Influence of slope property variabilities on seismic sliding displacement analysis

In this study we quantitatively examined how the variabilities of slope property parameters influence the seismic slope displacement predictions based on two commonly used methods, namely the Newmark's rigid-block and the fully coupled deformable methods. A suite of 20 acceleration time-series...

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Main Authors: Du, Wenqi, Wang, Gang, Huang, Duruo
Other Authors: Institute of Catastrophe Risk Management (ICRM)
Format: Article
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/145054
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1450542020-12-09T07:24:37Z Influence of slope property variabilities on seismic sliding displacement analysis Du, Wenqi Wang, Gang Huang, Duruo Institute of Catastrophe Risk Management (ICRM) Science::Geology Seismic Slope Displacement Newmark In this study we quantitatively examined how the variabilities of slope property parameters influence the seismic slope displacement predictions based on two commonly used methods, namely the Newmark's rigid-block and the fully coupled deformable methods. A suite of 20 acceleration time-series were selected as input motions, and Monte Carlo simulations were performed to account for the influence of slope parameter variabilities. The results show that, for both Newmark's and fully coupled analyses, modeling the variability of the effective friction angle ϕ' significantly increases the geometric mean and standard deviation σlnD of the resultant displacements, while modeling the variability of the other slope parameters (i.e., soil cohesion c', thickness, and water table level) results in a similar estimate of and a slight increase of σlnD. The other sources of uncertainty exist in fully coupled analysis are the characterizations of the average shear wave velocity Vs, and the nonlinear soil properties. Modeling the variability in nonlinear soil properties yields a reduced estimate, and modeling the Vs variability causes a slight reduction of . Also, incorporating the variability of slope property parameters in fully coupled analysis consistently increases σlnD, in which the variation of ϕ' plays the predominant effect. This study thoroughly quantified the influence of slope property variabilities on the computed displacements, which could help engineers in addressing the uncertainty issue in seismic slope displacement analysis. 2020-12-09T07:24:37Z 2020-12-09T07:24:37Z 2018 Journal Article Du, W., Wang, G., & Huang, D. (2018). Influence of slope property variabilities on seismic sliding displacement analysis. Engineering Geology, 242, 121-129. doi:10.1016/j.enggeo.2018.06.003 0013-7952 https://hdl.handle.net/10356/145054 10.1016/j.enggeo.2018.06.003 242 121 129 en Engineering Geology © 2018 Elsevier B.V. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Science::Geology
Seismic Slope Displacement
Newmark
spellingShingle Science::Geology
Seismic Slope Displacement
Newmark
Du, Wenqi
Wang, Gang
Huang, Duruo
Influence of slope property variabilities on seismic sliding displacement analysis
description In this study we quantitatively examined how the variabilities of slope property parameters influence the seismic slope displacement predictions based on two commonly used methods, namely the Newmark's rigid-block and the fully coupled deformable methods. A suite of 20 acceleration time-series were selected as input motions, and Monte Carlo simulations were performed to account for the influence of slope parameter variabilities. The results show that, for both Newmark's and fully coupled analyses, modeling the variability of the effective friction angle ϕ' significantly increases the geometric mean and standard deviation σlnD of the resultant displacements, while modeling the variability of the other slope parameters (i.e., soil cohesion c', thickness, and water table level) results in a similar estimate of and a slight increase of σlnD. The other sources of uncertainty exist in fully coupled analysis are the characterizations of the average shear wave velocity Vs, and the nonlinear soil properties. Modeling the variability in nonlinear soil properties yields a reduced estimate, and modeling the Vs variability causes a slight reduction of . Also, incorporating the variability of slope property parameters in fully coupled analysis consistently increases σlnD, in which the variation of ϕ' plays the predominant effect. This study thoroughly quantified the influence of slope property variabilities on the computed displacements, which could help engineers in addressing the uncertainty issue in seismic slope displacement analysis.
author2 Institute of Catastrophe Risk Management (ICRM)
author_facet Institute of Catastrophe Risk Management (ICRM)
Du, Wenqi
Wang, Gang
Huang, Duruo
format Article
author Du, Wenqi
Wang, Gang
Huang, Duruo
author_sort Du, Wenqi
title Influence of slope property variabilities on seismic sliding displacement analysis
title_short Influence of slope property variabilities on seismic sliding displacement analysis
title_full Influence of slope property variabilities on seismic sliding displacement analysis
title_fullStr Influence of slope property variabilities on seismic sliding displacement analysis
title_full_unstemmed Influence of slope property variabilities on seismic sliding displacement analysis
title_sort influence of slope property variabilities on seismic sliding displacement analysis
publishDate 2020
url https://hdl.handle.net/10356/145054
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