Influence of soil spatial variability on the response of strip footing on geocell-reinforced slope

Halder, Koushik; Chakraborty, Debraj

doi:10.1016/j.compgeo.2020.103533

Cited by 41 publications

(11 citation statements)

References 42 publications

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“…Beyond a certain scale of fluctuation, the failure probability is observed to be almost insensitive with the scale of fluctuation for both the figures. The similar kind of trend has been observed by Griffiths and Fenton (2004), Chenari and Alaie (2015) and, Halder and Chakraborty (2020). Figures 12A,B also compare the failure probability between the consideration of spatial variability and without consideration of spatial variability for different values of FOS.…”

Section: Failure Probability Of the Pavementsupporting

confidence: 76%

“…After modeling the embankment slope geometry and allocating the soil properties node wise, the loading is simulated on the nodes representing pavement width (and along with the out of the plane length of the pavement) by implementing a very small amount of downward velocity in vertical direction. An optimized velocity of magnitude 5 × 10 -6 m/step is taken after few trials, as it is found to be less time-consuming as well as does not affect the pavement bearing pressure settlement response (Halder and Chakraborty, 2020). The numerical model is then run for numerous steps until the plastic steady state is achieved.…”

Section: Numerical Modelingmentioning

confidence: 99%

“…7 is used to generate the random field. The randomly distributed c and ϕ values generated in MATLAB are again taken back to FLAC 3D and are allocated node wise (Halder and Chakraborty, 2018;Halder and Chakraborty, 2020). In this way, the random fields are generated in FLAC 3D .…”

Section: Random Field Generationmentioning

confidence: 99%

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Probabilistic Bearing Capacity of a Pavement Resting on Fibre Reinforced Embankment Considering Soil Spatial Variability

Choudhuri

Chakraborty

2021

Front. Built Environ.

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This paper intends to examine the influence of spatial variability of soil properties on the probabilistic bearing capacity of a pavement located on the crest of a fibre reinforced embankment. An anisotropic random field, in combination with the finite difference method, is used to carry out the probabilistic analyses. The cohesion and internal friction angle of the soil are assumed to be lognormally distributed. The Monte Carlo simulations are carried out to obtain the mean and coefficient of variation of the pavement bearing capacity. The mean bearing capacity of the pavement is found to decrease with the increase in horizontal scale of fluctuation for a constant vertical scale of fluctuation; whereas, the coefficient of variation of the bearing capacity increases with the increase in horizontal scale of fluctuation. However, both the mean and coefficient of variation of bearing capacity of the pavement are observed to be increasing with the increase in vertical scale of fluctuation for a constant horizontal scale of fluctuation. Apart from the different scales of fluctuation, the effects of out of the plane length of the embankment and randomness in soil properties on the probabilistic bearing capacity are also investigated in the present study.

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Section: Failure Probability Of the Pavementsupporting

confidence: 76%

Section: Numerical Modelingmentioning

confidence: 99%

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Probabilistic Bearing Capacity of a Pavement Resting on Fibre Reinforced Embankment Considering Soil Spatial Variability

Choudhuri

Chakraborty

2021

Front. Built Environ.

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“…It is well recognized that spatial variability exerts a substantial influence on the behavior of soil and the stability of geotechnical structures. [1][2][3][4][5] In order to quantify the effects of spatial variability and the associated uncertainties, various probabilistic methods have been increasingly employed in geotechnical assessments, such as Bayesian methods, [6][7][8] the Markov processes [9][10][11] and stratified sampling. [12][13][14] In the field of slope engineering, primary research has focused on long slopes with indeterminate or significant ample width.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic analysis of width‐limited 3D slope in spatially variable soils: UBLA enhanced with efficiency‐improved discretization of horn‐like failure mechanism

Sun,

Zhao,

et al. 2023

Num Anal Meth Geomechanics

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Reliability analysis of earth slopes considering soil spatial variability has garnered significant attention from researchers. However, previous studies have predominantly focused on long slopes with infinite or ample width, such as dams and subgrades, but rare research was dedicated to slopes with width restricted by boundary constraints. In this regard, this paper proposes an efficient reliability framework suitable for width‐limited slopes in spatially variable soils. The proposed framework employed spatial discretization‐based upper bound limit analysis (UBLA) to conduct the deterministic slope stability analysis. The established failure mechanism can well capture the width‐limited three‐dimensional slip surface characteristics and satisfies the kinematically admissible conditions in spatially variable soils. Two innovative strategies are proposed to boost the efficiency of the discretized mechanism. They reduce the computational time to determine safety factors from over 20 min to less than 2 min. For the uncertainty modeling and slope reliability computing procedure, the Sparse Polynomial Chaos Expansion (SPCE) and Monte Carlo Simulation (MCS) methods are combined to generate the distribution of safety factors and failure probabilities. This combination addresses the high‐dimensional stochastic problem arising from 3D spatial variability. Using the proposed framework, a parametric analysis of a 3D spatially variable slope is conducted to investigate the impact of various factors. The findings of this paper are beneficial to the risk evolution of width‐limited slopes, and the efficiency enhancement strategies have the potential to expedite the limit analysis of other geo‐structures, such as tunnels, retaining walls, and foundations.

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“…et al [20] proposed that frictional resistance develops at soil-geocell interfaces. Also, geocells have been inferred to play an important role in governing the characteristics of interface friction [21,22]. In this regard, geocells can significantly improve the frictional characteristics at the interface and can substantially arrest lateral spreading of railway subgrade [23].…”

Section: Introductionmentioning

confidence: 99%

Modeling Riverbank Slope Reinforcement Using Anti-Slide Piles with Geocells

Liu

Zhou

et al. 2021

JMSE

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Geocells are increasingly used in engineering applications, but the design of riverbank slope reinforcements that use only geocells limits reinforcement performance. Moreover, the design and use of anti-slide piles with geocells are mainly based on experiences that are unsupported by theoretical models. In this paper, by combining the confinement effect and vertical action mechanism of geocells, the horizontal friction mechanism of the geocell layer and the vertical support mechanism of piles, a theoretical model of riverbank slope reinforced by anti-slide piles with geocells was constructed. In addition, to describe the mechanical behavior of a riverbank slope reinforced by anti-slide piles with geocells, the slip-resisting mechanism of the anti-slide pile with interaction between geocells and their internal filler is considered in the model. Furthermore, to investigate the influence of changes in water level on riverbank slope stability, the developed model takes into account settlement, lateral displacement, pile bending moment and pile axial force. The model predications were validated by the field measurement data. The results from a series of parametric studies show that the use of anti-slide pile and geocells can effectively reduce the settlement and the lateral displacement of a riverbank slope. The developed model could contribute to an optimal design of anti-slide pile with geocells for enhancing the stability of a riverbank slope.

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Influence of soil spatial variability on the response of strip footing on geocell-reinforced slope

Cited by 41 publications

References 42 publications

Probabilistic Bearing Capacity of a Pavement Resting on Fibre Reinforced Embankment Considering Soil Spatial Variability

Probabilistic Bearing Capacity of a Pavement Resting on Fibre Reinforced Embankment Considering Soil Spatial Variability

Probabilistic analysis of width‐limited 3D slope in spatially variable soils: UBLA enhanced with efficiency‐improved discretization of horn‐like failure mechanism

Modeling Riverbank Slope Reinforcement Using Anti-Slide Piles with Geocells

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