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Research on Construction Risk Assessment of Long-Span Cantilever Casting Concrete Arch Bridges Based on Triangular Fuzzy Theory and Bayesian Networks

Auteur(s):
ORCID




Médium: article de revue
Langue(s): anglais
Publié dans: Buildings, , n. 9, v. 14
Page(s): 2627
DOI: 10.3390/buildings14092627
Abstrait:

Considering the complex construction processes involved, there are significant risks during the construction of long-span cantilever casting arch bridges. In this study, a risk assessment method for the construction process of cantilever casting concrete arch bridges was developed. The compositional elements and characteristics of safety risks in the construction of cantilever casting concrete arch bridges were clarified, and a safety risk source list that includes seven major risk sources and thirty-three minor risk sources was formed. Then, a Bayesian model for the risk analysis of cantilever casting concrete arch bridge construction was established, and a method was proposed to determine the prior and posterior probabilities of the Bayesian network using triangular fuzzy numbers. This method fully utilizes the experience of experts while avoiding the subjectivity of expert opinions. A cantilever casting concrete open spandrel arch bridge (Bridge A) with a total span length of 287 m was taken as an example, and a safety risk assessment was conducted during its construction process. The calculation results show that the construction safety risk level of Bridge A was level III. This engineering application verified the feasibility of determining key node parameters of the Bayesian network using triangular fuzzy numbers.

Copyright: © 2024 by the authors; licensee MDPI, Basel, Switzerland.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
    sur cette fiche
  • Reference-ID
    10795787
  • Publié(e) le:
    01.09.2024
  • Modifié(e) le:
    01.09.2024
 
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