Large-scale parallel computation for earthquake response spectrum analysis. Issue 2 (16th April 2018)

• Record Type: Journal Article
• Authors: Fan, Xuanhua; Wang, Keying; Xiao, Shifu
• Is Part Of: Engineering computations. Volume 35:Issue 2(2018)
• Page Start: 800
• Page End: 817
• Publication Date: 2018-04-16
• Subjects: Finite element method -- Earthquake response spectrum -- Modal superposition method -- Parallel computation -- Seismic design; Computer-aided engineering -- Periodicals; Computer graphics -- Periodicals; 620.00285
• DOI: 10.1108/EC-08-2016-0294
• Languages: English
• ISSNs: 0264-4401

Abstract

Abstract : Purpose: As a practical engineering method, earthquake response spectra play an important role in seismic hazard assessment and in seismic design of structures. However, the computing scale and the efficiency of commercial software restricted the solution of complex structures. There is a clear need of developing large-scale and highly efficient finite element procedures for response spectrum analysis. Design/methodology/approach: In this paper, the kernel theories for earthquake response spectra are deduced and the corresponding parallel solution flow via the modal superposition method is presented. Based on the algorithm and the parallel data structure of JAUMIN framework, a parallel finite element (FE) solution module is established. Using the solution procedure on a supercomputer equipped with up to thousands of processors, the correctness and parallel scalability of the algorithm are evaluated via numerical experiments of typical engineering examples. Findings: The results show that the solution module has the same precision as the commercial FE software ANSYS; the maximum solution scale achieves 154 million degrees of freedom (DOFs) with a favorable parallel computing efficiency, going far beyond the computing ability of the commercial FE software. Originality/value: The solution scale in this paper is very challenging for the large-scale parallel computing of structural dynamics and will promote the dynamic analysis ability of complex facilities greatly.