UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Development of Bayesian Networks for the multi-hazard fragility assessment of bridge systems

Gehl, P; D'Ayala, D; (2016) Development of Bayesian Networks for the multi-hazard fragility assessment of bridge systems. Structural Safety , 60 pp. 37-46. 10.1016/j.strusafe.2016.01.006.

[img] Text
1-s2.0-S0167473016000229-main.pdf - Published version
Access restricted to UCL open access staff

Download (795kB)

Abstract

This article proposes an approach for the derivation of multi-hazard fragility functions, through the use of system reliability methods and Bayesian Networks. A bridge system is broken down into its constitutive components to isolate specific failure mechanisms and damage states at the component level. At the system level, the probability of occurrence of failure modes (i.e. various configurations of component damage states) is estimated thanks to a Bayesian analysis. These system fragility functions can then be directly related to harmonized functionality levels in order to get accurate predictions of downtime or traffic reduction. The applicability of the Bayesian Network formulation is compared to the matrix-based system reliability method, in terms of accuracy and computation time, while modeling strategies are proposed in the case of large systems with complex failure modes or multi-state components. Finally, the proposed approach is applied to a bridge system that is exposed to multiple hazard events (earthquakes, ground failures and floods): using the Bayesian framework, four functionality loss levels can be predicted with fragility surfaces that are expressed as a function of peak ground acceleration and flow discharge, taking into account multi-hazard interactions at the vulnerability level (i.e. cumulated damage events).

Type: Article
Title: Development of Bayesian Networks for the multi-hazard fragility assessment of bridge systems
DOI: 10.1016/j.strusafe.2016.01.006
Publisher version: http://dx.doi.org/10.1016/j.strusafe.2016.01.006
Language: English
Keywords: System reliability; Bayesian Network; Fragility analysis; Cascading events
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1482234
Downloads since deposit
2Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item