Space decomposition based parallelization solutions for the combined finiteediscrete element method

来源 :Journal of Rock Mechanics and Geotechnical Engineering | 被引量 : 0次 | 上传用户:yinlei102
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The combined finiteediscrete element method(FDEM) belongs to a family of methods of computational mechanics of discontinua. The method is suitable for problems of discontinua, where particles are deformable and can fracture or fragment. The applications of FDEM have spread over a number of disciplines including rock mechanics, where problems like mining, mineral processing or rock blasting can be solved by employing FDEM. In this work, a novel approach for the parallelization of two-dimensional(2D) FDEM aiming at clusters and desktop computers is developed. Dynamic domain decomposition based parallelization solvers covering all aspects of FDEM have been developed. These have been implemented into the open source Y2 D software package and have been tested on a PC cluster. The overall performance and scalability of the parallel code have been studied using numerical examples. The results obtained confirm the suitability of the parallel implementation for solving large scale problems. The combined finiteediscrete element method (FDEM) belongs to a family of methods of computational mechanics of discontinua. The method is suitable for problems of discontinua, where particles are deformable and can fracture or fragment. The applications of FDEM have spread over a number of disciplines including rock mechanics, where problems like mining, mineral processing or rock blasting can be solved by employing FDEM. In this work, a novel approach for the parallelization of two-dimensional (2D) FDEM aiming at clusters and desktop computers is developed. Dynamic domain decomposition based parallelization solvers covering all aspects of FDEM have been developed. These have been implemented into the open source Y2 D software package and have been tested on a PC cluster. The overall performance and scalability of the parallel code have been studied using numerical examples. The results obtained confirm the suitability of the parallel implementation for solving large scale problems.
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