Abstract
This paper uses probabilistic models and minimization of certain risk measures to expose risk aversion and optimal retrofit strategies for an existing building portfolio. A case study is presented addressing 622 buildings on the Vancouver campus of the University of British Columbia, Canada, a location subjected to multiple sources of seismicity. An array of probabilistic models is used to predict ground-motion intensities, structural responses, and consequent cost of damage due to earthquakes in the next 50 years. A key result is the exceedance probability curve for repair costs discounted to present value. A model is also postulated for the cost of retrofit, i.e., strengthening each building. Because both costs depend on the level of retrofit, the total expected cost and other properly defined risk measures are convex functions of the retrofit level. As a result, the conducted optimization analyses yield unique optimal retrofit levels. A computer program is employed to coordinate the multimodel analyses, which consist of 281 random variables in 4,389 instances of 14 different model types. The analyses reveal substantial risk aversion in the current designs when the direct cost of damage is considered. If indirect costs eight times the direct cost of damage are included, then current designs are optimal from an expected cost perspective.
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Acknowledgments
The financial support from the Natural Science and Engineering Research Council of Canada (NSERC) through the Strategic Project Grant No. 336498-06 is gratefully acknowledged. The first author thanks Grant No. 96013800 from Iran National Science Foundation (INSF).
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Information & Authors
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Published In
Journal of Structural Engineering
Volume 145 • Issue 2 • February 2019
Copyright
©2018 American Society of Civil Engineers.
History
Received: Jul 25, 2017
Accepted: Jul 24, 2018
Published online: Nov 26, 2018
Published in print: Feb 1, 2019
Discussion open until: Apr 26, 2019
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