Concerning the time-consuming problem of finite element analysis for solving the nonlinear dynamic problems of large-scale structure,some parallel computational strategies for implementing explicit nonlinear finite element analysis were proposed under the environment of Message Passing Interface (MPI) cluster.Based on the technique of domain decomposition with explicit message passing,using overlapped,non-overlapped domain decomposition techniques and Dynamic Task Allocation (DTA) algorithm,domain decomposition parallel algorithms for overlapped domain,non-overlapped domain,clustering for DTA,DTA and Dynamic Load Balancing (DLB) were researched by overlapping calculations and communications to improve the performance of communication between processors.A parallel finite element analysis programwas developed with message passing interface as software development environment.Some numerical examples were implemented on workstation cluster to evaluate the performance of the parallel algorithm,the computation performance was also compared with the conventional Newmark algorithm.The experimental results show that the performance of the algorithm for dynamic task allocation with clustering technique is better than that of the dynamic task allocation,which is lower than that of the domain decomposition algorithm,and the dynamic load balancing algorithm is the best.For the problem with the same size,the proposed algorithms are faster and better than conventional Newmark algorithm.The proposed algorithms are efficient for parallel computing of nonlinear dynamic problems of structure.%针对大规模结构非线性动力问题的有限元分析非常耗时,基于消息传递接口(MPI)机群环境,提出多种基于并行求解策略的显式有限元并行算法.基于显式消息传递的区域分解技术,采取重叠、非重叠区域分解技术及动态任务分配方法,通过将计算与通信重叠,优化处理器间的通信,对非重叠通信区域分解并行算法、重叠通信区域分解并行算法、群动态任务分配算法、动态任务分配算法及动态负载平衡算法进行研究.为在机群环境下实现非线性动力有限元分析,开发了基于有效并行求解策略的显式有限元并行算法.编写了基于消息传递编程模式的并行有限元程序,在工作站机群上实现了数值算例,分析了算法的性能,并与传统的Newmark算法进行了比较.算例表明:群动态任务分配算法的性能优于动态任务分配算法,低于区域分解算法的性能,动态负载平衡算法最优.对相同规模的问题提出的算法比Newmark算法快,优于Newmark算法.对结构非线性动力问题的有限元分析,所提出的并行算法是可行有效的.
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