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Title: Exploring Structural Health Monitoring Value of Information based on Remaining Useful Life Extension Potential
Authors: Valkonen, Antti
Advisors: Glisic, Branko
Contributors: Civil and Environmental Engineering Department
Keywords: Bridges
Structural Health Monitoring
Survival Analysis
Value of Information
Subjects: Civil engineering
Issue Date: 2023
Publisher: Princeton, NJ : Princeton University
Abstract: Structural Health Monitoring (SHM) is an overarching term for methods and techniques used to gain accurate, in-time information about the condition and performance of civil engineering structures. SHM allows moving from traditional maintenance and inspection approaches into a predictive approach where data and lifecycle modeling is used to optimize operations and maintenance decisions. Even though SHM is an important technology in modern asset management, a proliferation of industrial applications is yet to be seen. One of the reasons for the lack of industrial applications is the uncertainty of the return on investment offered by SHM systems. Currently, there is no systematic methodology to quantify the benefits of SHM system deployment. Widespread utilization of SHM requires development of valuation methods so decision-makers can evaluate potential investments into monitoring systems. This dissertation advances SHM Value of Information (VoI) valuation literature by creating a framework for evaluating the VoI generated by postponing the replacement of bridge decks using SHM. Postponing the replacement of structures will generate savings from avoiding the opportunity cost of having to commit funds for the replacement project prematurely. Evaluating the potential value requires the ability to estimate the Remaining Useful Life (RUL) distribution of structures and the risk preference of the decision-makers, which is tied to the opportunity cost. To Understand the RUL distribution, a Neural Network -based survival model for bridge deck deterioration is created. To understand decision-maker risk preferences a survey tool is created. The main findings of this dissertation are 1) Traditional Proportional Hazards Assumption does not necessarily hold for new or rehabilitated bridges in their early years. 2) Bridge population heterogeneity has a limiting effect on survival model predictive performance 3) implementation of SHM influences decision-maker risk preferences 4) VoI potential based on postponing bridge deck replacement is large.
Type of Material: Academic dissertations (Ph.D.)
Language: en
Appears in Collections:Civil and Environmental Engineering

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