• Fire Science and Engineering
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• v.8 no.2
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• pp.58-63
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• 1994

독일 원자력 발전소에서는 포괄적인 방화 연구의 한 부분으로써 방화에 관한 분석과 그것을 최적화 할 수 있는 확률론적 방법을 개발하였다. 그 일반적인 흐름을 살펴보면, 미국의 화재 위험성 분석의 방법을 따랐으며, 세밀한 부분에서는 약간의 수정을 한 것이다. 먼저, 선정된 공장지역에서의 화재 사건 경로(fire event tree)는 화재가 발생했을 때, 방화 조치와 안전시스템을 능 수동적으로 고려해서 설정된다. 방화 조치와 안전 시스템에 있어서의 실패 모델(failure model)은 발화 후 시간과 화재 영향과 같은 일상적인 변수와 관련해서 생긴다. 이러한 관련성은 일차(first-order) 시스템의 신뢰성 이론을 적절히 이용해서 화재 사건 경로를 분석할 때 알 수 있다. 더불어 화재가 발생했을 떠 방화 시스템의 실패 빈도, event paths의 상대적인 비중, 이러한 path내에서의 방화 조치 그리고 실패모델의 변수 등은 모두 시간 함수로 계산된다. 이러한 자료에 근거를 두고, 방화의 최적화는 주로 event path, 방화조치와 비중이 가장 큰 변수를 수정함으로써 가능하게 된다. 이것은 독일의 1300 MW PWR reference plant를 예를 들어서 증명될 것이다. 또한 충고를 받아들여서 수정을 하는 것은 발전소 직원과 화재 피해의 위험성을 줄일 수 있다는 것을 보여주고 있다.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.05a
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• pp.99-100
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• 2006

철도안전법의 제정 및 시행에 즈음하여 철도안전관리에 대한 인식이 제고되고 있는 시점에서 인적요소를 고려한 전기철도안전관리기법을 제시한다. 이를 위해서는 인적신뢰성분석이 필요하나 현재로서는 세계적으로도 이에 관한 규격이 정비되어 가고 있는 실정으로서 국내에서는 규격 적합성 인증 제도가 아직 구축되어 있지 못하고 따라서 규격 정비의 진행에 따라 위험성정보교환에 관련된 대책의 필요성이 증가하고 안전성의 확률론적 정량적평가가 보다 중요시 될 것으로 예상된다. 본고에서는 시스템 위험도분석을 통한 안전공학적 절차를 준수함으로써 위험도를 정량적으로 평가하고 정량적으로 평가된 위험도를 적정 수준으로 관리함으로써 철도시스템 안전관리체계를 향상시킬 수 있는 기법으로서 최근 주목받고 있는 인적신뢰성분석기법과 위험도정보교환에 대한 기본 개념을 제시한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.155-163
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• 2019

The knowledge about drought propagation is very important in accurate estimation of hydrological drought characteristics and efficient development of early warning system. This study investigated a probabilistic relationship of drought propagation based on Bayesian network model for historic period and for future projection under climate change scenario RCP 8.5 over the Han River basin. The results revealed that the propagation rate and lag time have increasing and decreasing trends from the historic period of 1967-2013 to the future periods of 2014-2053 and 2054-2100 under climate change, respectively. The probabilistic results of Bayesian model revealed that the probability of occurrence of lag time varied spatially and decreased when the intensity of meteorological drought changed from moderate to severe and extreme condition during 1967-2013. The values of probability increased in the first future period of 2014-2053 in several sub-basins and slight decreased in the second period of 2054-2100. The proposed probabilistic results will be useful for the decision makers to develop related policies with an appropriate insight toward the future drought status.

• Journal of the Korea institute for structural maintenance and inspection
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• v.21 no.2
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• pp.46-52
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• 2017

Recently durability design based on deterministic or probabilistic method has been attempted since service life evaluation in RC(Reinforced Concrete) structure exposed to chloride attack is important. The deterministic durability design contains a reasonable method with time effect on surface chloride content and diffusion coefficient, however the probabilistic design procedure has no consideration of time effect on both. In the paper, a technique on PDF(Probability of Durability Failure) evaluation is proposed considering time effect on diffusion and surface chloride content through equivalent surface chloride content which has same induced chloride content within a given period and cover depth. With varying period to built-up from 10 to 30 years and maximum surface chloride content from $5.0kg/m^3$ to $10.0kg/m^3$, the changing PDF and the related service life are derived. The proposed method can be reasonably applied to actual durability design with preventing conservative design parameters and considering the same analysis conditions of the deterministic method.

• Journal of the Korea Concrete Institute
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• v.18 no.1 s.91
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• pp.101-108
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• 2006

Accurate prediction of time-dependent column shortening is essential for tall buildings in both strength and serviceability aspects. The uncertainty associated with assumed values for concrete properties such as strength, creep, and shrinkage coefficients should be considered for the prediction of time-dependent column shortening of tall concrete buildings. In this study, the column shortenings of 41-story tall concrete building are predicted using monte carlo simulation technique based on the probabilistic analysis. The probabilistic column shortenings considering confidence intervals are compared with the actual column shortenings by field measurement. The time-dependent strains measured at tall bearing wall building were generally lower than the predicted strains and the measured values fell within a range ${\mu}-1.64$, confidence level 90%.

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

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.319-326
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• 2015

Recently in the fields o f stochastic optimal control ( SOC) and reinforcemnet l earning (RL), there have been a great deal of research efforts for the problem of finding data-based sub-optimal control policies. The conventional theory for finding optimal controllers via the value-function-based dynamic programming was established for solving the stochastic optimal control problems with solid theoretical background. However, they can be successfully applied only to extremely simple cases. Hence, the data-based modern approach, which tries to find sub-optimal solutions utilizing relevant data such as the state-transition and reward signals instead of rigorous mathematical analyses, is particularly attractive to practical applications. In this paper, we consider a couple of methods combining the modern SOC strategies and approximate inference together with machine-learning-based data treatment methods. Also, we apply the resultant methods to a variety of application domains including financial engineering, and observe their performance.

• The Journal of Engineering Geology
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• v.20 no.2
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• pp.155-167
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• 2010

In analysis of slope stability, deterministic analysis which yields a factor of safety has been used until recently. However, probability of failure is considered as a more efficient method because it deals with the uncertainty and variability of rock mass. In both methods, a factor of safety or a probability of failure is calculated for a slope although characteristics of rock mass, such as characteristics of joints, weathering degree of rock and so on, are not uniform throughout the slope. In this paper, we divided a model slope into several zones depending on conditions of rock mass and joints, and probabilities of failure in each zone are calculated and compared with that calculated in whole slope. The persistence of joint was also used as a parameter in calculation of probability of failure. A rock slope located in Hongcheon, Gangwondo was selected and the probability of failure using zoning and persistence as parameter was calculated to confirm the applicability of model analysis.

• Economic and Environmental Geology
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• v.41 no.6
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• pp.763-771
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• 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 Society of Propulsion Engineers
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• v.22 no.2
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• pp.131-137
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• 2018

This paper analyzes the probability of failure for the equivalence ratio error. The control error of the equivalence ratio is affected by the aleatory and epistemic uncertainties. In general, reliability analysis techniques are easily incorporated to handle the aleatory uncertainty. However, the epistemic uncertainty requires a new approach, as it does not provide an uncertainty distribution. The Bayesian inference incorporates the reliability analysis results to handle both uncertainties. The result gives a distribution of failure probability, whose equivalence ratio does not meet the requirement. This technique can be useful in the analysis of most engineering systems, where the aleatory and epistemic uncertainties exist simultaneously.