Finite element limit analysis of the seismic bearing capacity of strip footing adjacent to excavation in <i>c-φ</i> soil

Beygi, Majid; Keshavarz, Amin; Abbaspour, Mohsen; Vali, Ramin; Saberian, Mohammad

doi:10.1080/17486025.2020.1728396

Cited by 22 publications

(5 citation statements)

References 25 publications

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“…The study covers a range of five dimensionless parameters, which comprise the value of c u /γB varies from 1.5 to 5.0, while H/B varies from 1 to 4, L/B values have the ranges of 0-4, D/B varies from 1 to 2, four β values of 15°, 30°, 45°, and 60° and the horizontal seismic acceleration coefficient k h is taken into account at three distinct values of 0.1, 0.2, and 0.3, respectively. These ranges are decided based on the related published literature in [40][41][42].…”

Section: Problem Statement and Modelling Techniquementioning

confidence: 99%

“…In addition, Cinicioglu and Erkli [40] investigated the seismic bearing capacity of strip footings lying on or adjacent to a slope by employing the finite element program PLAXIS in undrained conditions. Recently, the FELA technique was employed by Luo et al [41], Beygi et al [42], and Zhang et al [23] to solve the seismic bearing capacity of strip footings on cohesive and cohesive-frictional soils, in spite that their solutions are limited to the cases of footings resting on the surface of slopes. Due to its popularity, the FELA technique has also been used to many other geotechnical problems [43][44][45][46][47][48][49][50][51][52][53].…”

Section: Introductionmentioning

confidence: 99%

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Determining Seismic Bearing Capacity of Footings Embedded in Cohesive Soil Slopes Using Multivariate Adaptive Regression Splines

Lai

Yang

et al. 2022

Int. J. of Geosynth. and Ground Eng.

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Seismic bearing capacity of strip footings in cohesive soil slopes considering various embedded depths is investigated in this study. Novel solutions using pseudo-static method and finite element limit analysis (FELA) with upper bound (LB) and lower bound (LB) theorems are presented. The influences of footing depth, slope angle, slope height, undrained shear strength and pseudo-static acceleration on bearing capacity and failure mechanisms are examined using dimensionless parameters. With the comprehensive numerical results, the multivariate adaptive regression splines (MARS) model is then utilized to simulate the sensitivity of all dimensionless input parameters (i.e., the normalized depth of footing D/B, the normalized slope height H/B, the normalized distance from top slope to edge of the footing L/B, slope angle β, the strength ratio cu/γB, and the pseudo-static acceleration factor, kh). The degree of influence of each design parameter is produced, and an empirical equation for the dimensionless output parameter (i.e., bearing capacity factor Nc) is proposed. The study results are accessible in the design charts, tables, empirical equation for design practitioners.

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Section: Problem Statement and Modelling Techniquementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Determining Seismic Bearing Capacity of Footings Embedded in Cohesive Soil Slopes Using Multivariate Adaptive Regression Splines

Lai

Yang

et al. 2022

Int. J. of Geosynth. and Ground Eng.

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“…This approach is broadly used in geotechnical engineering to solve stability problems [11,44] and ascertain the footing bearing capacity [18,[45][46][47][48]. Through the FELA method, which is a mixture of the finite element and the classical limit analysis of plasticity, lower and upper bounds on the ultimate bearing capacity of the foundation can be obtained.…”

Section: Size Of Void √ √ √mentioning

confidence: 99%

Machine Learning-Based Prediction of the Seismic Bearing Capacity of a Shallow Strip Footing over a Void in Heterogeneous Soils

et al. 2021

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The seismic bearing capacity of a shallow strip footing above a void displays a complex dependence on several characteristics, linked to geometric problems and to the soil properties. Hence, setting analytical models to estimate such bearing capacity is extremely challenging. In this work, machine learning (ML) techniques have been employed to predict the seismic bearing capacity of a shallow strip footing located over a single unsupported rectangular void in heterogeneous soil. A dataset consisting of 38,000 finite element limit analysis simulations has been created, and the mean value between the upper and lower bounds of the bearing capacity has been computed at the varying undrained shear strength and internal friction angle of the soil, horizontal earthquake accelerations, and position, shape, and size of the void. Three machine learning techniques have been adopted to learn the link between the aforementioned parameters and the bearing capacity: multilayer perceptron neural networks; a group method of data handling; and a combined adaptive-network-based fuzzy inference system and particle swarm optimization. The performances of these ML techniques have been compared with each other, in terms of the following statistical performance indices: coefficient of determination (); root mean square error (); mean absolute percentage error; scatter index; and standard bias. Results have shown that all the ML techniques perform well, though the multilayer perceptron has a slightly superior accuracy featuring noteworthy results (0.9955 and 0.0158).

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“…In addition, the NGI-ADP constitutive model was presented by Grimstad et al (2012). Although the recent finite element limit analysis is considered as a powerful technique to solve various stability problems in the geotechnical engineering field (e.g., Shiau and Al-Asadi 2020a, b, c, d;Keawsawasvong et al, 2022;Keawsawasvong and Ukritchon, 2017a, 2021Lai et al 2021a;Yodsomjai et al 2021b, c;Beygi et al 2020;Ukritchon and Keawsawasvong, 2017, 2019Tho et al 2014;Bhattacharya and Sahoo 2017;Bhattacharya 2016Bhattacharya , 2018, the displacement-based finite element analysis is also useful in solving the complex boundary conditions (e.g. Shiau and Yu 2000;Shiau and Smith 2006;Shiau et al 2006a;b, 2018;Shiau and Watson 2008;Halder and Manna 2020;Pirastehfar et al 2020;Chakraborty and Goswami, 2021;Chatterjee and Murali Krishna 2021;Keawsawasvong and Ukritchon, 2017b;Hamouma et al 2021;Huynh et al 2022a, b;Ukritchon et al 2017a, b).…”

Section: Introductionmentioning

confidence: 99%

Bearing Capacity of Ring Foundations on Anisotropic and Heterogenous Clays: FEA, NGI-ADP, and MARS

et al. 2022

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Axisymmetric solutions for the bearing capacity of ring foundation resting on anisotropic and heterogenous clays are presented in this paper using finite element analysis (FEA). The NGI-ADP model in PLAXIS FEA, a widely used anisotropic soil model, is adopted to study the stability responses of ring foundations, with special consideration given to the effects of increasing undrained shear strength with the depth. Numerical results are formulated in terms of a dimensionless stability number (bearing capacity ratio) that is a function of three dimensionless input parameters: namely, the ratio of inner and outer radius, the increasing strength gradient ratio, and the anisotropic shear strength ratio. The influence of each dimensionless input parameter on the bearing capacity ratio is investigated using design charts and failure mechanisms, and they are scored by relative importance indexes in multivariate adaptive regression splines (MARS) model—a machine learning approach. A highly accurate equation generated from the MARS model is proposed as an effective tool for engineering practitioners.

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Finite element limit analysis of the seismic bearing capacity of strip footing adjacent to excavation in c-φ soil

Cited by 22 publications

References 25 publications

Determining Seismic Bearing Capacity of Footings Embedded in Cohesive Soil Slopes Using Multivariate Adaptive Regression Splines

Determining Seismic Bearing Capacity of Footings Embedded in Cohesive Soil Slopes Using Multivariate Adaptive Regression Splines

Machine Learning-Based Prediction of the Seismic Bearing Capacity of a Shallow Strip Footing over a Void in Heterogeneous Soils

Bearing Capacity of Ring Foundations on Anisotropic and Heterogenous Clays: FEA, NGI-ADP, and MARS

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