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author:

Feng, Y. (Feng, Y..) [1] | Briseghella, B. (Briseghella, B..) [2] | Fenu, L. (Fenu, L..) [3] | Zordan, T. (Zordan, T..) [4]

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Scopus

Abstract:

To address the challenges of optimizing cable-stayed bridges under seismic loading, a multi-objective particle swarm optimization (PSO) procedure to optimize load-bearing components of cable-stayed bridges is presented. The procedure integrates numerical computing software MATLAB with finite element analysis software ANSYS. The final goal is to identify the optimal cross-sectional dimensions of towers and girders, as well as the optimal cross-sectional areas of cables and their corresponding pre-tension forces. The goal is achieved by coupling the PSO for global searching, time history analysis or spectrum analysis for dynamic evaluation, and the influence matrix method for determining the cable pre-tension forces. The effectiveness of proposed procedure is validated through a two dimensional (2D) and a three dimensional (3D) symmetric layout bridge. Following that, the design procedure is utilized in the preliminary design of a single tower bridge without backstays located in Pescara, Italy. The results demonstrate that the proposed optimization procedure could be an useful tool to optimize cable-stay bridges under seismic loading. © The Author(s), under exclusive licence to Springer Nature B.V. 2025.

Keyword:

Cross-sectional area Multi-objective Particle swarm optimization Pre-tension forces Seismic load

Community:

  • [ 1 ] [Feng Y.]School of Civil Engineering and Architecture, Hainan University, Hainan, 570228, China
  • [ 2 ] [Briseghella B.]College of Civil Engineering, Fuzhou University, Fuzhou, China
  • [ 3 ] [Fenu L.]Department of Civil Engineering, Environment Engineering, and Architecture, The University of Cagliari, Cagliari, Italy
  • [ 4 ] [Zordan T.]BOLINA, Consultant Engineering Ltd., Venice, Italy

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Source :

Bulletin of Earthquake Engineering

ISSN: 1570-761X

Year: 2025

3 . 8 0 0

JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 0

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