The Benefit of Informed Risk-Based Management of Civil Infrastructures

Author:

Giordano Pier FrancescoORCID,Limongelli Maria PinaORCID

Abstract

One of the most interesting applications of Structural Health Monitoring (SHM) is the possibility of providing real-time information on the conditions of civil infrastructures during and following disastrous events, thus supporting decision-makers in prompt emergency operations. The Bayesian decision theory provides a rigorous framework to quantify the benefit of SHM through the Value of Information (VoI) accounting for different sources of uncertainties. This decision theory is based on utility considerations, or, in other words, it is based on risk. Instead, decision-making in emergency management is often based on engineering judgment and heuristic approaches. The goal of this paper is to investigate the impact of different decision scenarios on the VoI. To this aim, a general framework to quantify the benefit of SHM information in emergency management is applied to different decision scenarios concerning bridges under scour and seismic hazards. Results indicate that the considered decision scenario might tremendously affect the results of a VoI analysis. Specifically, the benefit of SHM information could be underestimated when considering non-realistic scenarios, e.g., those based on risk-based decision-making, which are not adopted in practice. Besides, SHM information is particularly valuable when it prevents the selection of suboptimal emergency management actions.

Funder

Italian Civil Protection Department

Publisher

MDPI AG

Subject

Computer Science Applications,Geotechnical Engineering and Engineering Geology,General Materials Science,Building and Construction,Civil and Structural Engineering

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Value of information analysis accounting for data quality;Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2023;2023-04-18

2. Value of Seismic Structural Health Monitoring Information for Management of Civil Structures Under Different Prior Knowledge Scenarios;Lecture Notes in Civil Engineering;2023

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