Accounting for time and state-dependent vulnerability of structural systems

• Main Authors: Rabonza, Maricar, Lallemant, David
• Other Authors: Asian School of the Environment
• Format: Conference or Workshop Item
• Language: English
• Published: 2021
• Subjects: Engineering::Civil engineering::Structures and design; Science::Mathematics::Applied mathematics::Simulation and modeling; Seismic Risk Analysis; Stochastic Modelling; Urban Risk Modelling
• Online Access: https://hdl.handle.net/10356/152834
• Institution: Nanyang Technological University

The typical process of engineering risk analysis assumes a static state of vulnerability through the lifespan of the structure. However, many civil engineering systems change states over time causing significant impact on their vulnerability. Such dynamic changes may involve an increase in vulnerability driven by deterioration processes (e.g. corrosion, fatigue, creep, hazard-induced damage, etc.), or a decrease in vulnerability driven by strengthening interventions (e.g. retrofitting, maintenance, building replacement, etc.). Accounting for these dynamics is critical to properly understand hazardrelated risk of civil engineering systems over their lifespan. This paper presents a stochastic framework for accounting for time and state dependent vulnerability in risk analysis of civil engineering systems. Time-homogeneous Markov chains are used to model various state change processes, and integrated within the risk analysis framework in closed-form expressions. Several applications are demonstrated: (1) quantifying risk of structurally deteriorating buildings and the risk reduction impact of maintenance, (2) urban-scale seismic retrofitting policies based on various retrofit rates, and (3) impact of varying rates of building replacement to higher design grade. These demonstrate the importance of accounting for time dependent state change as a significant factor in the life-span vulnerability of the built environment. The study further provides a framework to study and compare various risk reduction policies.