Accéder directement au contenu Accéder directement à la navigation
Nouvelle interface
Communication dans un congrès

Bayesian updating for rapid earthquake loss assessment of road network systems

Abstract : Within moments following an earthquake event, observations collected from the affected area can be used to define a picture of expected losses and to provide emergency services with accurate information. A Bayesian Network framework could be used to update the prior loss estimates based on ground-motion prediction equations and fragility curves, considering various field observations (i.e., evidence). The present study explores the applicability of approximate Bayesian inference, based on Monte-Carlo Markov-Chain sampling algorithms, to a real-world network of roads where expected loss metrics pertain to the accessibility between damaged areas and hospitals in the region. Observations are gathered either from free-field stations (for updating the ground-motion field) or from structure-mounted stations (for the updating of the damage states of infrastructure components). It is found that the proposed Bayesian approach is able to process a system comprising hundreds of components with reasonable accuracy, time and computation cost. Emergency managers may readily use the updated loss distributions to make informed decisions.
Liste complète des métadonnées

https://hal-brgm.archives-ouvertes.fr/hal-03748966
Contributeur : Pierre Gehl Connectez-vous pour contacter le contributeur
Soumis le : mercredi 10 août 2022 - 10:34:54
Dernière modification le : samedi 1 octobre 2022 - 03:24:47
Archivage à long terme le : : vendredi 11 novembre 2022 - 18:31:27

Fichier

3ECEES_paper_road_BN.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-03748966, version 1

Collections

Citation

Pierre Gehl, Rosemary Fayjaloun, Li Sun, Enrico Tubaldi, Caterina Negulescu, et al.. Bayesian updating for rapid earthquake loss assessment of road network systems. 3rd EUROPEAN CONFERENCE ON EARTHQUAKE ENGINEERING & SEISMOLOGY, Sep 2022, Bucarest, Romania. ⟨hal-03748966⟩

Partager

Métriques

Consultations de la notice

16

Téléchargements de fichiers

9