Structural Health Monitoring (SHM) is aimed at assessing and tracking structural conditions in time so that the occurrence of anomalies can be detected. In the last decades, the interest in SHM techniques has grown increasingly. The possibility of automating the process of data management (collection, acquisition, transmission, storage, and processing) allows obtaining real-time knowledge on the state of structures. This characteristic makes SHM very appealing to support the management of transportation infrastructures in the aftermath of disruptions. In these circumstances, managers are expected to ensure the safety of users and minimize the disturbance to the circulation of rescue vehicles and common drivers while minimizing human and economic losses. The prompt selection of the optimal emergency operation is generally based on the minimization of the expected consequences of the alternative actions (minimum risk), according to the available knowledge on the state of the structure. The availability of real-time data can provide insight into the actual state of the components and support the selection of the most efficient emergency management plan. Nevertheless, the installation and the management of the SHM system might be expensive. Therefore, owners and managers of bridges require tools to estimate the social and economic benefit associated with the implementation of monitoring strategies to optimize the allocation of economic resources. A suitable tool to compute the benefit of an SHM system before its adoption is the Value of Information (VoI) from Bayesian decision analysis. In general terms, the VoI represents the reduction in the expected management cost associated with a given data acquisition strategy. The VoI can be compared with the cost of the SHM system to decide if its installation is worth it. This PhD thesis investigates the use of the VoI from SHM in the context of the emergency management of bridges, after damaging events. The goal of the research is to provide decision-maker with a framework based on the VoI which they can apply to quantify the benefit associated with an SHM system which supports emergency management operations. Specifically, the developed framework can be used in decision-making related to the adoption of SHM systems to optimize the use of economic resources and ultimately enhance the safety of users. Two types of damaging events are considered which may produce emergency conditions, namely floods and earthquakes. Floods may generate scour at piers which is considered the major cause of the collapse of bridges worldwide. Earthquakes affect large areas producing large human and economic losses. Several case studies are addressed to demonstrate the feasibility of the framework developed.
Negli ultimi decenni, l'interesse per il monitoraggio strutturale è cresciuto notevolmente. I sistemi di monitoraggio hanno lo scopo di fornire informazioni sulle condizioni strutturali al fine di poter rilevare tempestivamente il verificarsi di anomalie. La possibilità di automatizzare il processo di gestione dei dati (raccolta, acquisizione, trasmissione, archiviazione ed elaborazione) consente di ottenere una conoscenza in tempo reale dello stato delle strutture. Questa caratteristica rende il monitoraggio strutturale particolarmente interessante nella gestione di infrastrutture di trasporto in situazioni di emergenza, come in seguito ad una catastrofe naturale. In queste circostanze, i gestori sono infatti tenuti a garantire la sicurezza degli utenti e ridurre al minimo il disturbo alla circolazione dei veicoli di soccorso e degli utenti comuni, minimizzando dunque le perdite umane ed economiche. Tuttavia, i sistemi di monitoraggio strutturale sono generalmente costosi. Pertanto, il loro costo deve essere confrontato - prima della loro adozione - con il relativo beneficio atteso, in modo tale da ottimizzare la gestione delle (generalmente limitate) risorse economiche. Il beneficio legato all’installazione di un sistema di monitoraggio è quantificato in questa tesi attraverso il valore dell’informazione, definito mediante l'analisi decisionale Bayesiana. Il valore dell’informazione può essere inteso come il prezzo massimo che un gestore dovrebbe pagare per un sistema di monitoraggio. L'obiettivo di questa tesi è fornire ai gestori di infrastrutture e, in particolare, di ponti stradali una metodologia per quantificare il beneficio associato ad un sistema di monitoraggio finalizzato al supporto della gestione di emergenze. Nello specifico, due tipologie di eventi catastrofici sono considerate, ovvero alluvioni e terremoti. Diversi casi di studio sono affrontati per dimostrare la fattibilità della metodologia sviluppata.
The value of structural health monitoring in emergency management
Pier Francesco, Giordano
2021
Abstract
Structural Health Monitoring (SHM) is aimed at assessing and tracking structural conditions in time so that the occurrence of anomalies can be detected. In the last decades, the interest in SHM techniques has grown increasingly. The possibility of automating the process of data management (collection, acquisition, transmission, storage, and processing) allows obtaining real-time knowledge on the state of structures. This characteristic makes SHM very appealing to support the management of transportation infrastructures in the aftermath of disruptions. In these circumstances, managers are expected to ensure the safety of users and minimize the disturbance to the circulation of rescue vehicles and common drivers while minimizing human and economic losses. The prompt selection of the optimal emergency operation is generally based on the minimization of the expected consequences of the alternative actions (minimum risk), according to the available knowledge on the state of the structure. The availability of real-time data can provide insight into the actual state of the components and support the selection of the most efficient emergency management plan. Nevertheless, the installation and the management of the SHM system might be expensive. Therefore, owners and managers of bridges require tools to estimate the social and economic benefit associated with the implementation of monitoring strategies to optimize the allocation of economic resources. A suitable tool to compute the benefit of an SHM system before its adoption is the Value of Information (VoI) from Bayesian decision analysis. In general terms, the VoI represents the reduction in the expected management cost associated with a given data acquisition strategy. The VoI can be compared with the cost of the SHM system to decide if its installation is worth it. This PhD thesis investigates the use of the VoI from SHM in the context of the emergency management of bridges, after damaging events. The goal of the research is to provide decision-maker with a framework based on the VoI which they can apply to quantify the benefit associated with an SHM system which supports emergency management operations. Specifically, the developed framework can be used in decision-making related to the adoption of SHM systems to optimize the use of economic resources and ultimately enhance the safety of users. Two types of damaging events are considered which may produce emergency conditions, namely floods and earthquakes. Floods may generate scour at piers which is considered the major cause of the collapse of bridges worldwide. Earthquakes affect large areas producing large human and economic losses. Several case studies are addressed to demonstrate the feasibility of the framework developed.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/203834
URN:NBN:IT:POLIMI-203834