. They serve as the boundaries for the fluid (Zhang et al, 2009;Zhou et al, 2022). In order to fit the curve boundary, the selected particle spacing of boundary is small.…”

Section: Introductionmentioning

confidence: 99%

“…In addition to the gravity and contact force, DEM particles are moved by the empirical drag force and buoyancy from the fluid. Simulations of water entry of a sphere are carried out by SPH−DEM resolved coupling method (Zhou et al, 2022) and the SPH−DEM unresolved coupling method (Xu et al, 2019). The SPH-DEM unresolved coupling method with low resolution even performs better than the resolved coupling method with higher resolution.…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulations of Liquid-Solid Flows in A Vertical Pipe by MPS-DEM Coupling Method

2022

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In the process of deep-sea mining, the liquid-solid flows in the vertical transportation pipeline are very complex. In the present work, an in-house solver MPSDEM-SJTU based on the improved MPS and DEM is developed for the simulation of hydraulic conveying. Firstly, three examples including the multilayer cylinder collapse, the Poiseuille flow and two-phase dam-break are used to validate the precision of the DEM model, the pipe flow model and MPS-DEM coupling model, respectively. Then, the hydraulic conveying with coarse particles in a vertical pipe is simulated. The solid particle distribution is presented and investigated in detail. Finally, the coupling method is successfully applied for the simulation of the liquid-solid flows in a vertical pipe with rotating blades, which shows the stability of the solver under rotating boundary conditions. This fully Lagrangian model is expected to be a new approach for analyzing hydraulic conveying.

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SPH-DEM coupling method based on GPU and its application to the landslide tsunami. Part I: method and validation

Cited by 21 publications

References 57 publications

Integrating Graph Neural Network-Based Surrogate Modeling with Inverse Design for Granular Flows

Integrating Graph Neural Network-Based Surrogate Modeling with Inverse Design for Granular Flows

Regularized SPH model for soil–structure interaction with generalized frictional boundary

Numerical Simulations of Liquid-Solid Flows in A Vertical Pipe by MPS-DEM Coupling Method

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