An improved GPU-oriented algorithm for elastostatic analysis with boundary element method

Iuspa, Luigi; Fusco, Pietro; Ruocco, Eugenio

doi:10.1016/j.compstruc.2014.08.009

Cited by 10 publications

(2 citation statements)

References 17 publications

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“…The above fracture models are generally based on many numerical methods, such as finite element method, 27 boundary finite element method, 28,29 meshless method, extended finite element method 30 and scaled boundary finite-element method. 31 In 2003, Gao 32 systematically proposed the theoretical system of "Base Force (BF)," which is much simpler than the traditional stress tensor and solves a series of specific problems that are difficult to solve.…”

Section: Introductionmentioning

confidence: 99%

3‐D base force element method on meso‐damage analysis for recycled concrete

Ying

Kamel

2021

Structural Concrete

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The 3-D base force element method (BFEM) for damage problems is proposed, which is applied to analyze the damage mechanism of recycled aggregate concrete (RAC). A piecewise curve damage constitutive model is given to simulate the constitutive relationships of RAC phases. A spatial random aggregate model of RAC is proposed. 3-D numerical simulations of RAC under uniaxial mechanical stress are carried out. The macroscopic stress-strain relationship and failure process of RAC under uniaxial stress based on the 3-D BFEM are obtained. The numerical results show a good consistency with the experimental results. This illustrates that the numerical simulation can reflect the nonlinearity deformation, stress redistribution, and crack propagation process of RAC. In addition, the influence of recycled aggregate replacement percentage on strength and elastic modulus is investigated. The results show that the content proportion of recycled aggregate has a great effect on RAC, which have to be considered in the analysis and the application of RAC. K E Y W O R D S3-D base force element method, damage constitutive model, damage mechanism, numerical simulation, recycled aggregate concrete, spatial random aggregate model

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Section: Introductionmentioning

confidence: 99%

3‐D base force element method on meso‐damage analysis for recycled concrete

Ying

Kamel

2021

Structural Concrete

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“…Lattice-Boltzmann methods are also very suited to fine parallelizations and very high speedups can be reached in GPU implementations: see for example [3,4]. There are also excellent results in molecular dynamics simulations [5], in contact detection for DEM (Discret Element Method) simulations [6] and in boundary element applications [7]. As examples of recent contributions in the FEM context, one can cite the work in [8], concerning the implementation of a domain-decomposition method.…”

Section: Introductionmentioning

confidence: 99%

An explicit dynamics GPU structural solver for thin shell finite elements

Bartezzaghi

Cremonesi

Parolini

et al. 2015

Computers & Structures

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With the availability of user oriented software tools, dedicated architectures, such as the parallel computing platform and programming model CUDA (Compute Unified Device Architecture) released by NVIDIA, one of the main producers of graphics cards, and of improved, highly performing GPU (Graphics Processing Unit) boards, GPGPU (General Purpose programming on GPU) is attracting increasing interest in the engineering community, for the development of analysis tools suitable to be used in validation/verification and virtual reality applications. For their inherent explicit and decoupled structure, explicit dynamics finite element formulations appear to be particularly attractive for implementations on hybrid CPU/GPU or pure GPU architectures. The issue of an optimized, double-precision finite element GPU implementation of an explicit dynamics finite element solver for elastic shell problems in small strains and large displacements and rotations, using unstructured meshes, is here addressed. The conceptual difference between a GPU implementation directly adapted from a standard CPU approach and a new optimized formulation, specifically conceived for GPUs, is discussed and comparatively assessed. It is shown that a speedup factor of about 5 can be achieved by an optimized algorithm reformulation and careful memory management. A speedup of more than 40 is achieved with respect of state-of-the art commercial codes running on CPU, obtaining real-time simulations in some cases, on commodity hardware. When a last generation GPU board is used, it is shown that a problem with more than 16 millions degrees of freedom can be solved in just few hours of computing time, opening the way to virtualization approaches for real large scale engineering problems.

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