Stochastic post-disaster functionality recovery of community building portfolios I: Modeling. (November 2017)

• Record Type: Journal Article
• Authors: Lin, Peihui; Wang, Naiyu
• Is Part Of: Structural safety. Volume 69(2017)
• Page Start: 96
• Page End: 105
• Publication Date: 2017-11
• Subjects: Recovery modeling -- Building portfolio -- Functionality state -- Building restoration -- Continuous time Markov Chain -- Community resilience; Structural stability -- Periodicals; Safety factor in engineering -- Periodicals; Reliability (Engineering) -- Periodicals; Constructions -- Stabilité -- Périodiques; Coefficient de sécurité en ingénierie -- Périodiques; Fiabilité -- Périodiques; 620.86
• DOI: 10.1016/j.strusafe.2017.05.002
• Languages: English
• ISSNs: 0167-4730

Abstract

Highlights: A simulation-based community building portfolio recovery model is proposed. Building-level restoration is model as a discrete state, continuous time Markov Chain. Portfolio-level recovery is formulated as a random field in both spatial and temporal dimensions. Uncertainties in various sources are propagated to obtain probabilistic recovery metrics. Abstract: Understanding the process of post-disaster recovery is a critical step toward assessing and achieving community resilience. However, the recovery process of a community building portfolio as a spatially distributed system is intrinsically complex and highly uncertain, and is conditional on the resourcefulness and social-economic characteristics of the community as well as the various decisions made by numerous community stakeholders and building owners at different phases of the recovery. We propose a simulation-based building portfolio recovery model (BPRM) to predict the functionality recovery time and recovery trajectory of a community building portfolio following natural scenario hazard events, in two steps: (1) modeling individual building-level restoration as a discrete state, continuous time Markov Chain (CTMC); and (2) modeling building portfolio-level recovery through aggregating the CTMC restoration processes of individual buildings across the domain of the community and over the entire recovery time horizon. We propagate uncertainties associated with the recovery process in a consistent manner in order to quantify portfolio recovery metrics probabilistically. The proposed building portfolio recovery model is intended to support risk-informed community resilience planning and hazard mitigation.