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Correlated damage probabilities of bridges in seismic risk assessment of transportation networks: Case study, Tehran

  • Shahin Borzoo (Lifeline Earthquake Engineering Department, International Institute of Earthquake Engineering and Seismology) ;
  • Morteza Bastami (Lifeline Earthquake Engineering Department, International Institute of Earthquake Engineering and Seismology) ;
  • Afshin Fallah (Department of Statistics, Imam Khomeini International University) ;
  • Alireza Garakaninezhad (Department of Civil Engineering, Faculty of Engineering, University of Jiroft) ;
  • Morteza Abbasnejadfard (Lifeline Earthquake Engineering Department, International Institute of Earthquake Engineering and Seismology)
  • 투고 : 2023.02.12
  • 심사 : 2023.12.18
  • 발행 : 2024.02.25

초록

This paper proposes a logistic multinomial regression approach to model the spatial cross-correlation of damage probabilities among different damage states in an expanded transportation network. Utilizing Bayesian theory and the multinomial logistic model, we analyze the damage states and probabilities of bridges while incorporating damage correlation. This correlation is considered both between bridges in a network and within each bridge's damage states. The correlation model of damage probabilities is applied to the seismic assessment of a portion of Tehran's transportation network, encompassing 26 bridges. Additionally, we introduce extra daily traffic time (EDTT) as an operational parameter of the transportation network and employ the shortest path algorithm to determine the path between two nodes. Our results demonstrate that incorporating the correlation of damage probabilities reduces the travel time of the selected network. The average decrease in travel time for the correlated case compared to the uncorrelated case, using two selected EDTT models, is 53% and 71%, respectively.

키워드

과제정보

The authors would like to acknowledge the International Institute of Earthquake Engineering and Seismology (IIEES) for providing research documents and financial support.

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