The Korea Institute of Nuclear Nonproliferation and Control (KINAC) is developing a simulation model to estimate nuclear material production. This model is a foundational technology in interpretation and evaluation in preparation for denuclearization verification. Through this model, it is possible to estimate the amount of nuclear material that can be produced based on information on the activities of facilities related to the nuclear fuel cycle in the actual denuclearization verification stage. This model makes it possible to determine whether the declared amount of nuclear material is reliable. In addition, the reliability of the reported information can be confirmed through on-site inspection. However, there is a possibility that proliferation-related activities cannot be detected even through this inspection, and a normal state may be misdiagnosed as carrying out nuclear proliferation-related activities. Therefore, it is unreasonable to specify activities related to nuclear proliferation with only one inspection. Since each inspection method has its diagnosis rate and false diagnosis rate, measures such as repeating the same inspection method or combining different inspection methods are required to detect activities related to nuclear proliferation reliably. Therefore, a model capable of estimating the number of repetitions to obtain a reliable nuclear activity detection probability was developed by using each inspection method’s diagnosis rate and false diagnosis rate as input information through a Bayesian inference method. Through this model, it can be concluded that repetitive inspections increase the probability of detecting nuclear proliferation-related activities. This approach confirmed the possibility of repeatedly breaking away from the high-intensity inspection method that causes political and diplomatic resistance from the target country and substituting it with a more readily acceptable, low-intensity inspection method.

The objective of this study is to estimate the dietary exposure of polychlorinated dibenzo-p-dioxins and dibezofurans (PCDD/Fs) of Korean population via milk and meat using a probabilistic exposure assessment model. Total 319 raw milk and meat samples collected in the period 2006-2008 from nationwide Korea were measured the concentrations of 17 PCDD/Fs. Distributions of dietary exposure of 7 age subgroups to PCDD/Fs from the commodities were estimated probabilistically using Monte Carlo simulations. Dietary exposure groups were divided as lower, medium and high consumer subgroups according to the consumption of each commodity. The amounts of dietary exposures of Korean population subgroups were compared to the provisional maximum tolerable monthly intake (PTMI) recommended by the Joint FAO/WHO Expert Committee on Food Additives and Contaminants (JECFA). The mean PCDD/Fs concentrations in raw milk and meat of beef, prok and chicken were measured as 0.501, and 0.022~0.150pg WHO-TEQ/g, respectively. Dietary exposure of children was significantly higher than that of adults due to their high milk consumption per body weight (BW). Dietary intake of PCDD/Fs of the Korean populations estimated ranged from 0.154 to 1.248 pg WHO- TEQ/kg BW/day for high consumers (the 97.5th percentile) at the upper bound. Dietary intakes of average population of various subgroups were below the half of PTMI, but those of higher consumers were found exceeding or comparable to PTMI at the upper bound level. This study also suggests that the estimated PCDD/Fs concentrations in milk and meat are comparable to those reported in previous studies. Probabilistic assessment model for PCDD/Fs exposure in meat and milk commodities could be used to estimate the exposure of PCDD/Fs in Korean population for the development of risk mangement mesaures for PCDD/Fs in meat and milk.

이 연구에서는 입력변수의 확률분포로부터 비선형 구조응답의 확률분포 추정방법을 제안한다. 응답함수를 확률변수들의 평균점과 응답의 꼬리부분 상위 0.01%값에 기여하는 확률변수조합에서 각각 1차 테일러급수로 근사한다. 두 응답함수에 대해 모멘트법을 적용한 후 이를 가우시안 분포로 추정한다. 추정된 두 분포를 결합하기 위해 연결함수를 도입하고, 분포의 연속조건을 적용하여 연결함수의 미정계수를 결정한다. 제안된 방법을 케이블 교량 예제에 적용하고, 카이제곱 검증을 이용하여 추정된 분포의 적합성을 확인한다. 기존의 모멘트법과 제안된 방법의 결과를 비교, 분석한다.

In engineering problems, many random variables have correlation, and the correlation of input random variables has a great influence on reliability analysis results of the mechanical systems. However, correlated variables are often treated as independent variables or modeled by specific parametric joint distributions due to difficulty in modeling joint distributions. Especially, when there are insufficient correlated data, it becomes more difficult to correctly model the joint distribution. In this study, multivariate kernel density estimation with bounded data is proposed to estimate various types of joint distributions with highly nonlinearity. Since it combines given data with bounded data, which are generated from confidence intervals of uniform distribution parameters for given data, it is less sensitive to data quality and number of data. Thus, it yields conservative statistical modeling and reliability analysis results, and its performance is verified through statistical simulation and engineering examples.

최근 백두산 화산분화의 전조현상 증가로 인해 백두산 분화의 가능성이 지속적으로 제기되고 있으며 주변국인 일본의 화산 활동 또한 활발한 추세이다. 일본 화산 및 백두산으로부터 500km 이상의 거리에 위치한 우리나라의 경우 화산 분화로부터 근접 재해의 직접적인 위험은 없으나 화산재 확산에 의한 영향을 받을 가능성이 있어 이에 대한 대책 및 대응 방안 마련이 요구되고 있는 실정 이며 이에 대한 대응 방안 중 하나로, 화산재 확산 모델을 이용하여 화산재 입자의 공간분포 예측 및 대기 중 화산재 농도와 지표면의 화산재 퇴적 두께를 예측하는 방법이 있다. 본 연구에서는 화산재 확산 예측 모형에 의해 도출된 대기 중의 화산재 농도와 낙하 화산재 퇴적 두께를 이용하여 한반도 근역에 대하여 화산재 공간 확산 확률 및 낙하 확률 분석 기법을 제시하고 우리나라 17개 광역지자체에 대한 분석을 수행하였다.

PURPOSES : This study estimated the load effect of a single heavy truck to develop a live load model for the design and assessment of bridges located on an expressway with a limited truck entry weight. METHODS: The statistical estimation methods for the live load effect acting on a bridge by a heavy vehicle are reviewed, and applications using the actual measurement data for trucks traveling on an expressway are presented. The weight estimation of a single vehicle and its effect on a bridge are fundamental elements in the construction of a live load model. Two statistical estimation methods for the application of extrapolation in a probabilistic study and an additional estimation method that adopts the extreme value theory are reviewed. RESULTS : The proposed methods are applied to the traffic data measured on an expressway. All of the estimation methods yield similar results using the data measured when the weight limit has been relatively well observed because of the rigid enforcement of the weight regulation. On the other hand, when the estimations are made using overweight traffic data, the resulting values differ with the estimation method. CONCLUSIONS: The estimation methods based on the extreme distribution theory and the modified procedure presented in this paper can yield reasonable values for the maximum weight of a single truck, which can be applied in both the design and evaluation of a bridge on an expressway.

Probabilistic tsunami hazard analysis (PTHA) is based on the approach of probabilistic seismic hazard analysis (PSHA) which is performed using various seismotectonic models and ground-motion prediction equations. The major difference between PTHA and PSHA is that PTHA requires the wave parameters of tsunami. The wave parameters can be estimated from tsunami propagation analysis. Therefore, a tsunami simulation analysis was conducted for the purpose of evaluating the wave parameters required for the PTHA of Uljin nuclear power plant (NPP) site. The tsunamigenic fault sources in the western part of Japan were chosen for the analysis. The wave heights for 80 rupture scenarios were numerically simulated. The synthetic tsunami waveforms were obtained around the Uljin NPP site. The results show that the wave heights are closely related with the location of the fault sources and the associated potential earthquake magnitudes. These wave parameters can be used as input data for the future PTHA study of the Uljin NPP site.

We present a robust power transmission lines detection method based on vanishing point estimation. Vanishing point estimation can be helpful to detect power transmission lines because parallel lines converge on the vanishing point in a projected 2D image. However, it is not easy to estimate the vanishing point correctly in an image with complex background. Thus, we first propose a vanishing point estimation method on power transmission lines by using a probabilistic voting procedure based on intersection points of line segments. In images obtained by our system, power transmission lines are located in a fan-shaped area centered on this estimated vanishing point, and therefore we select the line segments that converge to the estimated vanishing point as candidate line segments for power transmission lines only in this fan-shaped area. Finally, we detect the power transmission lines from these candidate line segments. Experimental results show that the proposed method is robust to noise and efficient to detect power transmission lines.

최근 전력 전송을 위해 지하에 건설되는 전력구 구조물이 증가함에 따라, 이러한 구조물의 수명 연장은 매우 중요한 문제로 대두되고 있다. 현재까지의 현장 및 실험결과들은 콘크리트 내부의 철근이 콘크리트 피복의 탄산화 현상에 의해 부식될 수 있음을 보이고 있으며,이러한 탄산화에 의한 철근의 부식은 구조물 주변의 높은 이산화탄소 농도에 의해 빈번히 발생할 가능성을 내포하고 있다. 따라서, 본 연구에서는 실제 전력구 현장에서의 철근 깊이와 탄산화 깊이를 측정한 결과를 바탕으로 우리나라의 전력구 콘크리트 구조물에 대한 탄산화위험도를 평가하였다. 현장 데이터를 기반으로 철근 주변에서의 탄산화에 의한 전력구의 사용수명을 평가하였으며, 이를 위해 확률론적 방법인 몬테카를로 기법을 적용하였다. 또한 균열을 유발한 시험체에 대한 탄산화 촉진 실험을 수행하여, 그 실험결과를 바탕으로 균열을 고려한 경우의 전력구의 사용수명을 수치적으로 평가하고 분석하였다.

Acoustic signal is crucial for the autonomous navigation of underwater vehicles. For this purpose, this paper presents a method of acoustic source localization. The proposed method is based on the probabilistic estimation of time delay of acoustic signals received by two hydrophones. Using Bayesian update process, the proposed method can provide reliable estimation of direction angle of the acoustic source. The acquired direction information is used to estimate the location of the acoustic source. By accumulating direction information from various vehicle locations, the acoustic source localization is achieved using extended Kalman filter. The proposed method can provide a reliable estimation of the direction and location of the acoustic source, even under for a noisy acoustic signal. Experimental results demonstrate the performance of the proposed acoustic source localization method in a real sea environment.

본 논문에서는 각각의 시점에서의 변화확률을 산정하여 변화시점을 추정하는 Barry and Hartigan (BH)의 베이지안 변화시점 추정방법(Bayesian changing points estimation method)을 이용하여 측우기 관측자료계열(CWK)과 근대우량계 관측자료계열(MRG)간의 변화에 대한 상대확률적 절점의 발생여부를 분석하였다. 어떠한 자연 현상도 완전히 동일하게 재현되지 않기때문에 시간적인 순서를 고려하지못하는 통계적 방법은 구체