Random field theory to interpret the spatial variability of lacustrine soils

Vessia, Giovanna; Russo, Savino

doi:10.1016/j.biosystemseng.2017.08.023

Cited by 15 publications

(3 citation statements)

References 8 publications

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“…In the random field model, the space mean-variance of soil parameters decreases with the increase of the average spatial range [11,12]. The minimum distance between any two points in the soil layer with parameters uncorrelated with each other is called the correlation distance of soil parameters [13][14][15]. Given the influence of the correlation distance, the spatial variability of foundation soil parameters can be better reflected [16,17].…”

Section: Introductionmentioning

confidence: 99%

Influence of Correlation Distance of Soil Parameters on Pile Foundation Failure Probability

et al. 2023

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Spatial variability of soil parameter distribution is crucial to calculating the pile foundation failure probability. Traditional reliability design methods describe the dispersion degree of soil parameters with their point variance without considering the influence of correlation distance. In this paper, static cone penetration test data of a project site are used, and random field theory is introduced to describe the average spatial characteristics of soil parameters. Then, the method of spatial average is used to calculate the correlation distance of soil parameters in each foundation soil layer. Given the influence of the correlation distance, a variance reduction function is determined to convert point variance to spatial mean-variance and further calculate the failure probability of pile foundation with the Monte Carlo method to study the influence of correlation distance on pile foundation failure probability. Results show that the spatial variability of parameters can be better reflected, and project cost can be reduced by considering the influence of correlation distance during the pile foundation design process. These results lay a foundation for further research on the pile foundation reliability design method.

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Section: Introductionmentioning

confidence: 99%

Influence of Correlation Distance of Soil Parameters on Pile Foundation Failure Probability

et al. 2023

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“…Random fields are essential in the uncertainty modelling of a subsoil based on limited in situ data [22,23]. Attempts are made to precisely model the subsoil medium in twodimensional [24] or three-dimensional [25] problems.…”

Section: Introductionmentioning

confidence: 99%

The Effect of the Selection of Three-Dimensional Random Numerical Soil Models on Strip Foundation Settlements

2021

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This paper delivers a probabilistic attempt to prove that the selection of a random three-dimensional finite element (FE) model of a subsoil affects the computed settlements. Parametric analysis of a random soil block is conducted, assuming a variable subsoil Young’s modulus in particular finite elements. The modulus is represented by a random field or different-sized sets of random variables; in both cases, the same truncated Gaussian model is assumed. Mean values and standard deviations of random soil settlement are estimated by a Monte Carlo simulation procedure. With regard to the adopted FE model, the estimated settlement mean values do not vary significantly, but standard deviations do strongly. Similarities also appear in the diagrams of random field correlation length versus settlement standard deviation and the diagrams displaying a total number of model random variables versus settlement standard deviation. Thus, relevant single random variable models represent the random field approach well with regard to settlement parameter estimation. This remark is verified upon a settlement analysis of a three-dimensional FE model of a hypothetical strip foundation. Following the preliminary model observations, various probabilistic geotechnical analyses may be supported, e.g., continuous footing design, slope stability analysis, and foundation reliability assessment.

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“…This uncertainty is a well-known problematic issue for the accurate design of soil-related structures. The random field theory (RFT) is an ordinary tool for applying the spatial variation of soils [1][2][3][4][5]. This theory has been utilized for formulating spatial variability of soil in geotechnical engineering problems.…”

Section: Introductionmentioning

confidence: 99%

Simple Equations for Considering Spatial Variability on the Bearing Capacity of Clay

Azan

Haddad

2019

Civ Eng J

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In the present paper, the effect of spatial variability of undrained shear strength on the bearing capacity of shallow strip footing on clay was investigated and two new and simple equations were introduced for incorporating the effect of soil variability parameters on the undrained bearing capacity of strip footing on clay. For investigating the spatial variability of clay, undrained shear strength was assumed as a spatial variable parameter with the use of random field theory. The Monte Carlo simulation technique was used to obtain the probability distribution of the bearing capacity of footing on nonhomogeneous clay. The spatial variability of the undrained shear strength was investigated using three controlling parameters: coefficient of variation (COV) of the undrained shear strength as well as the scales of fluctuation of the shear strength in horizontal and vertical directions. The Mohr-Coulomb failure criterion and finite difference method were used to model the plastic behaviour of soil and calculate the bearing capacity of the footing. The results show that by increasing the COV of the undrained shear strength, the average bearing capacity decreases while the COV of the bearing capacity increases. Moreover, the average bearing capacity of footing has an approximate increasing trend with increasing the scales of fluctuation.

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Random field theory to interpret the spatial variability of lacustrine soils

Cited by 15 publications

References 8 publications

Influence of Correlation Distance of Soil Parameters on Pile Foundation Failure Probability

Influence of Correlation Distance of Soil Parameters on Pile Foundation Failure Probability

The Effect of the Selection of Three-Dimensional Random Numerical Soil Models on Strip Foundation Settlements

Simple Equations for Considering Spatial Variability on the Bearing Capacity of Clay

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