Large-scale simulation of crack propagation based on continuum damage mechanics and two-step mesh partitioning

Chung, Soonwan; Lee, Chang Sung; Kim, Seung Jo

doi:10.1016/j.mechmat.2005.05.011

Cited by 1 publication

(1 citation statement)

References 26 publications

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“…Considering the rapid development of multicore processors in recent years, parallel computing has been increasingly used in solving eigenstrains and related problems, such as dislocation dynamics [19], crack propagation [20], and composite materials [21]. To employ parallel computing, a large problem is divided into smaller independent components, where each processor executes its own part of the algorithm simultaneously, leading to a significant increase in computational speed; and the theoretical maximum acceleration can be predicted by Amdahl's law [22].…”

Section: Introductionmentioning

confidence: 99%

An Efficient Numerical Method With a Parallel Computational Strategy for Solving Arbitrarily Shaped Inclusions in Elastoplastic Contact Problems

Wang¹,

Jin²,

Zhou

et al. 2013

Journal of Tribology

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The plastic zone developed during elastoplastic contact may be effectively modeled as an inclusion in an isotropic half space. This paper proposes a simple but efficient computational method to analyze the stresses caused by near surface inclusions of arbitrary shape. The solution starts by solving a corresponding full space inclusion problem and proceeds to annul the stresses acting normal and tangential to the surface, where the numerical computations are processed by taking advantage of the fast Fourier transform techniques with a parallel computing strategy. The extreme case of a cuboidal inclusion with one facet on the surface of the half space is chosen to validate the method. When the surface truncation domain is extended sufficiently and the grids are dense enough, the results based on the new approach are in good agreement with the exact solutions. When solving a typical elastoplastic contact problem, the present analysis is roughly two times faster than the image inclusion approach and six times faster than the direct method. In addition, the present work demonstrates that a significant enhancement in the computational efficiency can be achieved through the introduction of parallel computation.

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