Framework for Incorporating Probabilistic Building Performance in the Assessment of Community Seismic Resilience
Publication: Journal of Structural Engineering
Volume 142, Issue 8
Abstract
A framework is presented for incorporating probabilistic building performance limit states in the assessment of community resilience to earthquakes. The limit states are defined on the basis of their implications to postearthquake functionality and recovery. They include damage triggering inspection, occupiable damage with loss of functionality, unoccupiable damage, irreparable damage, and collapse. Fragility curves are developed linking earthquake ground motion intensity to the probability of exceedance for each of the limit states. A characteristic recovery path is defined for each limit state on the basis of discrete functioning states, the time spent within each state, and the level of functionality associated with each state. A building recovery function is computed accounting for the uncertainty in the occurrence of each recovery path and its associated limit state. The outcome is a probabilistic assessment of recovery of functionality at the building level for a given ground motion intensity. The effects of externalities and other socioeconomic factors on building-level recovery and ways to incorporate these in the framework are discussed. A case study is presented to demonstrate the application of the proposed framework to model the postearthquake recovery of the shelter-in-place housing capacity of an inventory of residential buildings. This type of assessment can inform planning and policy decisions to manage the earthquake risk to residential housing capacity of communities.
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Acknowledgments
The authors would like to thank the anonymous reviewers of this paper for their feedback. This research was partially supported by the John Blume Earthquake Engineering Center, the Engineering Diversity Fellowship, and the Diversifying Academia Recruiting Excellence (DARE) Fellowship at Stanford University. The computational models run for this study used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation Grant No. OCI-1053575 (Allocation: TG-BCS130008).
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Information & Authors
Information
Published In
Journal of Structural Engineering
Volume 142 • Issue 8 • August 2016
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Nov 6, 2013
Accepted: Mar 12, 2015
Published online: May 21, 2015
Discussion open until: Oct 21, 2015
Published in print: Aug 1, 2016
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