Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/152834
Title: Accounting for time and state-dependent vulnerability of structural systems
Authors: Rabonza, Maricar
Lallemant, David
Keywords: Engineering::Civil engineering::Structures and design
Science::Mathematics::Applied mathematics::Simulation and modeling
Issue Date: 2019
Source: Rabonza, M. & Lallemant, D. (2019). Accounting for time and state-dependent vulnerability of structural systems. 13th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP13), 2298-2305. https://dx.doi.org/10.22725/ICASP13.465
Project: NRF–NRFF2018–06
Abstract: 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.
URI: hdl.handle.net/10371/153549
https://hdl.handle.net/10356/152834
ISBN: 979-11-967125-0-1
DOI: 10.22725/ICASP13.465
Rights: © 2019 The Author(s). All rights reserved. This paper was published in Proceedings of 13th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP13) and is made available with permission of The Author(s).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:ASE Conference Papers

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