The influence of the unsaturated soil zone on 2-D and 3-D slope stability analyses

Zhang, L.L.; Fredlund, M. D.; Fredlund, D. G.; Lu, Haihua; Wilson, Gordon

doi:10.1016/j.enggeo.2015.05.011

Cited by 45 publications

(9 citation statements)

References 36 publications

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“…a) b) Figure 13. 3D numerical models of slopes of a more complex geometry with the sliding mass of the soil separately shown [35] Na slici 14 prikazani su 3D numerički modeli kosina nešto složenije geometrije, s prikazanom izdvojenom kliznom masom tla i položajima proračunatih tačaka faktora sigurnosti, dobijenih optimizacijom za konkavnu i konveksnu kliznu površ. Konkavna klizna površ formirana je iz 3D prostornih konačnih elemenata, dok je konveksna klizna površ formirana kombinacijom 3D prostornih i 2D površinskih konačnih elemenata.…”

Section: A) B)unclassified

“…The concave sliding surface is formed from 3D spatial finite elements, while the convex sliding surface is formed by combining 3D spatial and 2D surface finite elements. sliding surface [35] Modeliranje omekšanja i diskontinuiteta u tlu sprovodi se korekcijom parametara konstitutivnog modela ponašanja tla i eliminacijom veze određenih konačnih elemenata ili čak redukcijom određenog broja konačnih elemenata koji se nalaze u posebnoj zoni progušćenja mreže konačnih elemenata. Aproksimacija se odnosi na izbor optimalnog tipa konačnog elementa kojim se efikasno modelira polje pomeranja tla u modelu kosine.…”

Section: A) B)unclassified

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The systematization of analytical and numerical methods of landslide stability calculation

Božić-Tomić¹,

Nenad²,

Uljarević³

2018

Građ materijali i konstrukcije

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S obzirom na kompleksnost geometrije reljefa zemljine površi, kosine su među problematičnijim geološkim formama u geotehnici. Kosine karakteriše nagla promena geometrije terena (denivelacija), s predispozicijom promene ove geometrije usled dejstva različitih faktora. Najčešći i najsloženiji vid narušavanja tla i geometrije kosine odnosi se na stabilnost terenabilo prirodnih padina ili veštačkih kosina. Svako narušavanje postojeće ravnoteže na padinama ili kosinama izaziva pomeranja pod uticajem gravitacije: klizanje, odronjavanje ili tečenje površinskog dela tla, ali i dubljih delova stenske mase. Za ovako uspostavljeno klizanje, u geološkoj i geotehničkoj terminologiji i nomenklaturi, ustaljen je termin -klizište [11]. Uslovi za nastanak i razvoj klizišta jesu: geotehnički, geološki, geomorfološki, hidrogeološki, meteorološki, vegetacioni, antropogeni, dejstvo zemljotresa, dejstvo akumulacija, vibracije usled saobraćaja i drugi.U poslednjih sto godina, zabeležen je znatan broj katastrofalnih klizišta, nastalih kao posledica dejstva zemljotresa, erupcije vulkana, nagomilavanja snega, višednevnih i intenzivnih kiša i uragana [16]. Zbog formiranja ovih klizišta, poginulo je nekoliko stotina hiljada ljudi koji su -u najvećem broju slučajeva -imali sagrađene Mr Kristina Božić-Tomić, Institut za ispitivanje materijala

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Section: A) B)unclassified

The systematization of analytical and numerical methods of landslide stability calculation

Božić-Tomić¹,

Nenad²,

Uljarević³

2018

Građ materijali i konstrukcije

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“…In order to simplify the calculation process for FS , a vast majority of slope stability analyses in engineering practice are performed in two‐dimensions (2D) under plane strain assumption, in which the slope is assumed to be infinitely wide such that three‐dimensional (3D) end effects are negligible. However, numerous natural and constructed practical slopes exhibit a complex geometric configuration and a 3D state 1–4 . From reported slopes in the literature, 2,5,6 relative differences between the two‐dimensional factor of safety ( FS2D ) and three‐dimensional factor of safety ( FS3D ) are found greater than 50%.…”

Section: Introductionmentioning

confidence: 99%

“…However, numerous natural and constructed practical slopes exhibit a complex geometric configuration and a 3D state 1–4 . From reported slopes in the literature, 2,5,6 relative differences between the two‐dimensional factor of safety ( FS2D ) and three‐dimensional factor of safety ( FS3D ) are found greater than 50%. Therefore, the prediction based on 2D analysis can be excessively conservative and economically unjustified.…”

Section: Introductionmentioning

confidence: 99%

Three‐dimensional slope stability predictions using artificial neural networks

Meng

Mattsson

Laue

2021

Num Anal Meth Geomechanics

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To enable assess slope stability problems efficiently, various machine learning algorithms have been proposed recently. However, these developments are restricted to two‐dimensional slope stability analyses (plane strain assumption), although the two‐dimensional results can be very conservative. In this study, artificial neural networks are adopted and trained to predict three‐dimensional slope stability and a program, SlopeLab has been developed with a graphical user interface. To reduce the number of variables, groups of dimensionless parameters to express stability of slopes in classic stability charts are adopted to construct the neural network architecture. The model has been trained with a dataset from slope stability charts for fully cohesive and cohesive‐frictional soils. Furthermore, the impact of concave plan curvature on slope stability that is usually found by excavation in practice is investigated by introducing a dimensionless parameter, relative curvature radius. Slope stability analyses have been conducted with numerical calculations and the artificial neural networks are trained with dimensionless data. The performance of the trained artificial neural networks has been evaluated with the correlation coefficient (R) and root mean square error (RMSE). High accuracy has been found in all the trained models in which R > 0.999 and RMSE < 0.15. Most importantly, the proposed program can help engineers to estimate 3D effects of a slope quickly from the ratio of the factors of safety, FS3D/FS2D. When FS3D/FS2D is large (such as larger than 1.2), a 3D numerical modelling on slope stability analyses that can consider complex 3D geometry and boundary condition is advised.

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“…It is widely considered that hydraulic factors such as atmospheric precipitation, fluctuation, and the change rate of the water level of the reservoir, as well as river wave erosion, etc., could reduce the stability of bank slopes, even leading to landslide disasters. Landslides often occur after long rainy periods due to the increase in the positive pore pressure on a potential sliding surface and the decrease in the stability of deeper slopes [9][10][11]. If intense rainfall occurs or the water level of the reservoir fluctuates rapidly, shallow landslides can occur as the moisture content in the soil becomes close to saturation, resulting in a considerable reduction in soil strength [12,13].…”

Section: Introductionmentioning

confidence: 99%

Sensitivity Analysis of Anchored Slopes under Water Level Fluctuations: A Case Study of Cangjiang Bridge—Yingpan Slope in China

Liang

Sui

2021

Applied Sciences

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This paper presents an improved slope stability sensitivity analysis (ISSSA) model that takes anchoring factors into consideration in umbrella-anchored sand and clay slopes under reservoir water level fluctuation. The results of the ISSSA model show that the slope inclination and the layout density of anchors are the main controlling factors for sand slope stability under fluctuation of the water level, while the slope inclination and water head height are the main controlling factors for slope stability in the Cangjiang bridge—Yingpan slope of Yunnan province in China. Moreover, there is an optimum anchorage angle, in the range of 25–45 degrees, which has the greatest influence on slope stability. The fluctuation of the reservoir water level is an important factor that triggers slope instability; in particular, a sudden drop in the surface water level can easily lead to landslides; therefore, corresponding measures should be implemented in a timely manner in order to mitigate landslide disasters.

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The influence of the unsaturated soil zone on 2-D and 3-D slope stability analyses

Cited by 45 publications

References 36 publications

The systematization of analytical and numerical methods of landslide stability calculation

The systematization of analytical and numerical methods of landslide stability calculation

Three‐dimensional slope stability predictions using artificial neural networks

Sensitivity Analysis of Anchored Slopes under Water Level Fluctuations: A Case Study of Cangjiang Bridge—Yingpan Slope in China

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