Document Type



Doctor of Philosophy


Civil Engineering

First Adviser

Frangopol, Dan M.

Other advisers/committee members

Wilson, John L.; Yen, Ben T.; Pakzad, Shamim N.; Cheng, Liang


The presence of uncertainties in the structural design process requires the incorporation of system reliability and redundancy concepts in the design specifications. AASHTO Load and Resistance Factor Design specifications utilize a factor relating to redundancy from the load side in the strength limit state to account for system redundancy in the component design. However, the classification of the component redundancy level is very general and the evaluation of values for this factor is also very subjective. Moreover, this factor does not account for several parameters that have significant effects on the system redundancy. Therefore, there is room for further improvement in the classification of the redundancy level and quantification of the associated values. Structural safety is of paramount importance during the entire lifetime of a structure. Aggressive environmental conditions such as corrosion and / or extreme events such as earthquakes and scour can cause a reduced level of structural safety and functionality under uncertainties. For this reason, assessment of structural performance using probabilistic performance measures such as reliability, redundancy and risk is necessary to determine if maintenance actions need to be applied. Due to the financial constraints on the maintenance budget, optimization tools should be incorporated in the structural maintenance process for seeking the effective and economical solution. The accuracy of performance assessment affects the efficiency of decision making on the maintenance. To enhance the accuracy of the assessment results, objective data from structural health monitoring can be integrated with the prior information on resistances and / or load effects to obtain a better estimation. The main objective of this study is two-fold: firstly, to propose a redundancy factor considering the effects of several parameters to provide a rational reliability-based design of structural components; secondly, to develop general approaches for integrating the reliability- and risk-based performance indicators in the life-cycle management framework for structures. Redundancy factors for a wide range of systems consisting of different number of components are evaluated considering several correlation cases. An approach for evaluating time-variant reliability, redundancy, direct and indirect risk considering the effects of resistance deterioration, system modeling type and correlations among failure modes of components is proposed. A risk-based approach for optimum maintenance of bridges under traffic and earthquake loads is also developed. Furthermore, a methodology for assessing risk caused by partially or fully closure of bridge lanes due to traffic load and scour is proposed. Finally, approaches for incorporating structural heath monitoring data in the reliability and redundancy assessment of ship structures by updating one and two parameters using Bayesian method are developed. The proposed new definition of redundancy factor improves the classification of redundancy levels of structural components and quantification of the factor relating to redundancy used in the current AASHTO Load and Resistance Factor Design specifications by considering several parameters which have significant effects on structural redundancy. The direct, indirect and total risks caused by component failure based on the developed event-tree model can provide guidance on determining the maintenance priorities of bridge components. The proposed approaches for assessing the time-variant risk due to bridge failure / lanes closure under traffic and earthquake / scour hazards can be efficiently used for obtaining lifetime risk profiles based on which the optimum risk mitigation strategies can be determined through the proposed risk-based optimization process. Finally, the developed Bayesian updating approaches provide a way to make efficient use of the acquired SHM information to improve the accuracy in the performance assessment of naval ships and highway bridges.