Date

2017

Document Type

Dissertation

Degree

Doctor of Philosophy

Department

Civil Engineering

First Adviser

Frangopol, Dan M.

Other advisers/committee members

Quiel, Spencer; Wilson, John L.; Pamukcu, Sibel; Akiyama, Mitsuyoshi

Abstract

The condition and performance of infrastructure systems is continuously deteriorating due to various environmental and mechanical stressors. There is a great need to implement optimal mitigation strategies that maintain structural performance within acceptable levels through the life-cycle of deteriorating civil infrastructure. In order to ensure adequate life-cycle performance, cost-efficient interventions must be implemented. This study presents computational frameworks that serve as decision support tools for bridge and ship managers, which ultimately allow them to make cost-, risk-, and sustainability-informed choices in the context of life-cycle engineering. Reliability, risk, sustainability, and utility-based performance indicators are examined and applied to civil and marine infrastructure systems subjected to a variety of hazards in order to determine optimal life-cycle management plans, balancing structural performance, cost of intervention, and available resources. The final product of the proposed decision support tools, optimal life-cycle management plans, describe which performance enhancing measure(s) should be implemented and when to intervene.Specifically, this study adds to existing probabilistic life-cycle management frameworks by integrating a novel utility-based sustainability metric in the life-cycle maintenance planning of civil and marine infrastructure. The effect of the risk attitude of the decision maker is examined in this study by including utility functions, which in this context, depict the relatively desirability of lifetime management plans to the decision maker. Additionally, lifetime functions such as hazard and availability are included as new performance indicators for bridges. Furthermore, the utility-based decision making framework developed is applied to a ship structure in order to determine optimal structural health monitoring plans under uncertainty. Optimal monitoring plans for the ship are determined by simultaneously maximizing availability and lifetime monitoring costs.

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