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Large‐scale seismic soil–structure interaction analysis via efficient finite element modeling and multi‐GPU parallel explicit algorithm.

Authors :
Zhao, Mi
Ding, Qingpeng
Cao, Shengtao
Li, Zhishan
Du, Xiuli
Source :
Computer-Aided Civil & Infrastructure Engineering. Jun2024, Vol. 39 Issue 12, p1886-1908. 23p.
Publication Year :
2024

Abstract

As urban population increases, integrated underground–aboveground complexes are being constructed at growing paces in major cities. The seismic analysis of such complexes is crucial for the safety and functionality in the threat of potential earthquake disasters. However, fine‐grained numerical modeling and analysis of such large and complex structures are still inefficient due to the consideration of the soil–structure interaction (SSI). To address this challenge, an efficient approach for numerical modeling of large‐scale seismic SSI analysis is presented in this paper to overcome the limitations of existing finite element analysis (FEA) software. Moreover, a multi‐graphic processing unit (GPU) parallel explicit algorithm is implemented for the nonlinear dynamic SSI problems to further increase the computational efficiency. A large underground–aboveground complex project in China is used as an example to demonstrate the capability of the integrated method. The accuracy and reliability of the multi‐GPU parallel explicit finite element algorithm for SSI analysis (GFEA‐SSIA) are verified through a comparative analysis of the linear‐elastic and nonlinear dynamic response of the building calculated by GFEA‐SSIA and common FEA software. Finally, the structural response and structural damage of the underground–aboveground complex are analyzed under multidirectional seismic motions, and the damage distributions of the structures are provided. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10939687
Volume :
39
Issue :
12
Database :
Academic Search Index
Journal :
Computer-Aided Civil & Infrastructure Engineering
Publication Type :
Academic Journal
Accession number :
177649932
Full Text :
https://doi.org/10.1111/mice.13163