Probabilistic stability analyses of multi-stage soil slopes by bivariate random fields and finite element methods
This study aimed to investigate the stability of multi-stage drained and undrained slopes considering the spatial variability in soil properties. A bivariate random field was adopted to characterize the spatial randomness in soil strength parameters of each stage of soil slopes. The random field was...
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| Veröffentlicht in: | Computers and geotechnics 2020-06, Vol.122, p.103529, Article 103529 |
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| creator | Wang, Man-Yu Liu, Yong Ding, Ya-Nan Yi, Bao-Long |
| description | This study aimed to investigate the stability of multi-stage drained and undrained slopes considering the spatial variability in soil properties. A bivariate random field was adopted to characterize the spatial randomness in soil strength parameters of each stage of soil slopes. The random field was then incorporated with the finite element method to obtain the factor of safety (FS) and evaluate the slope failure mechanism. Monte Carlo simulations were conducted for slopes with random soils, resulting in histograms of the FS. The results indicated that around 65%–75% cases of a random slope under the drained condition had an FS being less than that of a uniform slope, and this comparison value reached about 92.6% under the undrained condition. As such, the deterministic analysis of a multi-stage slope may result in an overestimated value of the FS. Moreover, the influence of cross-correlation between cohesive strength and friction angle on the stability of drained slopes was also investigated. The findings demonstrated that the failure probability of multi-stage slope increases as the correlation coefficient increases. |
| doi_str_mv | 10.1016/j.compgeo.2020.103529 |
| format | Article |
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A bivariate random field was adopted to characterize the spatial randomness in soil strength parameters of each stage of soil slopes. The random field was then incorporated with the finite element method to obtain the factor of safety (FS) and evaluate the slope failure mechanism. Monte Carlo simulations were conducted for slopes with random soils, resulting in histograms of the FS. The results indicated that around 65%–75% cases of a random slope under the drained condition had an FS being less than that of a uniform slope, and this comparison value reached about 92.6% under the undrained condition. As such, the deterministic analysis of a multi-stage slope may result in an overestimated value of the FS. Moreover, the influence of cross-correlation between cohesive strength and friction angle on the stability of drained slopes was also investigated. The findings demonstrated that the failure probability of multi-stage slope increases as the correlation coefficient increases.</description><identifier>ISSN: 0266-352X</identifier><identifier>EISSN: 1873-7633</identifier><identifier>DOI: 10.1016/j.compgeo.2020.103529</identifier><language>eng</language><publisher>New York: Elsevier Ltd</publisher><subject>Bivariate analysis ; Computer simulation ; Correlation coefficient ; Correlation coefficients ; Failure mechanism ; Failure mechanisms ; Fields (mathematics) ; Finite element method ; Histograms ; Monte Carlo simulation ; Multi-stage slope ; Probability theory ; Random finite element method ; Slope ; Slope stability ; Slopes ; Soil analysis ; Soil properties ; Soil stability ; Soil strength ; Soils ; Spatial variability ; Spatial variations ; Stability analysis ; Statistical analysis ; Statistical methods</subject><ispartof>Computers and geotechnics, 2020-06, Vol.122, p.103529, Article 103529</ispartof><rights>2020 Elsevier Ltd</rights><rights>Copyright Elsevier BV Jun 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c337t-e2674d6b3133c501b674d195a0bbc251d6b7313ae32b4865e087f062b31bcc0a3</citedby><cites>FETCH-LOGICAL-c337t-e2674d6b3133c501b674d195a0bbc251d6b7313ae32b4865e087f062b31bcc0a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.compgeo.2020.103529$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Wang, Man-Yu</creatorcontrib><creatorcontrib>Liu, Yong</creatorcontrib><creatorcontrib>Ding, Ya-Nan</creatorcontrib><creatorcontrib>Yi, Bao-Long</creatorcontrib><title>Probabilistic stability analyses of multi-stage soil slopes by bivariate random fields and finite element methods</title><title>Computers and geotechnics</title><description>This study aimed to investigate the stability of multi-stage drained and undrained slopes considering the spatial variability in soil properties. A bivariate random field was adopted to characterize the spatial randomness in soil strength parameters of each stage of soil slopes. The random field was then incorporated with the finite element method to obtain the factor of safety (FS) and evaluate the slope failure mechanism. Monte Carlo simulations were conducted for slopes with random soils, resulting in histograms of the FS. The results indicated that around 65%–75% cases of a random slope under the drained condition had an FS being less than that of a uniform slope, and this comparison value reached about 92.6% under the undrained condition. As such, the deterministic analysis of a multi-stage slope may result in an overestimated value of the FS. Moreover, the influence of cross-correlation between cohesive strength and friction angle on the stability of drained slopes was also investigated. The findings demonstrated that the failure probability of multi-stage slope increases as the correlation coefficient increases.</description><subject>Bivariate analysis</subject><subject>Computer simulation</subject><subject>Correlation coefficient</subject><subject>Correlation coefficients</subject><subject>Failure mechanism</subject><subject>Failure mechanisms</subject><subject>Fields (mathematics)</subject><subject>Finite element method</subject><subject>Histograms</subject><subject>Monte Carlo simulation</subject><subject>Multi-stage slope</subject><subject>Probability theory</subject><subject>Random finite element method</subject><subject>Slope</subject><subject>Slope stability</subject><subject>Slopes</subject><subject>Soil analysis</subject><subject>Soil properties</subject><subject>Soil stability</subject><subject>Soil strength</subject><subject>Soils</subject><subject>Spatial variability</subject><subject>Spatial variations</subject><subject>Stability analysis</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><issn>0266-352X</issn><issn>1873-7633</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNqFkE1LAzEQhoMoWKs_QQh43pqP3Wx7Eil-QUEPCt5Ckp2tKdlNm6SF_fdmbe-eMplnnoF5EbqlZEYJFfebmfHddg1-xggbe7xiizM0ofOaF7Xg_BxNCBOiyP3vS3QV44ZkbzFfTNDuI3ittHU2JmtwTH91GrDqlRsiROxb3O1dskVma8DRW4ej89uM9IC1PahgVQIcVN_4DrcWXBOz3uSytxmAgw76hDtIP76J1-iiVS7Czemdoq_np8_la7F6f3lbPq4Kw3mdCmCiLhuhOeXcVITq8UsXlSJaG1bRjOrMFHCmy7mogMzrlgiWBW0MUXyK7o57t8Hv9hCT3Ph9yFdFycqSi7JirM5T1XHKBB9jgFZug-1UGCQlckxXbuQpXTmmK4_pZu_h6EE-4WAhyGgs9AYaG8Ak2Xj7z4Zf1pCHTQ</recordid><startdate>202006</startdate><enddate>202006</enddate><creator>Wang, Man-Yu</creator><creator>Liu, Yong</creator><creator>Ding, Ya-Nan</creator><creator>Yi, Bao-Long</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H96</scope><scope>JQ2</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>202006</creationdate><title>Probabilistic stability analyses of multi-stage soil slopes by bivariate random fields and finite element methods</title><author>Wang, Man-Yu ; Liu, Yong ; Ding, Ya-Nan ; Yi, Bao-Long</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c337t-e2674d6b3133c501b674d195a0bbc251d6b7313ae32b4865e087f062b31bcc0a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Bivariate analysis</topic><topic>Computer simulation</topic><topic>Correlation coefficient</topic><topic>Correlation coefficients</topic><topic>Failure mechanism</topic><topic>Failure mechanisms</topic><topic>Fields (mathematics)</topic><topic>Finite element method</topic><topic>Histograms</topic><topic>Monte Carlo simulation</topic><topic>Multi-stage slope</topic><topic>Probability theory</topic><topic>Random finite element method</topic><topic>Slope</topic><topic>Slope stability</topic><topic>Slopes</topic><topic>Soil analysis</topic><topic>Soil properties</topic><topic>Soil stability</topic><topic>Soil strength</topic><topic>Soils</topic><topic>Spatial variability</topic><topic>Spatial variations</topic><topic>Stability analysis</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Man-Yu</creatorcontrib><creatorcontrib>Liu, Yong</creatorcontrib><creatorcontrib>Ding, Ya-Nan</creatorcontrib><creatorcontrib>Yi, Bao-Long</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computers and geotechnics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Man-Yu</au><au>Liu, Yong</au><au>Ding, Ya-Nan</au><au>Yi, Bao-Long</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Probabilistic stability analyses of multi-stage soil slopes by bivariate random fields and finite element methods</atitle><jtitle>Computers and geotechnics</jtitle><date>2020-06</date><risdate>2020</risdate><volume>122</volume><spage>103529</spage><pages>103529-</pages><artnum>103529</artnum><issn>0266-352X</issn><eissn>1873-7633</eissn><abstract>This study aimed to investigate the stability of multi-stage drained and undrained slopes considering the spatial variability in soil properties. A bivariate random field was adopted to characterize the spatial randomness in soil strength parameters of each stage of soil slopes. The random field was then incorporated with the finite element method to obtain the factor of safety (FS) and evaluate the slope failure mechanism. Monte Carlo simulations were conducted for slopes with random soils, resulting in histograms of the FS. The results indicated that around 65%–75% cases of a random slope under the drained condition had an FS being less than that of a uniform slope, and this comparison value reached about 92.6% under the undrained condition. As such, the deterministic analysis of a multi-stage slope may result in an overestimated value of the FS. Moreover, the influence of cross-correlation between cohesive strength and friction angle on the stability of drained slopes was also investigated. The findings demonstrated that the failure probability of multi-stage slope increases as the correlation coefficient increases.</abstract><cop>New York</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.compgeo.2020.103529</doi></addata></record> |
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| subjects | Bivariate analysis Computer simulation Correlation coefficient Correlation coefficients Failure mechanism Failure mechanisms Fields (mathematics) Finite element method Histograms Monte Carlo simulation Multi-stage slope Probability theory Random finite element method Slope Slope stability Slopes Soil analysis Soil properties Soil stability Soil strength Soils Spatial variability Spatial variations Stability analysis Statistical analysis Statistical methods |
| title | Probabilistic stability analyses of multi-stage soil slopes by bivariate random fields and finite element methods |
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