A stochastic simulation based approach for seismic loss analysis and probability function computation

Estimation of losses in a structure due to future earthquakes is essential to reduce potential losses and assist recovery. A new stochastic simulation based approach for the estimation of seismic loss probability function is proposed with the adoption of stochastic ground motion models coupled with...

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Main Authors: Cheung, Sai Hung, Bansal, Sahil
Other Authors: School of Civil and Environmental Engineering
Format: Conference or Workshop Item
Language:English
Published: 2015
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Online Access:https://hdl.handle.net/10356/100187
http://hdl.handle.net/10220/25163
http://www.iitk.ac.in/nicee/wcee/article/WCEE2012_5765.pdf
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1001872019-12-06T20:18:04Z A stochastic simulation based approach for seismic loss analysis and probability function computation Cheung, Sai Hung Bansal, Sahil School of Civil and Environmental Engineering World Conference on Earthquake Engineering (15th : 2012 : Lisboa) DRNTU::Engineering::Civil engineering Estimation of losses in a structure due to future earthquakes is essential to reduce potential losses and assist recovery. A new stochastic simulation based approach for the estimation of seismic loss probability function is proposed with the adoption of stochastic ground motion models coupled with nonlinear stochastic dynamic models. This proposed approach allows for a more comprehensive characterization of the probability distribution of the loss including the tail parts due to combinations of scenarios which can lead to extreme and catastrophic consequences. Those combinations of scenarios do not need to be pre-specified but are automatically included during the proposed simulation process. Another contribution of the proposed approach is that it allows for the simultaneous consideration of multiple types of losses and the evaluation of the exceedance probability of these losses at different combinations of thresholds. Seismic loss probability function estimation problem essentially becomes a reliability estimation problem with multiple performance objectives at different threshold combinations. The effectiveness and efficiency of the proposed method are shown by an illustrative example involving a multi-storey inelastic building. Published version 2015-03-03T08:57:38Z 2019-12-06T20:18:04Z 2015-03-03T08:57:38Z 2019-12-06T20:18:04Z 2012 2012 Conference Paper Cheung, S.H., & Bansal, S. (2012). A stochastic simulation based approach for seismic loss analysis and probability function computation. In Proceedings of the 15th World Conference on Earthquake Engineering. Lisbon. https://hdl.handle.net/10356/100187 http://hdl.handle.net/10220/25163 http://www.iitk.ac.in/nicee/wcee/article/WCEE2012_5765.pdf en © 2012 International Association for Earthquake Engineering (IAEE). This paper was published in 15th World Conference on Earthquake Engineering and is made available as an electronic reprint (preprint) with permission of International Association for Earthquake Engineering (IAEE). The paper can be found at the following official URL: [http://www.iitk.ac.in/nicee/wcee/article/WCEE2012_5765.pdf].  One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. 10 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Civil engineering
spellingShingle DRNTU::Engineering::Civil engineering
Cheung, Sai Hung
Bansal, Sahil
A stochastic simulation based approach for seismic loss analysis and probability function computation
description Estimation of losses in a structure due to future earthquakes is essential to reduce potential losses and assist recovery. A new stochastic simulation based approach for the estimation of seismic loss probability function is proposed with the adoption of stochastic ground motion models coupled with nonlinear stochastic dynamic models. This proposed approach allows for a more comprehensive characterization of the probability distribution of the loss including the tail parts due to combinations of scenarios which can lead to extreme and catastrophic consequences. Those combinations of scenarios do not need to be pre-specified but are automatically included during the proposed simulation process. Another contribution of the proposed approach is that it allows for the simultaneous consideration of multiple types of losses and the evaluation of the exceedance probability of these losses at different combinations of thresholds. Seismic loss probability function estimation problem essentially becomes a reliability estimation problem with multiple performance objectives at different threshold combinations. The effectiveness and efficiency of the proposed method are shown by an illustrative example involving a multi-storey inelastic building.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
Cheung, Sai Hung
Bansal, Sahil
format Conference or Workshop Item
author Cheung, Sai Hung
Bansal, Sahil
author_sort Cheung, Sai Hung
title A stochastic simulation based approach for seismic loss analysis and probability function computation
title_short A stochastic simulation based approach for seismic loss analysis and probability function computation
title_full A stochastic simulation based approach for seismic loss analysis and probability function computation
title_fullStr A stochastic simulation based approach for seismic loss analysis and probability function computation
title_full_unstemmed A stochastic simulation based approach for seismic loss analysis and probability function computation
title_sort stochastic simulation based approach for seismic loss analysis and probability function computation
publishDate 2015
url https://hdl.handle.net/10356/100187
http://hdl.handle.net/10220/25163
http://www.iitk.ac.in/nicee/wcee/article/WCEE2012_5765.pdf
_version_ 1681048750501396480