Bearing capacity and failure mechanism of shallow footings on unreinforced slopes: a state-of-the-art review

Dey, Arindam; Acharyya, Rana; Alammyan, Anangsha

doi:10.1080/19386362.2019.1617480

Cited by 17 publications

(4 citation statements)

References 108 publications

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“…The increase in the crest distance relates to the support available to the surface footing on the slope side, as discussed above. An increase in the crest distance reduces the asymmetric nature of the failure mechanism, allowing more support to the slope side of the footing and causing a decrease in the footing settlement (Dey et al 2019). The trends illustrated in Figure 8 comprehensively prove that the developed MLP model network correctly predicts the underlying physical behavior of the investigated system according to the known knowledge pertaining to geotechnical engineering, and thus can be considered reliable and robust.…”

Section: Model Robustness and Sensitivitymentioning

confidence: 69%

“…An increase in the slope angle ratio increases the slope instability and hence reduces the support available to the footing on the slope side, explained in terms of the asymmetric footing failure mechanism (Hovan 1985;Graham et al 1988). Due to the increase in asymmetric footing failure with an increase in slope angle ratio, the soil along the unstable slope yields under load application, resulting in increased footing settlement (Keskin and Laman 2013;Dey et al 2019). The hoop and bending stiffness of the conduit are the design parameters that are employed to classify a conduit as either rigid or flexible (Mcgrath 1999).…”

Section: Model Robustness and Sensitivitymentioning

confidence: 99%

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Load-settlement response of a footing over buried conduit in a sloping terrain: a numerical experiment-based artificial intelligent approach

2022

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Settlement estimation of a footing located over a buried conduit in a sloping terrain is a challenging task for practicing civil/geotechnical engineers. In the recent past, the advent of machine learning technology has made many traditional approaches antiquated. This paper investigates the viability, development, implementation, and comprehensive comparison of five artificial intelligence-based machine learning models, namely, multi-layer perceptron (MLP), Gaussian processes regression (GPR), lazy K-Star (LKS), decision table (DT), and random forest (RF) to estimate the settlement of footing located over a buried conduit within a soil slope. The pertaining dataset of 3600 observations was obtained by conducting large-scale numerical simulations via the finite element modelling framework. After executing the feature selection technique that is correlation-based subset selection, the applied load, total unit weight of soil, constrained modulus of soil, slope angle ratio, hoop stiffness of conduit, bending stiffness of conduit, burial depth of conduit, and crest distance of footing were utilized as the influence parameters for estimating and forecasting the settlement. The predictive strength and accuracy of all models mentioned supra were evaluated using several well-established statistical indices such as Pearson's correlation coefficient (r), root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), scatter index (SI), and relative percentage difference (RPD).The results showed that among all the models employed in this study, the multi-layer perceptron model has shown better results with r, RMSE, NSE, SI, and RPD values of (0.977, 0.298, 0.937, 0.31, and 4.31) and (0.974, 0.323, 0.928, 0.44 and 3.75) for training and testing dataset, respectively. The sensitivity analysis revealed that all the selected parameters play an important role in determining the output value. However, the applied load, constrained modulus, unit weight, slope angle ratio, hoop stiffness have the highest strength with the relative importance of 18.4%, 16.3% and 15.3%, 13.8%, 11.4%, respectively. Finally, the model was translated into a functional relationship for easy implementation and can prove useful for practitioners and researchers in predicting the settlement of a footing located over a buried conduit in a sloping terrain.

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Section: Model Robustness and Sensitivitymentioning

confidence: 69%

Section: Model Robustness and Sensitivitymentioning

confidence: 99%

Load-settlement response of a footing over buried conduit in a sloping terrain: a numerical experiment-based artificial intelligent approach

2022

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“…While the prior research rather regarded analytical methods, the current analytical trends are FEM-directed. The computations involve various methods, material models, and detailed solutions adjusted to specific tasks, see (Dey et al 2019) and their references. Aldosary et al (Aldosary et al Abstract This work conducts a probabilistic inquiry on how the variability of the parameter defining soil deformability affects the settlement of the foundation located on the soil.…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of Random Field Approach in Serviceability Limit State Analysis of Strip Foundation

et al. 2022

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This work conducts a probabilistic inquiry on how the variability of the parameter defining soil deformability affects the settlement of the foundation located on the soil. The analysis addresses the random foundation model to relevantly estimate the probability of allowable deflection exceedance. The constitutive model parameter is based either on a single random variable or a random field. The computations incorporate direct Monte Carlo sampling and the variance reduction techniques, i.e. Stratified Sampling and Latin Hypercube Sampling. The work focuses on soil parameter modelling by random fields defined by various correlation functions. One of the analytical means is the application of a non-homogeneous function capable of reflecting the soil strata. The probabilistic methods proposed in the paper are tested on a standard example of a foundation strip featuring load eccentricity. It is proved that the modelling mode of the soil—a single variable or a random field—substantially affects the results, i.e. foundation settlements. It was detected that incorporating random fields in soil analysis allows for a valid reliability assessment of a foundation in respect to Serviceability Limit State. The relevantly adjusted correlation functions of random fields allow for a realistic subsoil analysis even in the case of a limited in situ measurement database.

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“…For example, the Po Shan landslides in 1972 has killed 138 people and lead to the damage of the several civil infrastructures on the slope (Choi et al [5]). There are several studies undertaken during the last 50 years to understand the behavior of foundations-slope systems (Meyerhof [6], Shields et al [7], Raj et al [8], Dey et al [9], Li et al [10]). These studies provide valuable information for understanding the foundation-slope behavior taking account influence of various parameters such as the slope geometry and foundation positions.…”

Section: Introductionmentioning

confidence: 99%

Performance estimation of a shallow foundation on an unsaturated expansive soil slope subjected to rainfall infiltration

Tan

Vanapalli

2021

MATEC Web Conf.

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In the last two decades, there has been a significant increase in infrastructure development on slopes of hilly regions of the world, due to population growth. There are many infrastructures on unsaturated expansive slopes, especially in semi-arid and arid regions. Rainfall infiltration is one of the major factors that contributes to the slope and infrastructure foundations failures on hilly slopes with unsaturated expansive soils. In the current study, a rational approach is proposed considering the combined influence of the foundation-slope behavior based on the principles of unsaturated soil mechanics. This is achieved by a novel numerical modelling approach using the commercial software Geo-studio to investigate the performance of strip foundation located on the top of the unsaturated expansive soil slope subjected to various rainfall infiltration conditions. Hydro-mechanical coupling analysis is conducted to evaluate the rainfall water infiltration influence combined with slope stability analysis using limit equilibrium method. Comparisons are made between both the foundation bearing capacity, slope stability before and after rainfall water infiltration. Different failure mechanisms of the foundation and slope system are presented with and without foundation loading for various rainfall scenarios. Results summarized in this paper are helpful for the geotechnical engineers for understanding the performance of shallow foundations on unsaturated expansive soil slopes considering the influence of rainfall infiltration conditions.

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Bearing capacity and failure mechanism of shallow footings on unreinforced slopes: a state-of-the-art review

Cited by 17 publications

References 108 publications

Load-settlement response of a footing over buried conduit in a sloping terrain: a numerical experiment-based artificial intelligent approach

Load-settlement response of a footing over buried conduit in a sloping terrain: a numerical experiment-based artificial intelligent approach

Effectiveness of Random Field Approach in Serviceability Limit State Analysis of Strip Foundation

Performance estimation of a shallow foundation on an unsaturated expansive soil slope subjected to rainfall infiltration

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