• 한국지반공학회논문집
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• 제33권5호
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• pp.25-35
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• 2017

액상화는 지진에 의해 발생하는 대표적인 피해 중 하나로 이에 대한 가능성을 평가하기 위한 많은 방법들이 개발되었으며, 최근에는 지반이 갖는 불확실성을 합리적으로 고려하기 위한 확률론적 접근방법에 대한 연구가 이루어지고 있다. 본 연구에서는 지반의 물성치가 갖는 공간 변동성을 고려하여 확률론적 해석을 수행하고자 서로 다른 변동특성을 갖는 세 지점의 CPT 데이터를 활용하여 콘관입 저항치에 대한 공간 변동성을 평가하였다. 이후, 각 지점의 공간 변동성을 고려한 콘관입 저항치의 확률장을 생성하였으며, CPT기반 액상화 평가방법을 통하여 액상화에 의해 유발되는 침하량의 확률론적 해석을 수행하였다. 연구결과, 공간변동성이 고려되지 않을 경우 지반의 불확실성을 과대평가할 수 있으며, 기준 허용 침하량에 따라 약 30%까지 큰 확률론적 차이가 발생할 수 있는 것으로 나타났다.

• 한국지반공학회논문집
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• 제27권10호
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• pp.93-104
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• 2011

본 연구에서는 댐이나 보와 같은 수리구조물이 설치된 포화 기초지반에서의 구속흐름(confined flow)에 대하여 확률론적 침투해석을 수행하였다. 침투해석은 유한요소법을 이용하였으며 투수계수의 수평방향과 연직방향의 공간적 상관성이 상이한 비등방성을 고려하였다. 지정된 입력 확률분포함수와 자기상관함수(autocorrelation function)를 따르는 2차원의 랜덤필드를 생성하기 위하여 Karhunen-Lo$\grave{e}$ve 전개법을 사용하였으며 생성된 랜덤필드를 이용하여 확률론적 응답을 얻기 위해 Monte Carlo 시뮬레이션을 수행하였다. 이로부터 투수계수의 불확실성과 공간적 변동성이 수리구조물과 기초의 침투로 인한 안정성과 관련된 기초를 통한 유량, 구조물 하부에 작용하는 양압력, 하류 유출면에서의 유출동수경사에 미치는 영향을 연구하였다. 해석결과로부터 투수계수의 확률분포와 자기상관 구조를 만족하는 랜덤필드로 고려하여 공간적 변동을 고려하는 방법은 결정론적 해석이나 투수계수를 하나의 랜덤변수로 고려하는 경우에 나타나지 않는 다양한 지반의 침투거동을 효과적으로 고려할 수 있음을 보여준다.

• Geomechanics and Engineering
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• 제17권1호
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• pp.31-45
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• 2019

In this study the spatial variability of soils is substantiated physically and numerically by using random field theory. Heterogeneous samples are fabricated by combining nine homogeneous soil clusters that are assumed to be elements of an adopted random field. Homogeneous soils are prepared by mixing different percentages of kaolin and bentonite at water contents equivalent to their respective liquid limits. Comprehensive characteristic laboratory tests were carried out before embarking on direct shear experiments to deduce the basic correlations and properties of nine homogeneous soil clusters that serve to reconstitute the heterogeneous samples. The tests consist of Atterberg limits, and Oedometric and unconfined compression tests. The undrained shear strength of nine soil clusters were measured by the unconfined compression test data, and then correlations were made between the water content and the strength and stiffness of soil samples with different consistency limits. The direct shear strength of heterogeneous samples of different stochastic properties was then evaluated by physical and numerical modelling using FISH code programming in finite difference software of $FLAC^{3D}$. The results of the experimental and stochastic numerical analyses were then compared. The deviation of numerical simulations from direct shear load-displacement profiles taken from different sources were discussed, potential sources of error was introduced and elaborated. This study was primarily to explain the mathematical and physical procedures of sample preparation in stochastic soil mechanics. It can be extended to different problems and applications in geotechnical engineering discipline to take in to account the variability of strength and deformation parameters.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2004년도 학술발표회
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• pp.705-708
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• 2004

The spatial variability of the L- and C- band large scale remotely sensed soil moisture data, obtained during tire Southern Great Plain 1999 (SGP'99), was characterized. The results demonstrate that soil moisture data using L-band show the break in statistical symmetry (multiscaling behavior) with the variation of scale of observation, which is similar to that of the soil property such as sand content. Also, soil moisture data using C-band show single scaling behavior with the variation of scale of observation, which Is similar to that of the vegetation condition.

• Geomechanics and Engineering
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• 제17권6호
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• pp.565-572
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• 2019

Spatial variability is an inherent characteristic of soil, and auto-correlation length (ACL) is a very important parameter in the reliability or probabilistic analyses of geotechnical engineering that consider the spatial variability of soils. Current methods for estimating the ACL need a large amount of laboratory or in-situ experiments, which is a great obstacle to the application of random field theory to geotechnical reliability analysis and design. To estimate the ACL reasonably and efficiently, we propose a micro-structure based numerical simulation method. The quartet structure generation set algorithm is used to generate stochastic numerical micro-structure of soils, and scanning electron microscope test of soil samples combined with digital image processing technique is adopted to obtain parameters needed in the QSGS algorithm. Then, 2-point correlation function is adopted to calculate the ACL based on the generated numerical micro-structure of soils. Results of a case study shows that the ACL can be estimated efficiently using the proposed method. Sensitivity analysis demonstrates that the ACL will become stable with the increase of mesh density and model size. A model size of $300{\times}300$ with a grid size of $1{\times}1$ is suitable for the calculation of the ACL of clayey soils.

• Geomechanics and Engineering
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• 제24권2호
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• pp.167-178
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• 2021

Spatial variability is an inherent uncertainty of soil properties. Current reliability analyses generally incorporate random field theory and Monte Carlo simulation (MCS) when dealing with spatial variability, in which the computational efficiency is a significant challenge. This paper proposes a KL-FORM algorithm to improve the computational efficiency. In the proposed KL-FORM, Karhunen-Loeve (KL) expansion is used for discretizing random fields, and first-order reliability method (FORM) is employed for reliability analysis. The KL expansion and FORM can be used in conjunction, through adopting independent standard normal variables in the discretization of KL expansion as the basic variables in the FORM. To illustrate the effectiveness of this KL-FORM, it is applied to a case study of a strip footing in spatially variable unsaturated soil under rainfall, in which the bearing capacity of the footing is computed by numerical simulation. This case study shows that the KL-FORM is accurate and efficient. The parametric analyses suggest that ignoring the spatial variability of the soil may lead to an underestimation of the reliability index of the footing.

• 한국지진공학회논문집
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• 제19권2호
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• pp.63-74
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• 2015

This study investigated the influence of probabilistic variability in stiffness and nonlinearity of soil on response of nuclear power plant (NPP) structure subjected to seismic loads considering the soil-structure interaction (SSI). Both deterministic and probabilistic methods have been employed to evaluate the dynamic responses of the structure. For the deterministic method, $SRP_{min}$ method given in USNRC SRP 3.7.2(2013) (envelope of responses using three shear modulus profiles of lower bound($G_{LB}$), best estimate($G_{BE}$) and upper bound($G_{UB}$)) and $SRP_{max}$ method (envelope of responses by more than three ground profiles within range of $G_{LB}{\leq}G{\leq}G_{UB}$) have been considered. The probabilistic method uses the Latin Hypercube Sampling (LHS) that can capture probabilistic feature of soil stiffness defined by the median and the standard deviation. These analysis results indicated that 1) number of samples shall be larger than 60 to apply the probabilistic approach in SSI analysis and 2) in-structure response spectra using equivalent linear soil profiles considering the nonlinear behavior of soil medium can be larger than those based on low-strain soil profiles.

• Geomechanics and Engineering
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• 제20권1호
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• pp.19-28
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• 2020

The spatial variability of geotechnical properties can lead to the uncertainty of settlement for frozen soil foundation around the oil pipeline, and it can affect the stability of permafrost foundation. In this paper, the elastic modulus, cohesion, angle of internal friction and poisson ratio are taken as four independent random fields. A stochastic analysis model for the uncertain settlement characteristic of frozen soil foundation around an oil pipeline is presented. The accuracy of the stochastic analysis model is verified by measured data. Considering the different combinations for the coefficient of variation and scale of fluctuation, the influences of spatial variability of geotechnical properties on uncertain settlement are estimated. The results show that the stochastic effects between elastic modulus, cohesion, angle of internal friction and poisson ratio are obviously different. The deformation parameters have a greater influence on stochastic settlement than the strength parameters. The overall variability of settlement reduces with the increase of horizontal scale of fluctuation and vertical scale of fluctuation. These results can improve our understanding of the influences of spatial variability of geotechnical properties on uncertain settlement and provide a theoretical basis for the reliability analysis of pipeline engineering in permafrost regions.

• 한국지반공학회논문집
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• 제35권3호
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• pp.37-46
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• 2019

최근 다른 현장시험에 비하여 비교적 정확성이 높은 CPT 기반 액상화 평가법의 사용이 증가하고 있다. CPT 기반 액상화 평가는 다양한 흙의 특성을 예측하고 이를 액상화 평가에 활용할 수 있다. 특히, 세립분 함량은 CPT 기반 액상화 평가에서 중요한 입력 변수 중 하나로 이에 대한 정확한 예측식의 사용 및 예측 변동성을 정량적으로 파악하는 것은 매우 중요하다. 본 연구에서는 2017년 포항지진 시 액상화 현상이 관측된 지점에서 수행된 CPT 자료를 이용하여 기존 세립분 함량 예측식들의 오차를 분석하고 포항지역에 적합한 세립분 함량 예측식을 선정하였다. 또한, 지반의 고유한 변동성을 분석하고 CPT의 측정오차, 선정된 예측식에 대한 변환 불확실성을 고려한 세립분 함량의 예측 변동성을 정량적으로 평가하였다.

• 한국지반공학회논문집
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• 제24권8호
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• pp.111-123
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• 2008

지반공학 문제는 많은 불확실한 요인을 내포한다. 이러한 불확실성 중 일부는 해석 수행과정에 필요한 지반 물성의 변동성과 관련이 있다. 본 연구에서는 지반물성의 공간적 변동성을 고려한 확률론적 해석을 수행할 수 있는 절차를 제시하였다. 제시된 방법은 유한차분 해석기법과 랜덤필드 이론을 확률론적 해석기법에 통합하게 된다. 지정된 입력 확률분포함수와 자기상관함수를 따르는 non-Gaussian 랜덤필드를 생성하기 위하여 Karhunen-$Lo{\grave{e}}ve$ 전개법을 사용하였다. 생성된 랜덤필드를 이용하여 확률론적 응답을 얻기 위해 Monte Carlo 시뮬레이션을 수행하였다. 지반의 공간적인 변동성에 기인하는 불확실성의 효과를 연구하기 위하여 대상 기초의 침하량과 지지력에 대한 일련의 해석을 수행하였다. 해석결과는 지반공학 문제에서 불확실성을 고려할 수 있는 관점을 제시하며 확률론적 평가의 결과에 미치는 지반물성의 공간적 변동성의 중요성을 보여준다.