Resilience of engineering systems is related to their ability of absorbing both gradual and abrupt changes under exposure conditions and rapidly recover from disruptions. In this thesis, we develop a general stochastic formulation to model the recovery process and quantify system's resilience. In particular, we develop models for time-dependent capacity of a system and the imposed demand, under joint effects of recovery and shock deterioration processes. Using the developed models, a recovery curve is formulated in terms of system's reliability, functionality and work progress. Furthermore, we propose a novel approach for resilience analysis by defining measures to capture characteristics of recovery curves. The proposed approach makes a distinction in resilience of systems with different recovery patterns. A numerical example is provided to illustrate the application of the model.

Reducing hazard-induced disruptions to infrastructure functionality is cardinal to regional resilience. Specifically, effective strategies to enhance regional resilience require: (a) developing mathematical models for infrastructure recovery; (b) quantifying resilience associated with the developed recovery process; and (c) developing a computationally manageable approach for resilience optimization. This paper proposes a rigorous mathematical formulation to model recovery, quantify resilience, and optimize the resilience of large-scale infrastructure. Specifically, a multiscale model of the recovery process is proposed that significantly reduces the computational cost, while favoring practical and easily manageable recovery schedules. To quantify regional resilience, resilience metrics are proposed that capture the temporal and spatial variations of the recovery process. The paper then formulates a multiobjective optimization problem that aims to improve regional resilience in terms of the proposed metrics, while minimizing the recovery cost. Finally, the paper illustrates the proposed formulation by considering interdependent infrastructure in Shelby County, Tennessee, United States.

No abstract

No abstract

No abstract