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Risk-Based Multiobjective Optimal Seismic Design for RC Piers Using the Response Surface Method and NSGA-II

Autor(en): ORCID




Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Advances in Civil Engineering, , v. 2021
Seite(n): 1-11
DOI: 10.1155/2021/8852203
Abstrakt:

In this paper, a risk-based multiobjective optimal seismic design method for reinforced concrete (RC) piers is proposed. This method is used to determine the size and reinforcement ratios of piers to minimize the seismic risk of bridge systems and the construction cost of piers. The Pacific Earthquake Engineering Research- (PEER-) based probabilistic seismic risk assessment approach and the response surface method (RSM) are adopted to develop the seismic risk response surface model, which represents the relationship between the design parameters of piers and the seismic risk of bridge systems. The Pareto optimal solutions of piers are determined by applying an improved version of the nondominated sorting genetic algorithm (NSGA-II). As a case study, the proposed optimal seismic design method is applied to a continuous concrete box girder bridge. The optimal design schemes of piers according to two strategies are determined from the Pareto optimal solutions. The results show that the seismic risk response surface model can be used to accurately describe the relationship between the design parameters of piers and the seismic risk of bridge systems. The case study demonstrates the effectiveness of the proposed optimal seismic design method. The analysis of the Pareto optimal solutions allows designers to more rationally conduct the seismic design of piers.

Copyright: © 2021 Sicong Hu et al.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10602174
  • Veröffentlicht am:
    17.04.2021
  • Geändert am:
    02.06.2021
 
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