Engineering Mechanics ›› 2019, Vol. 36 ›› Issue (2): 53-65,86.doi: 10.6052/j.issn.1000-4750.2017.11.0898

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DEVELOPMENT ON SOFTWARE PLATFORM FOR NONLINEAR DYNAMIC ANALYSIS OF UNDERGROUND STRUCTURE BASED ON GPU PARALLEL COMPUTING

CAO Sheng-tao, LU De-chun, DU Xiu-li, ZHAO Mi, CHENG Xing-lei   

  1. Key Lab of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, Beijing 100124, China
  • Received:2017-11-27 Revised:2018-11-08 Online:2019-02-22 Published:2019-02-22

Abstract: The implicit nonlinear dynamic analysis of underground structures is of poor convergence and low computational efficiency. Based on GPU parallel computing, a software platform for the explicit dynamic analysis of underground structures was established, which can solve the technical bottleneck of the implicit method. In this platform, a smeared crack model for concrete was proposed and implemented. A coupling method for rebar fibers and solid elements was developed and implemented. Based on the isoparametric element idea, a method for calculating the element area of artificial boundary nodes was proposed. A two-node interface element for solid elements was proposed to perform the interaction analysis between soil and structure with uncoordinated nodes. The gravity field analysis, linear and nonlinear dynamic analysis of Daikai subway station in Japan were performed by the software. The results of gravity field analysis and linear dynamic analysis were compared with the results of ABAQUS. The results of the software were in an agreement with the results of ABAQUS, and the computational efficiency was about 5.68 times the efficiency of ABAQUS. Thusly, the accuracy and efficiency of the software modules were verified. Besides, the stability and rationality of the software nonlinear analysis were verified by comparing the results of nonlinear analysis with the disaster investigation.

Key words: underground structure, nonlinear dynamic analysis, GPU parallel computing, constitutive model, software platform

CLC Number: 

  • TU311.3
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