Bearing Capacity of Rough Rigid Strip Footing on Cohesive Soil: Probabilistic Study

Griffiths, D. V.; Fenton, Gordon A.; Manoharan, N.

doi:10.1061/(asce)1090-0241(2002)128:9(743)

Cited by 244 publications

(96 citation statements)

References 12 publications

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“…The mean, Qualitatively similar results have been presented by Griffiths et al (2002). However, these Authors also report a local minimum in the expected bearing capacity for  ln s u ≈ 1.0, which is not seen in the current numerical limit analyses (Fig.…”

Section: Bearing Capacity Resultssupporting

confidence: 88%

“…If N c is log-normally distributed, the probability that the bearing capacity is less than the nominal load is given by: As expected, when spatial variability is included in the analyses, the ultimate bearing capacity is almost always less than the deterministic capacity based on the mean shear strength. These results agree with earlier solutions from FEM-LAS reported by Griffiths et al (2002) (for the same range of input parameters).…”

Section: Probability Of Failuresupporting

confidence: 92%

“…The current paper provides a completely independent method of evaluating undrained stability, but follows the statistical assumptions on clay shear strength properties and notations introduced by Griffiths et al (2002) to facilitate the comparisons of results.…”

Section: N O T C O P Y E D I T E Dmentioning

confidence: 99%

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Bearing Capacity of Spatially Random Cohesive Soil Using Numerical Limit Analyses

Kasama

Whittle

2011

J. Geotech. Geoenviron. Eng.

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This paper describes a probabilistic study of the two dimensional bearing capacity of a vertically loaded strip footing on spatially random, cohesive soil using Numerical Limit Analyses (NLA-CD). The analyses uses a Cholesky Decomposition (CD) technique with mid-point discretization to represent the spatial variation in undrained shear strength within finite element meshes for both upper and lower bound analyses, and assumes an isotropic correlation length. Monte Carlo simulations are then used to interpret the bearing capacity for selected ranges of the coefficient of variation in undrained shear strength and the ratio of correlation length to footing width. The results are compared directly with data from a very similar study by Griffiths et al. in which bearing capacity realizations were computed using a method of Local Average Subdivision (LAS) in a conventional displacement-based Finite Element Method (FEM-LAS). These comparisons show the same qualitative features, but suggest that the published FEM calculations tend to overestimate the probability of failure at large correlation lengths. The NLA method offers a more convenient and computationally efficient approach for evaluating effects of variability in soil strength properties in geotechnical stability calculations.

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Section: Bearing Capacity Resultssupporting

confidence: 88%

Section: Probability Of Failuresupporting

confidence: 92%

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Bearing Capacity of Spatially Random Cohesive Soil Using Numerical Limit Analyses

Kasama

Whittle

2011

J. Geotech. Geoenviron. Eng.

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“…Reliability techniques have been applied frequently to other kind of problems in the geotechnical field, such as slope stability, where probabilistic analysis has received considerable attention [7][8][9][10][11][12][13][14]. …”

Section: Introductionmentioning

confidence: 99%

Methodology for estimating the probability of failure by sliding in concrete gravity dams in the context of risk analysis

et al. 2012

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ElsevierAltarejos García, L.; Escuder Bueno, I.; Serrano Lombillo, AJ.; Gómez De Membrillera Ortuño, M. (2012). Methodology for estimating the probability of failure by sliding in concrete gravity dams in the context of risk analysis. Structural Safety. 34(1):1-13. doi:10.1016/j.strusafe.2012.01.001. METHODOLOGY FOR ESTIMATING THE PROBABILITY OF FAILURE BY SLIDING IN CONCRETE GRAVITY DAMS IN THE CONTEXT OF RISK ANALYSISJanuary 12 th , 2012 AbstractDam safety based on risk analysis methodologies demand quantification of the risk of the dam-reservoir system. This means that, for a given initial state of the system, and for the several failure modes considered, it is necessary to estimate the probability of the load events and the conditional probability of response of the system for a given load event, as well as estimating the consequences on the environment for the obtained response of the system. The following paper focuses in the second of these probabilities, that is, quantifying the conditional probability of response of the system, for a given load event, and for the specific case of concrete gravity dams. Dam-reservoir systems have a complex behavior which has been tackled traditionally by simplifications in the formulation of the models and adoption of safety factors. The purpose of the methodology described in this paper is to improve the estimation of the conditional probability of response of the damreservoir system for concrete gravity dams, using complex behavior models based on numerical simulation techniques, together with reliability techniques of different levels of precision are applied, including Level 3 reliability techniques with Monte Carlo simulation. The paper includes an example of application of the proposed methodology to a Spanish concrete gravity dam, considering the failure mode of sliding along the rock-concrete interface. In the context of risk analysis, the results obtained for conditional probability of failure allow several conclusions related to their validity and safety implications that acquire a significant relevance due to the innovation of the study performed.

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“…Several authors have considered the effect of the spatial variability of the soil properties in their calculation models. For the bearing capacity of foundations which is the subject of the present paper, one may cite among others [1,2].…”

Section: Introductionmentioning

confidence: 99%

Bearing Capacity of Strip Footings on Spatially Random Soils Using Kriging and Monte Carlo Simulation

Thajeel¹,

Al-Bittar²,

Issa³

et al. 2016

Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016)

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Abstract. The probabilistic analysis of geotechnical structures presenting spatial variability in the soil properties is generally performed using Echard et al. (2011). The present study involves a probabilistic analysis at the ultimate limit state of a strip footing resting on a spatially varying soil using AK-MCS approach. The objective is the computation of the probability P f of exceeding the ultimate bearing capacity of the footing under a prescribed footing load. The soil cohesion and angle of internal friction were considered as two non-isotropic non-Gaussian random fields. The deterministic model was based on numerical simulations using the finite difference code FLAC 3D . Some probabilistic results are presented and discussed.

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Bearing Capacity of Rough Rigid Strip Footing on Cohesive Soil: Probabilistic Study

Cited by 244 publications

References 12 publications

Bearing Capacity of Spatially Random Cohesive Soil Using Numerical Limit Analyses

Bearing Capacity of Spatially Random Cohesive Soil Using Numerical Limit Analyses

Methodology for estimating the probability of failure by sliding in concrete gravity dams in the context of risk analysis

Bearing Capacity of Strip Footings on Spatially Random Soils Using Kriging and Monte Carlo Simulation

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