A stability analysis of a layered-soil slope based on random field

Zhou, Xiao Ping; Zhu, Bin; Juang, C. Hsein; Wong, Louis Ngai Yuen

doi:10.1007/s10064-018-1266-x

Cited by 14 publications

(4 citation statements)

References 34 publications

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“…22 θ tan ϕ ′ is the scale of fluctuation, it can be confirmed by variance reduction function in a certain structure. 6,22 It suggests that…”

Section: The Anti-sliding Stability Analysis Of Retaining Walls Based...mentioning

confidence: 99%

“…In this regard, some probability-based methods received attentions; for instance, the first-order second moment method, the second-order reliability method, and other approaches are widely used in structural engineering and geotechnical engineering. [1][2][3][4][5][6][7] The probabilistic methods are suggested but not used as a substitute for traditional deterministic methods. 8 This statement was further illustrated by Duncan, 9 who advocated computing both the factor of safety and probability of failure.…”

Section: Introductionmentioning

confidence: 99%

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Reliability analysis of the anti-sliding of a retaining wall subjected to seismic loads

Huang

Chen

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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Geotechnical engineering involves various types of uncertainties, as it always deals with highly variable natural materials. Reliability-based design/analysis can play at least a complementary role in the design approach. In this paper, reliability analysis of anti-sliding of retaining wall with the parameters treated as random variables is performed based on the concept of random fields. Both friction angle and cohesion of soils near the interface along the base of retaining wall are treated as Gaussian fields. The spatial correlation and cross correlation of the variables are calculated by a specific covariance function and the seismic loads act on retaining walls are also taken into account. Examples are illustrated to verify the accuracy of the proposed approach. It is found from the numerical results that the spatial correlation of shear strength has an important influence on the probability of the anti-sliding failure of retaining wall. Moreover, the numerical results obtained from the proposed method are in full agreement with those obtained from Monte Carlo simulations. Therefore, the proposed method provides a new view to study the stability of a retaining wall subjected to seismic loads.

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“…22 θ tan ϕ ′ is the scale of fluctuation, it can be confirmed by variance reduction function in a certain structure. 6,22 It suggests that…”

Section: The Anti-sliding Stability Analysis Of Retaining Walls Based...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reliability analysis of the anti-sliding of a retaining wall subjected to seismic loads

Huang

Chen

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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show abstract

“…In general, random friction modelling involves treating COF as random variables [6,7,8,9,10,11,12,13], a stochastic process [14,15] or a random field [10,16,17,18,19] in the literature. For modelling COF as a random variable, Antonio et al [6] studied the occurrence of squeal instability of a brake system, modelling the COF as random variables with the lognormal distribution.…”

Section: Introductionmentioning

confidence: 99%

Coefficient of friction random field modelling and analysis in planar sliding

Batou²,

Ouyang³

2021

Journal of Sound and Vibration

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“…He generated the slope stability design charts, which were widely used for years. Additionally, some mathematical solutions such as robust design [7,8,9,10,11] and random field theory [12,13] are still receiving considerable attention in the field of slope analysis. More recently, intelligent techniques such as the support vector machine and artificial neural network (ANN) have been broadly-used for exploring the relationship between landslide and causative factors [14,15].…”

Section: Introductionmentioning

confidence: 99%

Slope Stability Monitoring Using Novel Remote Sensing Based Fuzzy Logic

Moayedi

Bui

Foong

2019

Sensors

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By the assist of remotely sensed data, this study examines the viability of slope stability monitoring using two novel conventional models. The proposed models are considered to be the combination of neuro-fuzzy (NF) system along with invasive weed optimization (IWO) and elephant herding optimization (EHO) evolutionary techniques. Considering the conditioning factors of land use, lithology, soil type, rainfall, distance to the road, distance to the river, slope degree, elevation, slope aspect, profile curvature, plan curvature, stream power index (SPI), and topographic wetness index (TWI), it is aimed to achieve a reliable approximation of landslide occurrence likelihood for unseen environmental conditions. To this end, after training the proposed EHO-NF and IWO-NF ensembles using training landslide events, their generalization power is evaluated by receiving operating characteristic curves. The results demonstrated around 75% accuracy of prediction for both models; however, the IWO-NF achieved a better understanding of landslide distribution pattern. Due to the successful performance of the implemented models, they could be promising alternatives to mathematical and analytical approaches being used for discerning the relationship between the slope failure and environmental parameters.

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A stability analysis of a layered-soil slope based on random field

Cited by 14 publications

References 34 publications

Reliability analysis of the anti-sliding of a retaining wall subjected to seismic loads

Reliability analysis of the anti-sliding of a retaining wall subjected to seismic loads

Coefficient of friction random field modelling and analysis in planar sliding

Slope Stability Monitoring Using Novel Remote Sensing Based Fuzzy Logic

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