• Journal of the Korean Geotechnical Society
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• v.35 no.3
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• pp.37-46
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• 2019

Recently, the use of CPT-based liquefaction assessment method has increased by providing more accurate results than other field tests. In CPT-based liquefaction evaluation, various soil properties are predicted and they are used for liquefaction potential assessment. In particular, fines content is one of the important input parameters in CPT-based liquefaction assessment, so it is very important to use correct prediction model and to make quantitative evaluation of estimating variability of fines content. In this study, the error evaluation of existing models for prediction of fines content through CPT was performed, and the most suitable model was selected for Pohang area, where the liquefaction phenomenon was observed in the 2017. In addition, the inherent variability of soil was analyzed, and the estimating variability of fines content was evaluated quantitatively considering the inherent variability of soil, measurement error of CPT and transformation uncertainty of selected model.

• Journal of the Korean Geotechnical Society
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• v.20 no.7
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• pp.33-44
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• 2004

This paper is focused on the spatial variability of measured strong motion data during earthquake and its relationship with the performance of water distribution pipelines and residential buildings. Analyses of strong motion and the correlations of peak ground velocity (PGV) and pipeline and building damage were conducted with a very large geographical information system (GIS) database including the relationship of time and earthquake intensity and the measured location, and Kriging spatial statistics. Kriging was used to develop regressions of pipeline repair rate (RR) and residential building damage ratio (DR) associated with $90\%$ confidence peak ground velocity (PGV). Such regressions using Kriging provide an explicit means of characterizing the uncertainty embodied in the strong motion data compared with other spacial statistics such as inverse distance method.

• Journal of the Korean Geotechnical Society
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• v.22 no.11
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• pp.101-111
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• 2006

Slope stability analysis is a geotechnical engineering problem characterized by many sources of uncertainty. Some of them are connected to the variability of soil properties involved in the analysis. In this paper, a numerical procedure of probabilistic analysis of slope stability is presented based on Spencer's method of slices. The deterministic analysis is extended to a probabilistic approach that accounts fur the uncertainties and spatial variation of the soil parameters. The procedure is based on the first-order reliability method to compute the Hasofer-Lind reliability index and Monte-Carlo Simulation. A probabilistic stability assessment was performed to obtain the variation of failure probability with the variation of soil parameters in homogeneous and layered slopes as an example. The examples give insight into the application of uncertainty treatment to the slope stability and show the impact of the spatial variability of soil properties on the outcome of a probabilistic assessment.

• Journal of the Korean Geotechnical Society
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• v.24 no.5
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• pp.27-35
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• 2008

Geotechnical characteristic values for reliability-based design were analyzed using domestic marine clays. Analysis results indicate that there were close to mean values in oder of Student/Ovesen, Schneider and EN 1990's approach. However, it was found that the EN 1990's approach is inappropriate far estimating geotechnical characteristic value due to low reliability of estimation results. Four approaches had a trend of evaluating characteristic value conservatively with increasing of soil variability. Also, stability and settlement of breakwater subjected to nominal stress with unimproved soft grounds were computed to investigate the effects of estimated characteristic values. In case of using the Schneider's approach, the ratio of allowable bearing capacity/acting loads suggested 65% of that obtained from using the arithmetic mean approach, and showed underestimated value of 13.6% of the settlement obtained from the latter. The comparison of case designs using a representative value from arithmetic mean approach with the proposed approaches, using characteristic value showed that the former was mostly overestimated.

• Journal of the Korean Geotechnical Society
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• v.26 no.12
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• pp.71-79
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• 2010

The reliable evaluation of the coefficient of variation (COV) of soil properties is required for the determination of adequate design values and the application of a probabilistic method for the design of geotechnical structures. In this paper, the applicability of methods for estimating the standard deviation, such as the. Three-Sigma Rule and a statistical method, is evaluated by using site investigation data of the Songdo area. It is found that the Three-Sigma Rule provides similar results to those of a statistical method when using $N_{\sigma}$=6 for the property with small variability and $N_{\sigma}$=4.2~5.3 for the property with large variability. It is also observed that, for the undrained shear strength that has an increasing trend with depth, a $N_{\sigma}$ value of 4 is adequate for the evaluation of the variability by the Three-Sigma Rule. The COVs of soil properties determined in this paper could be used in the estimation of the confidence interval and characteristic values of soil properties.

• Journal of the Korean Geotechnical Society
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• v.27 no.10
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• pp.93-104
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• 2011

In this paper, a numerical procedure of probabilistic steady seepage analysis that considers the spatial variability of soil permeability is presented. The procedure extends the deterministic analysis based on the finite element method to a probabilistic approach that accounts for the uncertainties and spatial variation of the soil permeability. Two-dimensional random fields are generated based on a Karhunen-Lo$\grave{e}$ve expansion in a fashion consistent with a specified marginal distribution function and an autocorrelation function. A Monte Carlo simulation is then used to determine the statistical response based on the random fields. A series of analyses were performed to verify the application potential of the proposed method and to study the effects of uncertainty due to the spatial heterogeneity on the seepage behavior of soil foundation beneath water retaining structure with a single sheet pile wall. The results showed that the probabilistic framework can be used to efficiently consider the various flow patterns caused by the spatial variability of the soil permeability in seepage assessment for a soil foundation beneath water retaining structures.

• Journal of the Korean Geotechnical Society
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• v.25 no.12
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• pp.13-25
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• 2009

In this paper, a numerical procedure of probabilistic slope stability analysis that considers the spatial variability of soil properties is presented. The procedure extends the deterministic analysis based on the limit equilibrium method of slices to a probabilistic approach that accounts for the uncertainties and spatial variation of the soil parameters. Making no a priori assumptions about the critical failure surface like the Random Finite Element Method (RFEM), the approach saves the amount of solution time required to perform the analysis. Two-dimensional random fields are generated based on a Karhunen-Lo$\grave{e}$ve expansion in a fashion consistent with a specified marginal distribution function and an autocorrelation function. A Monte Carlo simulation is then used to determine the statistical response based on the random fields. A series of analyses were performed to verify the application potential of the proposed method and to study the effects of uncertainty caused by the spatial heterogeneity on the stability of slope. The results show that the proposed method can efficiently consider the various failure mechanisms caused by the spatial variability of soil property in the probabilistic slope stability assessment.

• Earthquakes and Structures
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• v.22 no.3
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• pp.219-230
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• 2022

Knowing that the variability of soil properties is an important source of uncertainty in geotechnical analyses, we will study in this paper the effect of this variability on the seismic response of a structure within the framework of Soil Structure Interaction (SSI). We use the proposed and developed model (N2-ISS, Mekki et al., 2014). This approach is based on an extension of the N2 method by determining the capacity curve of the fixed base system oscillating mainly in the first mode, then modified to obtain the capacity curve of the system on a flexible basis using the concept of the equivalent nonlinear oscillator. The properties of the soil that we are interested in this paper will be the shear wave velocity and the soil damping. These parameters will be modeled at first, as independent random fields, then, the two parameters will be correlated. The results obtained showed the importance of the use of random field in the study of SSI systems. The variability of soil damping and shear wave velocity introduces significant uncertainty not only in the evaluation of the damping of the soil-structure system but also in the estimation of the displacement of the structure and the base-shear force.

• Journal of the Korean Geotechnical Society
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• v.24 no.1
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• pp.119-130
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• 2008

Uncertainties in physical and engineering parameters for the design of shallow foundations arise from various aspects such as inherent variability and measurement error. This paper aims at investigating and reducing uncertainty from deterministic method by using the reliability-based design of shallow foundations accounting for the variation of various design parameters. A probability distribution type and statistics of random variables such as unit weight, cohesion, infernal friction angle and Young's modulus in geotechnical engineering are suggested to calculate the ultimate bearing capacities and immediate settlements of foundations. Reliability index and probability of failure are estimated based on the distribution types of random variables. Widths of foundation are calculated at target reliability index and probability of failure. It is found that application and analysis of the best-fit distribution type for each random variables are more effective than adoption of the normal distribution type in optimizing the reliability-based design of shallow foundations.

• Geotechnical Engineering
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• v.4 no.3
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• pp.19-26
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• 1988

A stochastic numerical model for predictions of differential settlement of foundation Eoils is developed in this Paper. The differential settlement is highly dependent on the spatial variability of elastic modulus of soil. The Kriging method is used to account for the spatial variability of the elastic modulus. This technique provides the best linear unbiased estimator of a parameter and its minimum variance from a limited number of measured data. The stochastic finite element method, employing the first-order second-moment analysis for computations of error Propagation, is used to obtain the means, ariances, and covariances of nodal displacements. Finally, a reliability model of differential settlement is proposed by using the results of the stochastic FEM analysis. It is found that maximum differential settlement occurs when the distance between two foundations is approximately same It with the scale of fluctuation in horizontal direction, and the probability that differential settlement exceeds the allot.able vague might be significant.