• 한국수자원학회논문집
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• 제52권9호
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• pp.627-635
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• 2019

우리나라에서도 최근 들어 과거 눈이 내리지 않던 지역에 폭설이 내리거나 대설에 의한 인명피해가 발생하는 등의 설해가 발생하였다. 이에 자연재해저감 종합계획에 대설에 의한 설해 대비를 포함하는 등의 정책적인 변화가 생겼으나, 우리나라는 그동안 대설 피해가 많지 않았었기 때문에 대설이나 적설 자료의 특성에 대한 연구를 다양한 각도에서 수행한 적이 거의 없다. 우리나라의 적설자료는 강우자료와 특성이 다른 경우가 많다. 예를 들어, 우리나라 남해안 일부 지역은 연중 눈이 한 번도 내리지 않는 경우가 다수 있어, 연최대치계열 자료 중에 값이 없는 경우가 빈번히 존재하는 등 중도절단 자료(censored data)와 비슷한 특성을 가진다. 실제로 부산 지점은 적설관측시 시작된 이후 연최대치계열 자료의 값이 없는 경우가 전체 시계열의 36% 이상이었다. 그럼에도 불구하고 적설자료의 빈도해석은 기존 강우자료의 빈도해석 절차에 준해 시행되는 경우가 대부분이었다. 연최대치계열 자료가 존재하지 않는 경우, 기존의 빈도해석 방법을 적용하기 위해 자료가 존재하지 않는 기간에 대해 0으로 가정하여 빈도해석을 수행하거나 해당기간을 제외하고 빈도해석을 수행할 수 있다. 그러나 두 가지 경우 모두 구해진 확률분포의 적합도가 매우 낮은 경우가 존재했다. 그러므로 본 연구에서는 우리나라 적설자료의 특성을 고려하기 위해 조건부결합확률분포를 이용하여 확률밀도함수를 선정하는 방법을 제안하였다. 그 결과 기본 방법에 비해 적합도가 더 높은 확률밀도함수를 구할 수 있었으며, 100년 빈도 이상의 고빈도에서 기존 방법에 비해 대체로 적설심이 작아지는 경향을 보였으며, 최대 15%의 차이를 보였다. 눈의 단위중량에 따라 지역별로 하중은 달라질 수 있으며 그 영향의 크기가 달라질 수 있으나, 본 연구의 결과는 건축물의 설계기준에도 영향을 미칠 수 있고, 재해저감을 위한 대책 수립에도 큰 기여를 할 수 있을 것이다.

• 한국방사성폐기물학회:학술대회논문집
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• 한국방사성폐기물학회 2009년도 학술논문요약집
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• pp.186-186
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• 2009

The characterization strategy of fracture networks are classified into a deterministic or statistical characterization according to the type of required information. A deterministic characterization is most efficient for a sparsely fractured system, while the statistics are sufficient for densely fractured rock. In this study, the ensemble mean and variability of the effective connectivity is systematically analyzed with various density values for different network structures of a power law size distribution. The results of high resolution Monte Carlo analyses show that statistical characteristics can be a necessary information to determine the transport properties of a fracture system when fracture density is greater than a percolation threshold. When the percolation probability (II) approaches unity with increasing fracture density, the effective connectivity of the network can be safely estimated using statistics only (sufficient condition). It is inferred from conditional simulations that deterministic information for main pathways can reduce the uncertainty in estimation of system properties when the network becomes denser. Overall results imply that most pathways need to be identified when II < 0.5 statistics are sufficient when II $\rightarrow$ 1 and statistics are necessary and the identification of main pathways can significantly reduce the uncertainty in estimation of transport properties when 0.5$\ll$1. It is suggested that the proper estimation of the percolation probability of a fracture network is a prerequisite for an appropriate conceptualization and further characterization.

• 한국전산구조공학회논문집
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• 제23권6호
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• pp.641-649
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• 2010

Estimation of uncertain parameters is required in many engineering problems which involve probabilistic structural analysis as well as prognosis of existing structures. In this case, Bayesian framework is often employed, which is to represent the uncertainty of parameters in terms of probability distributions conditional on the provided data. The resulting form of distribution, however, is not amenable to the practical application due to its complex nature making the standard probability functions useless. In this study, Markov chain Monte Carlo (MCMC) method is proposed to overcome this difficulty, which is a modern computational technique for the efficient and straightforward estimation of parameters. Three case studies that implement the estimation are presented to illustrate the concept. The first one is an inverse estimation, in which the unknown input parameters are inversely estimated based on a finite number of measured response data. The next one is a metamodel uncertainty problem that arises when the original response function is approximated by a metamodel using a finite set of response values. The last one is a prognostics problem, in which the unknown parameters of the degradation model are estimated based on the monitored data.

• 산업공학
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• 제24권2호
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• pp.119-127
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• 2011

Most companies have been increasing temporary work projects to maximize the usage of their resources. They also have been developing the effective techniques for analyzing and managing the state of the projects. In order to monitor the state of a project in real-time and predict the project's future state more accurately, this paper suggests the Bayesian Network (BN) as a tool for discovering the causes of project risk and presenting the failure probability of the project. The proposed BN modeling method with consideration of the Earned Value Management (EVM) method shows how to induce the predictive and conditional probability of the risk occurrence in the future. The advantages of the suggested model are (1) that the cause of a project risk can be easily figured out via the BN, (2) that the future value of the project can be sufficiently increased by updating relevant components of the project, and (3) that more credible prediction can be made in the similar and future situation by using the data obtained in current analysis. A numerical example is also given.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2143-2147
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• 2005

Human-Robot interaction (HRI) has recently become one of the most important issues in the field of robotics. Understanding and predicting the intentions of human users is a major difficulty for robotic programs. In this paper we suggest an interaction method allows the robot to execute the human user's desires in an intelligent room-based domain, even when the user does not give a specific command for the action. To achieve this, we constructed a full system architecture of an intelligent room so that the following were present and sequentially interconnected: decision-making based on the Bayesian belief network, responding to human commands, and generating queries to remove ambiguities. The robot obtained all the necessary information from analyzing the user's condition and the environmental state of the room. This information is then used to evaluate the probabilities of the results coming from the output nodes of the Bayesian belief network, which is composed of the nodes that includes several states, and the causal relationships between them. Our study shows that the suggested system and proposed method would improve a robot's ability to understand human commands, intuit human desires, and predict human intentions resulting in a comfortable intelligent room for the human user.

• 산업경영시스템학회지
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• 제30권3호
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• pp.103-108
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• 2007

This paper presents the conceptual framework for estimating and predicting system's susceptibility to failure as function of condition parameter value which is representing the current status of performance measure using on-line performance reliability. The performance of such system depends on one parameter with a probability distribution that degrades with time gracefully. Performance reliability represents the probability that physical performance will remain satisfactory over a finite period of time or usage cycles in the future. An empirical physical performance function is constructed to incorporate explanatory variables (operating and environmental conditions) over a time or usage dimension. This function enables one to model device performance and the associated classical reliability measures simultaneously, in the performance domain and time domain. The conditional performance reliability structure developed represents a tool to predict system performance over time or usage for next usage period. By enabling such a framework, it can bring us more efficient planning and execution in system's operation control as well as maintenance to reduce costs and/or increase profits.

• 응용통계연구
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• 제33권4호
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• pp.439-449
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• 2020

메타 분석은 여러 연구 결과들을 종합시켜주는 분석 방법 중 하나이다. 이 때 수집되는 연구 문헌들은 소규모 연구인 경우 통계적으로 유의한 결과를 보이는 연구가 출간될 확률이 높기 때문에, 선택 편향의 특수한 경우인 출판 편향이 종종 발생한다. 선택 편향을 보정하는 방법에는 조건부 가능도와 가중 추정 방정식이 있는데 이 방법들은 실제 얻기 힘든 정확한 선택 확률 모형을 필요로한다. 반면 쌍별 유사가능도 접근법은 선택 확률 모형을 정확히 알 수 없는 경우에도 선택 편향을 보정할 수 있는 방법으로 제안되었다. 본 논문은 메타분석에서 쌍별 유사가능도 접근법의 성능과 문제점을 수치적으로 연구한다.

• Nuclear Engineering and Technology
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• 제46권5호
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• pp.699-706
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• 2014

The probabilistic seismic performance of a standard Korean nuclear power plant (NPP) with an idealized isolation is investigated in the present work. A probabilistic seismic hazard analysis (PSHA) of the Wolsong site on the Korean peninsula is performed by considering peak ground acceleration (PGA) as an earthquake intensity measure. A procedure is reported on the categorization and selection of two sets of ground motions of the Tohoku earthquake, i.e. long-period and common as Set A and Set B respectively, for the nonlinear time history response analysis of the base-isolated NPP. Limit state values as multiples of the displacement responses of the NPP base isolation are considered for the fragility estimation. The seismic risk of the NPP is further assessed by incorporation of the rate of frequency exceedance and conditional failure probability curves. Furthermore, this framework attempts to show the unacceptable performance of the isolated NPP in terms of the probabilistic distribution and annual probability of limit states. The comparative results for long and common ground motions are discussed to contribute to the future safety of nuclear facilities against drastic events like Tohoku.

• 한국국방경영분석학회지
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• 제28권2호
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• pp.70-84
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• 2002

This paper deals with the attrition rate of major facility such as a particular building that is one of the most important target in the war time. In order to estimate the attrition rate, we use JAWS, WinJMEM which are programed by JTCG/ME of AMSAA and spreadsheet package which is able to assist the limitation of those programs and calculate all the procedure of this computation. This method uses the effectiveness index(El) which indicates the numerical measure of the effectiveness of a given weapon of a given target. The range error probable(REP) and the deflection error probable(DEP) in the ground plane also should be used. Those mean the measure of delivery accuracy of the weapon system. In this paper, it is improved that the El can be obtained from the regression analysis using the weight of the warhead explosive as the independent variable. It implies that we are able to obtain the El and the conditional probability of damage of the enemy weapon. After that, the single-sortie probability of damage can be computed using WinJMEM or another assistant program such as the spreadsheet package which shows the result immediately.

• Nuclear Engineering and Technology
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• 제54권3호
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• pp.948-958
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• 2022

Since reliability and security of man-machine system increasingly depend on reliability of human, human reliability analysis (HRA) has attracted a lot of attention in many fields especially in nuclear engineering. Dependence assessment among human tasks is a important part in HRA which contributes to an appropriate evaluation result. Most of methods in HRA are based on experts' opinions which are subjective and uncertain. Also, the dependence influencing factors are usually considered to be constant, which is unrealistic. In this paper, a new model based on Dempster-Shafer evidence theory (DSET) and fuzzy number is proposed to handle the dependence between two tasks in HRA under uncertain and dynamic situations. First, the dependence influencing factors are identified and the judgments on the factors are represented as basic belief assignments (BBAs). Second, the BBAs of the factors that varying with time are reconstructed based on the correction BBA derived from time value. Then, BBAs of all factors are combined to gain the fused BBA. Finally, conditional human error probability (CHEP) is derived based on the fused BBA. The proposed method can deal with uncertainties in the judgments and dynamics of the dependence influencing factors. A case study is illustrated to show the effectiveness and the flexibility of the proposed method.