Stochastic finite element method applied to non-linear analysis of embankments

Mellah, R.; Auvinet, G.; Masrouri, Farimah

doi:10.1016/s0266-8920(99)00024-7

Cited by 42 publications

(18 citation statements)

References 5 publications

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“…At this juncture, it is mentioned that research work in the area of modelling the stochastic spatial variability of soil properties for geotechnical engineering problems has been done in the past among others by Auvinet and Gonzalez [1], Fenton [2; 3], Fenton and Vanmarcke [4], Mellah et al [5], Popescu [6] and Rackwitz [7].…”

Section: Introductionmentioning

confidence: 99%

Risk assessment of an interacting structure–soil system due to liquefaction

Koutsourelakis

Prévost

Deodatis

2002

Earthq Engng Struct Dyn

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SUMMARYThe present study deals with the non-linear stochastic dynamic analysis of a soil-structure interacting system. The ultimate objective is to determine the risk of damage to the system due to liquefaction under a wide range of earthquake intensities. A Monte Carlo simulation approach is followed in conjunction with advanced ÿnite element procedures. The stochastic spatial variability of soil properties and the randomness of the seismic excitation are taken into account in order to estimate the statistics of the response, measured in terms of uniform foundation settlement and tilting. Speciÿcally, soil properties are modelled as non-Gaussian random ÿelds and seismic excitations as non-stationary random processes. The probabilistic characteristics of the stochastic ÿeld modelling soil properties are established from in situ tests. The risk of damage to the soil-structure system due to liquefaction is assessed by establishing fragility curves, which are of paramount importance for risk assessment and management studies of such systems. Fragility curves express the probability of exceeding various thresholds in the response. The relative e ect of the variability of various soil parameters on the variability of the response is also examined.

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Section: Introductionmentioning

confidence: 99%

Risk assessment of an interacting structure–soil system due to liquefaction

Koutsourelakis

Prévost

Deodatis

2002

Earthq Engng Struct Dyn

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“…Another method is to combine spectral analysis with a Laplace transform to model the transport of material through, for instance, the riprap (Wörman and Xu 2001). A combination of the FEM with a stochastic approach and the FEM part is used to solve the mechanical behaviour of the earth structure whilst the stochastic method is used for the probabilistic part of the earth modelling (Mellah et al 2000). Numerical procedures based solely on the FEM are also common.…”

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confidence: 99%

Fluid Flow Induced Internal Erosion within Porous Media: Modelling of the No Erosion Filter Test Experiment

et al. 2011

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An investigation of the potential to numerically model the no erosion filter test is performed here, where the flow through a large ensemble of particles is considered by applying minimisation of dissipation rate of energy on the ensemble that is discretised with modified Voronoi diagrams and Delaunay triangulation. Low-Reynolds number simulations are applied to each part of the Voronoi diagram using computational fluid dynamics. The mechanical friction between particles is modelled by increasing the effective viscosity for closely spaced particles. Microscopic mechanisms for successful and unsuccessful sealing of filters are obtained. The numerical results agree with previously presented experimental observations by Sherard and Dunnigan. A conformity is that the sealing starts from the end of the channel and continues outwards in the radial direction. The sealing implies that the permeability can be reduced several orders of magnitude during a test.

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“…Unfortunately, this is rarely the case in the geotechnical engineering discipline because soil properties are inherently varied over space. Probabilistic modelling is often used by geotechnical researchers to deal with soil variability (Alonso 1976, Mostyn and Soo 1992, Mostyn and Li 1993, Mellah et al 2000, Hicks and Samy 2002, Babu and Mukesh 2004, Griffiths and Fenton 2004, El-Ramly et al 2005, Hicks and Onisiphorou 2005, Popescu et al 2005, Sejnoha et al 2007, Griffiths et al 2009, Griffiths et al 2011. Among various problems, analysis of slope stability is one of the most exposed to probabilistic treatment.…”

Section: Introductionmentioning

confidence: 99%

“…Mostyn and Soo 1992, Mellah et al 2000, Hicks and Samy 2002, Babu and Mukesh 2004. This characteristic is usually described in stochastic modelling by auto-correlation functions, auto-correlation distances (θ) and cross-correlation.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic modelling of auto-correlation characteristics of heterogeneous slopes

Sánchez

Gallipoli

et al. 2014

Geomechanics and Geoengineering

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Spatial variability of soil materials has long been recognised as an important factor influencing the reliability of geo-structures. This study stochastically investigates the influence of spatial variability of shear strength on the stability of heterogeneous slopes, focusing on the autocorrelation function, auto-correlation distance and cross-correlation between soil parameters. The finite element method is merged with the random field theory to probabilistically evaluate factor of safety and probability of failure via Monte-Carlo simulations. The simulation procedure is explained in detail with suggestions on improving efficiency of the Monte-Carlo process. A simple procedure to create cross-correlation between random variables, which allows direct comparison of the influence of each strength variable, is discussed. The results show that the auto-correlation distance and cross-correlation can significantly influence slope stability, while the choice of auto-correlation function only has a minor effect. An equation relating the probability of failure with the auto-correlation distance is suggested in light of the analyses performed in this work and other results from the literature.

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Stochastic finite element method applied to non-linear analysis of embankments

Cited by 42 publications

References 5 publications

Risk assessment of an interacting structure–soil system due to liquefaction

Risk assessment of an interacting structure–soil system due to liquefaction

Fluid Flow Induced Internal Erosion within Porous Media: Modelling of the No Erosion Filter Test Experiment

Probabilistic modelling of auto-correlation characteristics of heterogeneous slopes

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