JOURNAL ARTICLE

A computational framework for fluid–structure interaction with applications on stability evaluation of breakwater under combined tsunami–earthquake activity.

  • Published In: Computer-Aided Civil & Infrastructure Engineering, 2023, v. 38, n. 3. P. 325 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Huang, Shuai; Liu, Chuanzheng 3 of 3

Abstract

In this article, an improved impervious solid boundary condition of the coupled method called smooth particle hydrodynamics and discrete element method (SPH‐DEM) is proposed, which prevents the fluid particles from penetrating solid boundary under earthquake action. And an improved transmitting boundary condition of SPH‐DEM is designed in order to conquer the reflection of seismic waves on the boundary. Meanwhile, the effective stress method is proposed to be applied to the SPH‐DEM for simulating seabed liquefaction. Based on these, a new computational framework for the SPH‐DEM is put forward. Dynamic triaxial test of seabed soil samples indicate that our proposed computational framework can well reproduce the seismic liquefaction process of the seabed soil. Moreover, our proposed computational framework is used to numerically reproduce the failure mechanisms of a breakwater built in liquefied seabed under combined tsunami–earthquake activity and meantime the centrifuge test is carried out. And the experimental results demonstrate the effectiveness of our proposed computational framework, in which numerical results of it are consistent with results of the centrifuge test. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Computer-Aided Civil & Infrastructure Engineering. 2023/02, Vol. 38, Issue 3, p325
  • Document Type:Article
  • Subject Area:Earth and Atmospheric Sciences
  • Publication Date:2023
  • ISSN:1093-9687
  • DOI:10.1111/mice.12880
  • Accession Number:161338650
  • Copyright Statement:Copyright of Computer-Aided Civil & Infrastructure Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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