Quantifying the value of monitoring for post-earthquake emergency management of bridges

Maria Pina Limongelli*, Piotr Omenzetter, Ufuk Yazgan, Serdar Soyoz

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

6 Citations (Scopus)


SHM systems are widely installed to increase the knowledge of the structural state and in present practice it is implicitly assumed that the information they bring is beneficial for the structural integrity management. This may not always be the case since inappropriate use of monitoring data, leading to wrong decisions, may be detrimental for the structural safety or cause economic losses. In this paper, a framework based on the concept of Value of Information from the pre-posterior Bayesian analysis is applied to forecast the utility associated to the implementation of an SHM system for the case of emergency management of road bridges subjected to seismic risk. An optimization problem is formulated to identify the most efficient decisions regarding traffic restrictions after an earthquake defined as those corresponding to the minimum associated cost and consequences. The choice of a proper structural performance indicator and the methods for the computation of the prior probabilities of damage, of the likelihood functions and of the costs associated with the different possible traffic restrictions are also briefly discussed.

Original languageEnglish
Title of host publicationIABSE Conference, Vancouver 2017
Subtitle of host publicationEngineering the Future - Report
PublisherInternational Association for Bridge and Structural Engineering (IABSE)
Number of pages8
ISBN (Electronic)9783857481536
Publication statusPublished - 2017
Event39th IABSE Symposium in Vancouver 2017: Engineering the Future - Vancouver, Canada
Duration: 21 Sept 201723 Sept 2017


Conference39th IABSE Symposium in Vancouver 2017: Engineering the Future


  • Emergency management
  • Performance indicators
  • Road bridges
  • Seismic risk
  • Structural health monitoring
  • Value of information


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