Modeling of infrastructure deterioration and application to life-cycle analysis of engineering systems

Infrastructure systems worldwide are currently unable to sustain the demands they were originally intended to sustain. This is due to gradual deterioration processes and unexpected shock occurrences that have caused a decrease in their performance. It is crucial to develop methodologies for a proper assessment of the deterioration that has acted on engineering systems up to the present time, to obtain accurate estimates of their instantaneous reliability and accurately predict their future performance. It is one of the goals of Life-Cycle Analysis (LCA) to quantify the serviceability of engineering systems over time and the costs associated to possible closures for repair and replacement actions. Modeling the effects of adverse environmental conditions, of unexpected service loads, and of the occurrence of natural hazards is a key part of LCA, and the methodologies available in the literature are often imprecise and unable to provide a proper estimate of the associated uncertainties. The main goal of this dissertation is to propose a comprehensive framework for the LCA of engineering systems subject to deterioration. In the framework, the performance of the system is modeled as a function of its state variables, i.e. the physical characteristics that affect its performance such as geometry, boundary conditions, and material properties. The evolution of the state variables is investigated with accurate physics-based models that account for the effects of deterioration. To achieve this goal, we develop Stochastic Differential Equations (SDEs) formulations that are able to unify the effects of gradual deterioration and shock deterioration. The proposed models account for the interactions among different deterioration processes, as well as the interaction among the state variables (state-dependency). They can be adjusted and calibrated based on the output of inspection procedures such as Non-Destructive Testing (NDT) and Structural Health Monitoring (SHM). The dissertation details the available methods for calibration and proposes novel methods to incorporate the presence of shocks. Deterioration is then integrated with recovery, and both types of processes are incorporated into the vulnerability and resilience assessment of communities, focusing on the deterioration and time-varying serviceability of water networks. Finally, a framework is proposed to include the deterioration phenomena in the quantification of the Value of Information (VoI) associated with different inspection procedures, which can be used to evaluate whether monitoring or inspecting the system is beneficial in terms of economic costs and risk reduction.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Civil Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2022

Author dc:creator

• Iannacone, Leandro

Contributors dc:contributor

• Gardoni, Paolo
• DeVille, Lee
• Wang, Pingfeng
• Limongelli, Maria Pina
• Jia, Gaofeng

• Deterioration modeling
• life-cycle analysis
• physics-based models
• value of information
• stochastic analysis
• reliability
• stochastic differential equations
• structural health monitoring

Statement dc:rights

• Copyright 2022 Leandro Iannacone

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/115579

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F115579