Probabilistic models for life‐cycle performance of deteriorating structures: review and future directions

Abstract

In comparison with the well‐researched field of analysis and design of structural systems, the life‐cycle performance prediction of these systems under no maintenance as well as under various maintenance scenarios is far more complex, and is a rapidly emergent field in structural engineering. As structures become older and maintenance costs become higher, different agencies and administrations in charge of civil infrastructure systems are facing challenges related to the implementation of structure maintenance and management systems based on life‐cycle cost considerations. This article reviews the research to date related to probabilistic models for maintaining and optimizing the life‐cycle performance of deteriorating structures and formulates future directions in this field.

Reliability Acceptance Criteria for Deteriorating Elements of Structural Systems

“…While this applies equally to newly built and existing structures, the problem is particularly relevant for the latter, for which the cost of increasing the reliability is generally much higher (Melchers 2001). Extensive research has been carried out on probabilistic modeling of deterioration in structural systems, as reviewed by Frangopol et al (2004). Furthermore, methods for reliability analysis of deteriorating structural systems have been developed over the past two decades, including works by Mori and Ellingwood (1993), Li (1995), Ciampoli (1998), Estes and Frangopol (1999) and Stewart and Val (1999).…”

Risk- and Sustainability-Informed Decision Making for Structures in a Life-Cycle Context

“…Because of these uncertainties, it is imperative for structural engineers to accurately model and assess the structural performance and expected total cost within a probabilistic life-cycle context (Frangopol 2011).Furthermore, the effects of maintenance, repair, and rehabilitation on structural lifecycle performance must be quantified (Barone &Frangopol 2014b, Frangopol et al 2004, Sánchez-Silva et al 2016, Zhu & Frangopol 2012, 2013. Approaches for the life-cycle management of infrastructure systems involving reliability performance indicators consider uncertainties associated with loads and resistance, but are not able to account for the consequences incurred from structural failure.…”

Computational environment for modeling and enhancing community resilience: Introducing the center for risk-based community resilience planning

“…The past two decades have seen considerable research on time-dependent reliability of deteriorating structures (e.g., Mori and Ellingwood 1993;Frangopol, et al 2004). To model the life-cycle of a facility, including time to failure under random occurrences of loads or number of loads until failure occurs (e.g., operational and extreme loads), stochastic models of the deterioration processes and the dependencies between these processes will be included in NIST-CORE.…”