Toward multivariate fragility functions for seismic damage and loss estimation of high-rise buildings
Data-driven models for seismic damage and loss assessment of buildings have become more common in recent years due to the availability of large repositories of recorded and synthetic ground motions coupled with structural response simulation data. This paper explores the benefits of using bivariate...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2024
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| Online Access: | https://hdl.handle.net/10356/174161 |
| _version_ | 1811697501620666368 |
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| author | Kourehpaz, Pouria Hutt, Carlos Molina Lallemant, David |
| author2 | Asian School of the Environment |
| author_facet | Asian School of the Environment Kourehpaz, Pouria Hutt, Carlos Molina Lallemant, David |
| author_sort | Kourehpaz, Pouria |
| collection | NTU |
| description | Data-driven models for seismic damage and loss assessment of buildings have become more common in recent years due to the availability of large repositories of recorded and synthetic ground motions coupled with structural response simulation data. This paper explores the benefits of using bivariate and multivariate fragility functions to estimate earthquake-induced damage and economic loss in high-rise buildings. The dataset used in this study encompasses 15,000 simulations of modern high-rise reinforced concrete shear wall buildings ranging from eight to 24 stories which are subjected to ground motion records at five different intensity levels. The proposed functions are conditioned on average spectral accelerations and ground motion significant duration. The results indicate that bivariate fragility functions improve damage state prediction success (Brier score) by 16%, and multivariate fragility functions by 24% relative to conventional univariate functions (standard of practice). To develop multivariate functions, nominal and ordinal probit regression models are fit to the dataset. While both models yield satisfactory predictive performance, ordinal functions can lead to a 15% reduction in misclassified collapse instances, that is, the minority class. Univariate functions tend to overestimate seismic losses at lower intensity levels while underestimating them at higher intensities. These loss estimates are significantly improved when bivariate or multivariate building fragility functions are used. Given the increase in the use of physics-based ground motion simulations and/or multi-variate ground motion models, from which multiple intensity measures can be extracted, a shift toward a more complex representation of fragility functions, for example, multivariate curves, is necessary and inevitable. The proposed functions are used to evaluate the performance of a portfolio of modern high-rise reinforced concrete shear wall buildings at four sites across the Seattle, Washington metropolitan area under a potential magnitude-9 Cascadia subduction zone earthquake scenario. The results indicate that the proposed functions can be beneficial in enhancing damage state predictions and loss estimates at a regional scale. |
| first_indexed | 2024-10-01T07:56:16Z |
| format | Journal Article |
| id | ntu-10356/174161 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:56:16Z |
| publishDate | 2024 |
| record_format | dspace |
| spelling | ntu-10356/1741612024-03-18T15:30:56Z Toward multivariate fragility functions for seismic damage and loss estimation of high-rise buildings Kourehpaz, Pouria Hutt, Carlos Molina Lallemant, David Asian School of the Environment Earth Observatory of Singapore Earth and Environmental Sciences Collapse misclassification High-rise building Data-driven models for seismic damage and loss assessment of buildings have become more common in recent years due to the availability of large repositories of recorded and synthetic ground motions coupled with structural response simulation data. This paper explores the benefits of using bivariate and multivariate fragility functions to estimate earthquake-induced damage and economic loss in high-rise buildings. The dataset used in this study encompasses 15,000 simulations of modern high-rise reinforced concrete shear wall buildings ranging from eight to 24 stories which are subjected to ground motion records at five different intensity levels. The proposed functions are conditioned on average spectral accelerations and ground motion significant duration. The results indicate that bivariate fragility functions improve damage state prediction success (Brier score) by 16%, and multivariate fragility functions by 24% relative to conventional univariate functions (standard of practice). To develop multivariate functions, nominal and ordinal probit regression models are fit to the dataset. While both models yield satisfactory predictive performance, ordinal functions can lead to a 15% reduction in misclassified collapse instances, that is, the minority class. Univariate functions tend to overestimate seismic losses at lower intensity levels while underestimating them at higher intensities. These loss estimates are significantly improved when bivariate or multivariate building fragility functions are used. Given the increase in the use of physics-based ground motion simulations and/or multi-variate ground motion models, from which multiple intensity measures can be extracted, a shift toward a more complex representation of fragility functions, for example, multivariate curves, is necessary and inevitable. The proposed functions are used to evaluate the performance of a portfolio of modern high-rise reinforced concrete shear wall buildings at four sites across the Seattle, Washington metropolitan area under a potential magnitude-9 Cascadia subduction zone earthquake scenario. The results indicate that the proposed functions can be beneficial in enhancing damage state predictions and loss estimates at a regional scale. National Research Foundation (NRF) Published version The authors would also like to thank the Mitacs Globalink program and AI Singapore for their financial support to facilitate the research collaboration between the University of British Columbia and the Nanyang Technological University. This research was funded by Canada’s Natural Sciences and Engineering Research Council under Discovery. RGPIN-2019-04599. Partial funding support was also provided by the National Research Foundation, Singapore under the NRF-NRFF2018-06 award. 2024-03-18T04:29:37Z 2024-03-18T04:29:37Z 2023 Journal Article Kourehpaz, P., Hutt, C. M. & Lallemant, D. (2023). Toward multivariate fragility functions for seismic damage and loss estimation of high-rise buildings. Earthquake Engineering and Structural Dynamics, 52(13), 4164-4182. https://dx.doi.org/10.1002/eqe.3993 0098-8847 https://hdl.handle.net/10356/174161 10.1002/eqe.3993 2-s2.0-85168671501 13 52 4164 4182 en NRF-NRFF2018-06 Earthquake Engineering and Structural Dynamics © 2023 The Authors. Earthquake Engineering & Structural Dynamics published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. application/pdf |
| spellingShingle | Earth and Environmental Sciences Collapse misclassification High-rise building Kourehpaz, Pouria Hutt, Carlos Molina Lallemant, David Toward multivariate fragility functions for seismic damage and loss estimation of high-rise buildings |
| title | Toward multivariate fragility functions for seismic damage and loss estimation of high-rise buildings |
| title_full | Toward multivariate fragility functions for seismic damage and loss estimation of high-rise buildings |
| title_fullStr | Toward multivariate fragility functions for seismic damage and loss estimation of high-rise buildings |
| title_full_unstemmed | Toward multivariate fragility functions for seismic damage and loss estimation of high-rise buildings |
| title_short | Toward multivariate fragility functions for seismic damage and loss estimation of high-rise buildings |
| title_sort | toward multivariate fragility functions for seismic damage and loss estimation of high rise buildings |
| topic | Earth and Environmental Sciences Collapse misclassification High-rise building |
| url | https://hdl.handle.net/10356/174161 |
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