posted on 2023-08-30, 17:19authored bySimona Miraglia, Michael H. Faber, Sebastian Thöns, Mark G. Stewart
Critical infrastructure systems such as energy provision and distribution systems, transport systems and the built environment in general are subject to and sensitive to deterioration processes. Structural Health Monitoring (SHM) strategies have been increasingly employed as a means to detect deterioration, facilitate timely and efficient interventions – and thereby to enhance resilience of critical infrastructure. However, in specific situations, it is generally not obvious if and to what degree different SHM strategies are efficient and sufficient for enhancing the resilience of critical infrastructure systems. In response to this challenge, the present contribution puts forwards a novel approach, taking basis in the concept of value of information analysis from Bayesian pre-posterior decision. Utilizing a principal model framework we show how the proposed approach is implemented with due consideration of the resilience governing characteristics and interdependencies between infrastructure systems, social/organisational systems, regulatory systems, ecological systems as well as anthropological and geological hazard systems.
History
Name of event
12th International Conference on Structural Safety & Reliability (ICOSSAR 2017)
Location
Vienna, Austria
Event start date
2017-08-06
Event finish date
2017-08-10
File version
Accepted version
Language
eng
Legacy posted date
2020-06-04
Legacy creation date
2020-06-04
Legacy Faculty/School/Department
ARCHIVED Faculty of Science & Technology (until September 2018)