Efficient methodology for probabilistic analysis of consolidation considering spatial variability

Bong, Taeho; Stuedlein, Armin W.

doi:10.1016/j.enggeo.2018.02.009

Cited by 21 publications

(14 citation statements)

References 37 publications

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“…Different geometrical dimensions of the 3D soil domain and correlation lengths are considered and compared with respect to the corresponding solid problem without considering the pore pressure. The qualitative and quantitative results obtained in the present work agree with the published work in the field [5,9,21,22,29,34,37,46] 2 Formulation of the dynamic soil-pore-fluid interaction…”

Section: Introductionsupporting

confidence: 88%

“…Several investigations have studied the influence of the input variability, such as the Young modulus and the permeability on the actual displacements, the degree of consolidation and the stress distribution in the soil domain. Kim et al [29], Huang et al [22], Bong and Stuedlein [9], Ronold [46] and Houmadi et al [21]. In the stochastic finite element method there are two ways of describing the spatial distribution of the input stochastic variables [5, 8, 12, 20, 24, 35, 37-39, 42, 49].…”

Section: Introductionmentioning

confidence: 99%

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A probabilistic assessment for porous consolidation of clays

Savvides

Papadrakakis

2020

SN Appl. Sci.

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In this study, the quantitative effect of the random distribution of the soil material properties to the probability density functions of the soil displacements is presented. A numerical tool of FEM model with Modified Cam Clay criterion is used for this scope. Various assumptions for the random distribution of the compressibility factor , of the constitutive relation, the critical state line inclination c of the soil, and the permeability k have been tested and assessed with Monte Carlo simulation. It is portrayed that in porous problems the coefficient of variation (CV) of the output is always smaller than the CV of the input. Also, the output distribution remains Gaussian despite the nonlinear relation between input and output variables. Consequently, in porous consolidation problems, the maximum displacement of the soil can be predicted with smaller uncertainty and thus the soil structure interaction design is more accurate.

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Section: Introductionsupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

A probabilistic assessment for porous consolidation of clays

Savvides

Papadrakakis

2020

SN Appl. Sci.

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“…Random fields have been successfully used to model spatially correlated geotechnical properties during the last several decades (e.g., Vanmarcke 1977;Vanmarcke et al 1986;Phoon and Kulhawy 1999;Fenton and Griffiths 2008;Bong and Stuedlein 2018;Wang et al 2018;Zhao and Wang 2018b). In this study, soil property profiles from a wide variety of statistically homogenous and stationary soil layers are simulated using random fields.…”

Section: Random Field Simulation Of Soil Property Profilesmentioning

confidence: 99%

Sample size determination in geotechnical site investigation considering spatial variation and correlation

2019

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Site investigation is a fundamental element in geotechnical engineering practice, but only a small portion of geomaterials is sampled and tested during site investigation. This leads to a question of sample size determination: how many samples are needed to achieve a target level of accuracy for the results inferred from the samples? Sample size determination is a well-known topic in statistics and has many applications in a wide variety of areas. However, conventional statistical methods, which mainly deal with independent data, only have limited applications in geotechnical site investigation because geotechnical data are not independent, but spatially varying and correlated. Existing design codes around the world (e.g., Eurocode 7) only provide conceptual principles on sample size determination. No scientific or quantitative method is available for sample size determination in site investigation considering spatial variation and correlation of geotechnical properties. This study performs an extensive parametric study and develops a statistical chart for sample size determination with consideration of spatial variation and correlation using Bayesian compressive sensing or sampling. Real cone penetration test data and real laboratory test data are used to illustrate application of the proposed statistical chart, and the method is shown to perform well.

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“…Por consiguiente, es necesario caracterizar los suelos mediante PDF apropiadas que describan dicha variabilidad para cada uno de sus parámetros [15]. Lo anterior se debe a que no siempre la distribución de datos es uniforme y el valor medio de los mismos coincide con la mediana.…”

Section: Excelenteunclassified

“…Huang et al [14] combinaron la teoría de consolidación de Biot con el método aleatorio de elementos finitos y establecieron un estudio paramétrico entre el coeficiente de compresibilidad del volumen (m v ) y la permeabilidad del suelo (k) como variables aleatorias que siguen una distribución lognormal, sus resultados permitieron evaluar el fenómeno de consolidación en depósitos de suelo con propiedades espacialmente variables en espacios unidimensionales (1D) y bidimensionales (2D). Bong y Stuedlein [15] abordaron dos métodos para el análisis probabilístico del fenómeno de consolidación, el método confiabilidad de primer orden (FORM) y método de superficie de respuesta estocástica (SRSM); en dichos métodos se tuvo en cuenta la variabilidad espacial del coeficiente de consolidación (Cv) y una técnica para calcular una parámetro Cv equivalente para la consolidación vertical y radial combinada.…”

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Variabilidad espacial del suelo arcilloso de la Sabana de Bogotá en la confiabilidad de asentamientos por consolidación primaria

2018

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El objetivo de este artículo es presentar un estudio de confiabilidad de los parámetros de consolidación de un suelo arcilloso de la Sabana de Bogotá. La metodología de trabajo comprendió la extracción de muestras de arcillas inalteradas y la ejecución de un plan experimental de laboratorio que incluyó treinta ensayos edométricos. Además, se estimaron las distribuciones de probabilidad de los parámetros de consolidación del suelo de la Sabana de Bogotá. Los resultados permitieron obtener la variabilidad de las propiedades de compresibilidad de dichos materiales. Por otra parte, se realizaron simulaciones de Monte Carlo para estimar las curvas de confiabilidad de asentamientos. Se encontró que la magnitud de los asentamientos en los suelos arcillosos de la Sabana de Bogotá se ven afectados por la variabilidad espacial de las propiedades de compresibilidad de este tipo de suelo.

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Efficient methodology for probabilistic analysis of consolidation considering spatial variability

Cited by 21 publications

References 37 publications

A probabilistic assessment for porous consolidation of clays

A probabilistic assessment for porous consolidation of clays

Sample size determination in geotechnical site investigation considering spatial variation and correlation

Variabilidad espacial del suelo arcilloso de la Sabana de Bogotá en la confiabilidad de asentamientos por consolidación primaria

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