Massive parallelization of the phase field formulation for crack propagation with time adaptivity

被引:76
作者
Ziaei-Rad, Vahid [1 ]
Shen, Yongxing [2 ]
机构
[1] UPC BarcelonaTech, Univ Politecn Catalunya, Lab Calcul Numer, Barcelona 08034, Spain
[2] Shanghai Jiao Tong Univ, Univ Michigan Shanghai Jiao Tong Univ Joint Inst, 800 Dongchuan Rd, Shanghai 200240, Peoples R China
基金
中国国家自然科学基金;
关键词
Phase field; GPU parallelization; Explicit methods; Fracture mechanics; Time adaptivity; FINITE-ELEMENT-METHOD; DYNAMIC BRITTLE-FRACTURE; NUMERICAL EXPERIMENTS; VARIATIONAL APPROACH; GRADIENT FLOW; MODELS; APPROXIMATION; MECHANICS;
D O I
10.1016/j.cma.2016.04.013
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The phase field method has proven to be an important tool in computational fracture mechanics in that it does not require complicated crack tracking and is able to predict crack nucleation and branching. However, the computational cost of such a method is high due to a small regularization length parameter, which in turn restricts the maximum element size that can be used in a finite element mesh. In this work we developed a massively parallel algorithm on the graphical processing unit (GPU) to alleviate this difficulty in the case of dynamic brittle fracture. In particular, we adopted the standard finite element method on an unstructured mesh combined with second order explicit integrators. To ensure stability, we designed a time adaptivity strategy to account for the decreasing critical time step during the evolution of the fields. We demonstrated the performance of the GPU-implemented phase field models by means of representative numerical examples, with which we studied the effect of the artificial viscosity, an artificial parameter to be input, and compared the crack path branching predictions from three popular phase field models. Finally, we verified the method with convergence studies and performed a scalability study to demonstrate the desired linear scaling of the program in terms of the wall time per physical time as a function of the number of degrees of freedom. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:224 / 253
页数:30
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