• Tunnel and Underground Space
• /
• v.22 no.2
• /
• pp.86-92
• /
• 2012

Point estimate method has a less accuracy than Monte Carlo simulation that is usually considered as an exact probabilistic method, but this method still remains popular in probability-based reliability assessment in geotechnical and rock engineering, because it significantly reduce the number of sampling points and produces the statistical moments of a performance function in a reasonable accuracy. In the present study, we investigated the accuracy and applicability of point estimate methods proposed by Rosenblueth and Zhou & Nowak by comparing the results of these two methods with those of Monte Carlo simulations. The comparison was carried out for the problem of a lined circular tunnel in an elastic medium where an closed-form analytical solution is given. The comparison results showed that despite the non-linearity of the analytical solution, the statistical moments calculated by the point estimate methods and the Monte Carlo simulations agreed well with an average error of roughly 1-2%. This average error demonstrates the applicability of the two point estimate methods for the probabilistic reliability assessment of underground structures in combination with numerical analysis.

• Proceedings of the KSEEG Conference
• /
• 2003.04a
• /
• pp.165-168
• /
• 2003

최근 사면의 안정해석분야에서 자주 사용되고 있는 확률론적 해석 방법은 현장에서 획득 되는 자료들의 분산이 심하고 충분한 양의 자료가 획득되지 못할 경우 자료 내에 포함되는 불확실성과 가변성을 효과적으로 다룰 수 있는 방법 중의 하나로 인식되어 왔다. 그러나 대개 확률론적 해석 방법에서 이용되는 몬테카를로 시뮬레이션기법(Monte Carlo simulation method)은 파괴확률을 산정하기 위하여 수 많은 반복적인 계산과정이 요구되며 따라서 많은 시간과 노력이 필요하다는 단점을 가지고 있다. (중략)

• Tunnel and Underground Space
• /
• v.12 no.3
• /
• pp.189-197
• /
• 2002

In recent years, the probabilistic analysis has been used in rock slope engineering. This is because uncertainty is pervasive in rock slope engineering and most geometric and geotechnical parameters of discontinuity and rock masses are involved with uncertainty. Whilst the traditional deterministic analysis method fails to properly deal with uncertainty, the probabilistic analysis has advantages quantifying the uncertainty in parameters. As a probabilistic analysis method, the Monte Carlo simulation has been used commonly. However, the Monte Carlo simulation requires many repeated calculations and therefore, needs much effort and time to calculate the probability of failure. In contrast, the point estimate method involves a simple calculation with moments for random variables. In this study the probability of failure in rock slope is evaluated by the point estimate method and the results are compared to the probability of failure obtained by Monte Carlo simulation method.

• The Journal of Engineering Geology
• /
• v.11 no.2
• /
• pp.153-161
• /
• 2001

The quantitative evaluation of the stereo graphic projection, the limit equilibrium analysis, the finite difference analysis, the distinct element methocI is a analytical evaluation using many variables. Through the reliability analysis by the point estimation technique, uncertainty of other variables that have an effect on the stability of the rock slo~ was considered. The organized evaluation method of the approximate reasoning concept and using a fuzzy language was developed to confer and analysis the failure factors in planning and constructing the rock slope. Considering the result of the an- alysis, it was demonstrated that stability of entire sections can be evaluated through reliability analysis of point estimation technique. The results of stability evaluation by Fuzzy Approximate Reasoning is generally identical with the results of other existirw; analyses. As mentioned above, general and organized evaluation of special qualities of rock slope is possible using RMR Classification, Stereo Graphic Projection, Limit Equilibriwn Analysis, Finite Difference Analysis, Distinct Element Method, Point Estimation Technique, and Fuzzy Approximate Reasoning.

• Proceedings of the KSEEG Conference
• /
• 2007.04a
• /
• pp.631-633
• /
• 2007

• Tunnel and Underground Space
• /
• v.20 no.1
• /
• pp.39-48
• /
• 2010

The present study developed a program which can assess the reliability of tunnel support systems based on a probability-based method. The developed program uses FLAC2D as a solver, and can automatically execute all the processes, associated with numerical and probabilistic analysis. Since a numerical analysis, which models the ground, requires a significant calculation time, it is actually impossible to apply simulation-based methods to probabilistic assessment on the reliability of tunnel support systems. Therefore, the present study used a point estimate method, which is efficient for probabilistic analysis since the method can significantly reduce the number of samples when compared with the simulation-based method. The developed program was applied to a tunnel project, and the results were compared with those through a deterministic approach. From the comparison, it was identified that a probabilistic approach can quantitatively assess the reliability of tunnel support systems based on probability of failure and can be used as a tool for decision making in tunnel support designs.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2004.03b
• /
• pp.319-326
• /
• 2004

Uncertainty is inevitably involved in rock slope engineering since the rock masses are formed by natural process and subsequently the geotechnical characteristics of rock masses cannot be exactly obtained. Therefore the reliability analysis method has been suggested to deal properly with uncertainty. The reliability analysis method can be divided into level I, II and III on the basis of the approach for consideration of random variable and probability density function of reliability function. The level II approach, which is focused in this study, assumes the probability density function of random variables as normal distribution and evaluates the probability of failure with statistical moments such as mean and standard deviation. This method has the advantage that can be used the problem which the Monte Carlo simulation approach cannot be applied since the complete information on the random variables are not available. In this study, the analysis results of level II reliability approach compared with the analysis results of level III approach to verify the appropriateness of the level II approach. In addition, the results are compared with the results of the deterministic analysis.

• Economic and Environmental Geology
• /
• v.41 no.6
• /
• pp.763-771
• /
• 2008

Uncertainties are pervasive in engineering geological problems. Therefore, the presence of uncertainties and their significance in analysis and design of slopes have been recognized. Since the uncertainties cannot be taken into account by the conventional deterministic approaches in slope stability analysis, the probabilistic analysis has been considered as the primary tool for representing uncertainties in mathematical models. However, some uncertainties are caused by incomplete information due to lack of information, and those uncertainties cannot be handled appropriately by the probabilistic approach. For those uncertainties, the theory of fuzzy sets is more appropriate. Therefore, in this study, fuzzy reliability analysis has been proposed in order to deal with the uncertainties which cannot be quantified in the probabilistic analysis due to the limited information. For the practical example, a slope is selected in this study and both the probabilistic analysis and the fuzzy reliability analysis have been carried out for planar failure. In the fuzzy reliability analysis, the dip angle and internal friction angle of discontinuity are considered as triangular fuzzy numbers since the random properties of the variables cannot be obtained completely under the conditions of limited information. In the study, the fuzzy reliability index and the probabilities of failure are evaluated from fuzzy arithmetic and compared to those from the probabilistic approach using Monte Carlo simulation and point estimate method. The analysis results show that the fuzzy reliability analysis is more appropriate for the condition that the uncertainties arise due to incomplete information.

• Journal of the Korean Geotechnical Society
• /
• v.23 no.11
• /
• pp.109-117
• /
• 2007

Uncertainty is pervasive in rock slope stability analysis due to various reasons and subsequently it may cause serious rock slope failures. Therefore, the importance of uncertainty has been recognized and subsequently the probability theory has been used to quantify the uncertainty since 1980's. However, some uncertainties, due to incomplete information, cannot be handled satisfactorily in the probability theory and the fuzzy set theory is more appropriate for those uncertainties. In this study the random variable is considered as fuzzy number and the fuzzy set theory is employed in rock slope stability analysis. However, the previous fuzzy analysis employed the approximate method, which is first order second moment method and point estimate method. Since previous studies used only the representative values from membership function to evaluate the stability of rock slope, the approximated analysis results have been obtained in previous studies. Therefore, the Monte Carlo simulation technique is utilized to evaluate the probability of failure for rock slope in the current study. This overcomes the shortcomings of previous studies, which are employed vertex method. With Monte Carlo simulation technique, more complete analysis results can be secured in the proposed method. The proposed method has been applied to the practical example. According to the analysis results, the probabilities of failure obtained from the fuzzy Monte Carlo simulation coincide with the probabilities of failure from the probabilistic analysis.