Parallel Computing for Nonlinear Dynamic Finite Element Structural Analysis with General Sparse Matrix Technology

The principal objective of this research is to reduce the elapsed time of largescale nonlinear dynamic structural finite element analysis using parallel computing techniques. The major tasks and contributions of this research are: (a) employing the general sparse matrix technique to reduce the computing time and storage requirements for both sequential and parallel substructure analysis (b) employing state-of-the-art matrix ordering methods to perform substructure matrix ordering to reduce the extra computations of substructure method, (c) proposing an iterative mesh partitioning approach for better load balance of parallel substructure analysis, (d) employing the multi-level substructure method for improving the efficiency of the parallel finite element analyses, and (e) designing and implementing a highperformance finite element environment, called FE2000, for linear or geometric nonlinear, static or implicit dynamic finite element structural analyses. This research carefully investigates and integrates the aforementioned techniques and approaches into parallel finite element analysis. Numerical experiments show that the total elapsed time of large-scale nonlinear dynamic structural analysis can be significantly reduced by integrating the above techniques.