A probabilistic analysis of foundation settlements

Brząkała, W.; Puła, Wojciech

doi:10.1016/0266-352x(95)00033-7

Cited by 34 publications

(17 citation statements)

References 13 publications

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“…Stochastic finite element methods, which incorporated the spatial variability of the random variables together with the finite element methods, improved the probabilistic foundation settlement predictions (Beacher and Ingra, 1981;Zeitoun and Baker, 1992;Brzakala and Pula, 1996;Kuo et al, 2004). Different probabilistic distributions were assumed for the modulus of soil by different researchers: normal (Zeitoun and Baker, 1992), lognormal (Paice et al, 1996;Kuo et al, 2004;Griffiths and Fenton, 2009;Jimenez and Sitar, 2009), gamma (Jimenez and Sitar, 2009), and beta distributions (Sivakugan and Johnson, 2004).…”

Section: Discussionmentioning

confidence: 98%

“…Paice et al (1994) explored the effects of random soil parameters on foundation settlement using deterministic finite element analysis with stochastic soil input parameters (a lognormal distribution with exponential correlation structure was assumed for elastic modulus of soil). Brzakala and Pula (1996) studied the effects of shape of subsoil, material properties, and loads on the uncertainties in foundation settlement prediction. A random field was established with interface variation between two sub layers and was integrated with stochastic finite element analysis of perturbation technique and Neumann expansion method.…”

Section: Settlement Of Shallow Foundationsmentioning

confidence: 99%

“…Numerous amount of experimental, analytical, and numerical modeling research have been conducted on the behavior of shallow foundations over the years, though most of them included deterministic analysis. In recent years, bearing capacity and settlement of shallow foundations have been analyzed probabilistically by many researchers with spatial variability of soil properties (Wu and Kraft, 1967;Resendiz and Herrera, 1969;Folayan et al, 1970;Beacher and Ingra, 1981;Zeitoun and Baker, 1992;Nadim et al, 1993;Paice et al, 1994Paice et al, , 1996Brzakala and Pula, 1996;Cherubini, 2000;Griffiths et al, 2002aGriffiths et al, , 2002bGriffiths et al, , 2006Fenton and Griffiths, 2002, 2005Kuo et al, 2004;Sivakugan and Johnson, 2004;Popescu et al, 2005aPopescu et al, , 2005bAkbas, 2007;Fenton et al, 2008;Srivastava and Babu, 2009;Griffiths and Fenton, 2009;Akbas and Kulhawy, 2009;Roberts and Misra, 2009;Jimenez and Sitar, 2009). Reliability-based design (RBD) methods have also been developed for foundation engineering problems such as bearing capacity, settlement, and uplift by many researchers (Cherubini, 2000;Fenton et al, 2007Fenton et al, , 2008Akbas and Kulhawy, 2009;Roberts and Misra, 2009).…”

Section: Introductionmentioning

confidence: 98%

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Application of probabilistic methods to characterize soil variability and their effects on bearing capacity and settlement of shallow foundations: state of the art

Kayser

Gajan

2014

International Journal of Geotechnical Engineering

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This paper presents the applications of probabilistic methods to analyze the load-displacement behavior of shallow foundations supported by uncertain and spatially variable soils. The paper describes the types and sources of uncertainties in soil properties that dictate the bearing capacity and settlement of shallow foundations and characterizes their probabilistic distributions. General probabilistic analysis methods that are commonly used in foundation engineering applications such as first order second moment (FOSM) method, tornado diagram method, Monte Carlo (MC) simulation method, random finite element method (RFEM), and reliability-based design (RBD) method are briefly described. A thorough summary of the applications of these methods in determining the probabilistic bearing capacity, settlement, and differential settlement of shallow foundations from the research literature is presented.

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Section: Discussionmentioning

confidence: 98%

Section: Settlement Of Shallow Foundationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

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Application of probabilistic methods to characterize soil variability and their effects on bearing capacity and settlement of shallow foundations: state of the art

Kayser

Gajan

2014

International Journal of Geotechnical Engineering

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“…The other method is using probabilistic methods and combining them with geotechnical engineering analysis methods. In these methods, the effect of all possible parameters will be included in the calculations, so analyses precision will increase and share of all the errors will be considered in these analyses [5].…”

Section: Problem Statementmentioning

confidence: 99%

Probabilistic Analysis of Shallow Foundation Settlement considering Soil Parameters Uncertainty Effects

Nazarzadeh¹,

Sarbishe-ee²

2017

OJG

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One of the most important challenges in the design of the foundation of the Earth layer below the surface is the Summit Foundation, which can be a very large impact on the sustainability and the structure of the desired user. Based on this analysis and design criteria of two successive ruptures (load bearing) and settlement, due to the nature of non-homogeneous soil and its parameters uncertainty, relying on one number as the amount of foundation settlement doesn't seem logical. This is while in the methods of the probability distribution function by taking the probability for each of the input parameters, or the characteristics of each parameter, the parameter values are likely to have the chance of occurrence. In this research, effort is made using the method of probabilistic Monte Carlo simulation, the effect of the uncertainty of parameters influencing the mechanical behavior following the successive layers of earth and examined. In the event that non-deterministic model input variables for describing, not non-deterministic model output as well. So the output of each method to analysis of the concept of the probability distribution function for the input variables is a function of the probability distribution for the target function. In this study, the reliability of the settlement for the three modes of settlement center, corner of rigid foundation is fitted with two types of normal probability distribution and the log-normal distributions. For this purpose, the parameters of the effect of the transition on the analysis of soil modulus of elasticity of foundation, such as settlement and the coefficient of Poisson ratio distribution in probability using probabilistic log-normal and normal have been considered. Analysis indicated that the settlement in the center of the wake is flexible critical than the other two and has a higher probability of occurrence of the settlement in this part of the foundation. In the case of the normal distribution and the normal distribution graph of the log was used, the probability density function of the normal distribution is related to the log has a greater dispersion.

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“…In addition, they proposed an inverse analysis to identify the spatial distribution of the coefficients. Zeitoun and Baker [28] and Brzakala and Pula [29] analysed the settlement of heterogeneous shallow foundations by introducing uncertainty in the shear modulus. The system addressed was a randon layered elastic media and no hydro-mechanical coupling was considered.…”

Section: Introductionmentioning

confidence: 99%

Stochastic computational modelling of highly heterogeneous poroelastic media with long‐range correlations

Frias

Murad

Pereira

2003

Num Anal Meth Geomechanics

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SUMMARYThe compaction of highly heterogeneous poroelastic reservoirs with the geology characterized by long-range correlations displaying fractal character is investigated within the framework of the stochastic computational modelling. The influence of reservoir heterogeneity upon the magnitude of the stresses induced in the porous matrix during fluid withdrawal and rock consolidation is analysed by performing ensemble averages over realizations of a log-normally distributed stationary random hydraulic conductivity field. Considering the statistical distribution of this parameter characterized by a coefficient of variation governing the magnitude of heterogeneity and a correlation function which decays with a power-law scaling behaviour we show that the combination of these two effects result in an increase in the magnitude of effective stresses of the rock during reservoir depletion. Further, within the framework of a perturbation analysis we show that the randomness in the hydraulic conductivity gives rise to non-linear corrections in the upscaled poroelastic equations. These corrections are illustrated by a self-consistent recursive hierarchy of solutions of the stochastic poroelastic equations parametrized by a scale parameter representing the fluctuating log-conductivity standard deviation. A classical example of land subsidence caused by fluid extraction of a weak reservoir is numerically simulated by performing Monte Carlo simulations in conjunction with finite elements discretizations of the poroelastic equations associated with an ensemble of geologies. Numerical results illustrate the effects of the spatial variability and fractal character of the permeability distribution upon the evolution of the Mohr-Coulomb function of the rock.

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A probabilistic analysis of foundation settlements

Cited by 34 publications

References 13 publications

Application of probabilistic methods to characterize soil variability and their effects on bearing capacity and settlement of shallow foundations: state of the art

Application of probabilistic methods to characterize soil variability and their effects on bearing capacity and settlement of shallow foundations: state of the art

Probabilistic Analysis of Shallow Foundation Settlement considering Soil Parameters Uncertainty Effects

Stochastic computational modelling of highly heterogeneous poroelastic media with long‐range correlations

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