4차 산업혁명의 도래로 인한 기술혁신은 자율운항선박을 중심으로 해상 운송분야까지 활발한 발전을 불러왔다. 특히, 현재의 선원이 직접 운항하는 방식인 유인선박 사이에서 운항하게 될 자율운항선박은 자율도에 따라 원격제어를 통해 운항을 수행하며, 육상에 서 이를 제어할 원격운항자에 대한 관심 또한 늘어나고 있다. 하지만 아직 원격운항자가 개입이 필요한 상황이 동시에 발생하는 등을 고 려한 원격운항자 최소 인력 요구사항에 대한 연구는 부족한 상황이다. 본 연구는 특정 해역 구간의 누적된 항적데이터를 활용하여 선박 간에 발생할 수 있는 조우상황에서 원격운항자의 개입이 필요한 상황을 정의하고, 해당 구간을 특정 규모의 자율운항선박 선대로 운항하 였을 때, 원격운항자의 개입이 동시에 필요한 상황이 얼마나 발생하는지를 시뮬레이션을 통해 확인하였다. 연구의 결과는 향후 실제 자율 운항선박 선대를 운행할 원격운항센터의 원격운항자의 적정인력 배치 등의 계획 또는 정책 수립에 활용될 기초 자료로 활용될 것으로 기 대한다.

For safe and economical spent fuel management, assessing the integrity of the cladding, which is the first barrier to the escape of radioactive material, is very important. For the sake of risk assessment, it is essential to calculate the probability of failure of the spent fuel rods loaded inside the cask during the transportation or storage. However, due to the large amounts of calculations required, it is not practical to analyze every detail of the spent fuel rods and assemblies. This study presents a methodology to perform a cask-level analysis by sequentially simplifying the fuel rods and spent fuel assemblies for the calculation of fuel rod failure probability. A simplified single fuel rod model was generated by considering the material properties of a high burnup fuel rod stored in dry storage for approximately 5 years and the interfacial bonding conditions of the cladding tube. The simplified model produces the same deflection as the detailed model at the critical moment that produces a fracture plastic strain of 1%. The developed single fuel rod simplified model is assembled in a CE 16×16 configuration, and a methodology is presented in which the CE 16×16 assembly model is once again replaced by a simplified model with a cuboidal shape. Compression analyses were performed on each part of the CE 16×16 model to obtain isotropic property data, and a simplified model was created based on those data and the cross-sectional second moment values of the parts. A cask drop analysis was performed to validate the similarity of the CE 16×16 model and the simplified model by comparing important structural responses such as impact acceleration. The 20 simplified fuel assembly models and one detailed model were loaded into a cask to perform the drop analysis. For the detailed model, the impact acceleration was extracted for different loading positions and the corresponding impact load and pinch load were derived. The spring force and contact force corresponding to the pinch load were extracted by applying a Python script technique to extract the maximum value of them exerted on each fuel rod. The vulnerability of spent fuel rods to bending loads and the failure criteria were considered during the simplification process of a single fuel rod. From the extracted impact and pinch loads, the probability of failure of the spent fuel rods as a function of impact acceleration can be calculated.

국내외로 태풍, 홍수, 화산, 지진, 해일 등의 자연재난에 의하여 인명, 재산 피해가 지속적으로 발생하고 있으며 특히 최근에 는 황사, 미세먼지와 같은 입자상 오염물질의 확산이 가속되고 있어 입자상 물질 확산의 예측 및 대응 기술 대한 요구가 높아지고 있는 실정이다. 이와 같은 입자상 물질 관련 재난에 대응하기 위하여 수치 모델을 사용하여 입자상 물질의 확산 경로 및 농도를 예측하는 연구들을 진행하고 있으며, 본 연구에서는 선행연구로 라그랑지안 모델 중 하나인 PUFF-UAF 모델을 개선하여 개발된 PUFFGaussian 모델을 이용하여 연구를 진행하였다. PUFF-Gaussian 모형을 이용하여 온타케 화산의 분화 결과와 검증을 수행하여 유사한 결과가 도출되는 것을 확인하고 백두산 분화에 대한 화산재 확산 예측을 수행하였다. 또한 국내 17개 시·도에 대하여 기존 PUFF-UAF 모델의 결과를 이용하여 계산한 화산재 발생 확률과 PUFF-Gaussian을 이용하여 계산한 발생 확률에 대한 비교를 수행하고 PUFFGaussian 모델을 이용한 결과가 발생 확률이 더 낮은 것을 확인하였다.

본 연구는 국내 냉동보관창고 보관온도에 대한 조사자료를 활용하여, 온도분포를 추정하였고 이를 미생물 위해 평가(microbial risk assessment; MRA)의 입력변수로 활용 할 수 있도록 적정 확률분포 모델을 제시하였다. 조사에 참여한 8곳의 냉동보관창고에서 측정된 공간상의 온도는 최저 -25.8oC, 최고 -10.3oC, 평균 -20.48 ± 3.08oC이었으며, - 18oC이상의 냉동창고 비율은 20.4%로 조사되었다. 공간별 온도분포는 자연대류를 이용하는 냉동창고의 경우 상단 (2.4~4 m) -22.57 ± 0.84oC, 중단(1.5~2.4 m) -22.49 ± 1.05oC, 하단(0.7~1.5 m) -22.68 ± 1.03oC, 최고온도차이는 1.78oC이 었으며, 강제대류를 이용하는 냉동창고의 온도분포는 상단 (2.4~4 m) -17.81 ± 1.47oC, 중단(1.5~2.4 m) -17.94 ± 1.44oC, 하단(0.7~1.5 m) -18.08 ± 1.42oC, 최고온도차이는 0.94oC로 조사되었다. 보관온도는 냉동창고 모든 공간에서 온도가 일정하게 유지되는 것이 아니라 편차가 존재하는 것으로 나타났다. 이상의 수집된 온도자료는 @RISK를 이용, 적합성 검정(GOF: A-D, K-S test)을 수행하여, MRA에서 활용할 수 있는 국내 냉동보관창고 온도분포에 대한 가장 적합한 확률분포모델로 Lognormal [5.9731,3.3483, shift(-26.4281)] 이 선정하였다.

본 연구에서는 신갈나무와 졸참나무 임분의 입지환경인자 및 기후인자 자료를 활용하여 출현확률을 평가하였으며, 자료 분석은 Binary logit model을 이용하였다. 추정 결과, 신갈나무는 해발이 높고, 산복이나 산정의 지형에서 확률이 높게 나타난 반면 졸참나무는 대체로 해발고가 높지 않으며, 평탄지와 완구릉지에 비하여 산록과 산복의 지형에서 확률이 증가되는 경향이 나타났다. 그 외 적색산림토양군의 토성을 가지는 지형과 점토군이 아닌 미사군과 모래군으로 갈수록 출현확률이 높아지는 공통적인 특성이 나타났다. 본 연구의 결과는 장기적인 산림경영 측면에서 조림수종 선정에 유용하게 활용 될 수 있을 것으로 사료된다.

It was confirmed that the extreme value distribution model applies to probability of exceeding more than once a day monthly the facility capacities using data of daily maximum inflow rate for 7 wastewater treatment plant. The result of applying the extreme value model, A, D, E wastewater treatment plant has a problem compared to B, C, F, G wastewater treatment plant. but all the wastewater treatment plant has a problem except C, F wastewater treatment plant based 80% of facility capacity. In conclusion, if you make a standard in statistical aspects probability exceeding more than once a day monthly can be ‘exceed day is less than a few times annually’ or ‘probability of exceeding more than once a day monthly is less than what percent’.

This study was to present the proper probability distribution models that based on the data for surveys of food cold storage temperatures as the input variables to the further MRA (Microbial risk assessment). The temperature was measured by directly visiting 7 food plants. The overall mean temperature for food cold storages in the survey was 2.55 ± 3.55oC, with 2.5% of above 10oC, −3.2oC and 14.9oC as a minimum and maximum. Temperature distributions by space-locations was 0.80 ± 1.69oC, 0.59 ± 1.68oC, and 0.65 ± 1.46oC as an upper (2.4~4 m), middle (1.5~2.4 m), and lower (0.7~1.5 m), respectively. Probability distributions were also created using @RISK program based on the measured temperature data. Statistical ranking was determined by the goodness of fit (GOF) to determine the proper probability distribution model. This result showed that the LogLogistic (−4.189, 5.9098, 3.2565) distribution models was found to be the most appropriate for relative MRA conduction.

A probability prediction model for tropical cyclone (TC) genesis in the Northwestern Pacific area was developed using the logistic regression method. Total five predictors were used in this model: the lower-level relative vorticity, vertical wind shear, mid-level relative humidity, upper-level equivalent potential temperature, and sea surface temperature (SST). The values for four predictors except for SST were obtained from difference of spatial-averaged value between May and January, and the time average of Niño-3.4 index from February to April was used to see the SST effect. As a result of prediction for the TC genesis frequency from June to December during 1951 to 2007, the model was capable of predicting that 21 (22) years had higher (lower) frequency than the normal year. The analysis of real data indicated that the number of year with the higher (lower) frequency of TC genesis was 28 (29). The overall predictability was about 75%, and the model reliability was also verified statistically through the cross validation analysis method.

The expected busy period for the controllable M/G/1 queueing model operating under the triadic Max (N, T, D) policy is derived by using a new concept so called “the pseudo probability density function.” In order to justify the proposed approaches for the

  The expected busy period for the controllable M/G/1 queueing model operating under the triadic policy is derived by using the pseudo probability density function which is totally different from the actual probability density function. In order to justif

According to this research, it was confirmed that safety coefficient is useful tool to rationally quantify structural deterioration of pipe. In addition, it could perform simple and rapid evaluation escaping from confinement by time and budget, and it can be utilized as a tool to set up policy for future water supply.

Although some indicators for evaluating rural settlement conditions have been offered, these indicators could not reflect unique characteristics that rural has its own peculiarities. The rural area is identified with central districts functioned as service provision and hinterlands used its service. The aim of this study is to find a central district of rural villages and define range of its hinterlands using various physical characteristics of rural areas. Targeting areas are Yongsan and Hwanggan in Yeongdong-gun . The physical characteristics are represented by building density, number of shops among secondary and tertiary industries, official land price, and density of bus line. The rural central district is estimated by linear programming using defined the physical characteristics. Also its hinterlands used Huff model and social accessibility. The results of this study are as follows; (1) The physical characteristics in Hwanggan myeon is higher than Yongsan myeon because Hwanggan area has a large floating population for using Hwanggan station and ticket office; (2) The central district in Hwanggan has wider regional range than Yongsan. When central district estimate in rural areas, we suggest a grid diameter of Hexagon for controlling errors; (3) Considering accessibility, the life zone of 4 districts defined legally in Hwanggan use Yongsan and 2 legal districts in Hwanggan are possible to take advantage of Yongsan’s life zone; (4) The results of survey targeting boundary villages between Yongsan and Hwanggan, individual drivers use central districts both Yongsan and Hwanggan, however users by public transportation (especially bus) go more to Hwanggan because bus lines to Hwanggan have many routes than to Yongsan. Evaluating the rural settlement conditions by national unit through grasping central districts and its hinterlands, these results can use as base line data and the evidence for regional development projects.

This study applied the Bayesian method for the quantification of the parameter uncertainty of spatial linear mixed model in the estimation of the spatial distribution of probability rainfall. In the application of Bayesian method, the prior sensitivity analysis was implemented by using the priors normally selected in the existing studies which applied the Bayesian method for the puppose of assessing the influence which the selection of the priors of model parameters had on posteriors. As a result, the posteriors of parameters were differently estimated which priors were selected, and then in the case of the prior combination, F-S-E, the sizes of uncertainty intervals were minimum and the modes, means and medians of the posteriors were similar to the estimates using the existing classical methods. From the comparitive analysis between Bayesian and plug-in spatial predictions, we could find that the uncertainty of plug-in prediction could be slightly underestimated than that of Bayesian prediction.

Land cover and land use change data are important in many studies including climate change and hydrological studies. Although the various theories and models have been developed, it is difficult to identify the driving factors of the land use change because land use change is related to policy options and natural and socio-economic conditions. This study is to attempt to simulate the land cover change using the CLUE model based on a statistical analysis of land-use change. CLUE model has dynamic modeling tools from the competition among land use change in between driving force and land use, so that this model depends on statistical relations between land use change and driving factors. In this study, Yongin, Icheon and Anseong were selected for the study areas, and binary logistic regression and factor analysis were performed verifying with ROC curve. Land cover probability map was also prepared to compare with the land cover data and higher probability areas are well matched with the present land cover demonstrating CLUE model applicability.

The purpose of this paper is to estimate a probability to visit the Yeosu Aquarium with an ordered logit model. Ordered logit model is affordable to estimate the probability when the dependant variable represents likert-type scale. The estimated results are as follows. The more income induces the visiting-expectation. The experience for another aquarium and the visiting-expectation for the Yeosu EXPO are contributed to the visiting-expectation for the Yeosu Aquarium. The needs to visit the Yeosu Aquarium is low in Kyoungsang area and Seoul-Kyounggi-Incheun Metropolitan area. This is related to the Aquarium facilities, which were established in each area. In average level conditions regarding to all independent variables the probability to visit the Yeosu Aquarium is calculated to 15.75%. However, the probability to visit to the Yeosu Aquarium is decreasing according to the change of an admission fee.

A probability-based data generation is a typical context-generation method that is a not only simple and strong data generation method but also easy to update generation conditions. However, the probability-based context-generation method has been found its natural-born ambiguousness and confliction problems in generated context data. In order to compensate for the disadvantages of the probabilistic random data generation method, a situation propagation network is proposed in this paper. The situation propagating network is designed to update parameters of probability functions are included in probability-based data generation model. The proposed probability-based context-generation model generates two kinds of contexts: one is related to independent contexts, and the other is related to conditional contexts. The results of the proposed model are compared with the results of the probability-based model with respect to performance, reduction of ambiguity, and confliction.

현존하는 교량의 실제적인 거동에 대한 보다 정확한 예측방법의 개발은 보수보강이 필요한 교량에 예산이 집중될 수 있도록 하여 교량운영의 경제성 및 안전성 측면에서 매우 중요하다. 특히 교량의 형태와 설치 지역의 활하중의 특성을 고려하며 활하중에 교량이 반응하는 실제적인 거동을 파악하여 실제적인 교량의 내하력 평가 이외에도 평가대상 교량의 선정 및 평가의 우선순위를 결정하여 교량의 유지 보수에 사용되는 예산의 보다 효율적인 집행을 가능하게 할 수 있다. 이 연구에서는 교량 현장실험에서 얻어지는 결과를 신뢰성 해석에 반영하여 보다 실제적인 교량 안전성 평가의 방법론을 연구하였다. 17개의 강거더 교량에 대해 기존의 교량 실험 결과를 토대로 교량의 내하력을 평가하기 위하여 2단계의 신뢰성 해석을 수행하였다. 우선 대상교량에 대해 설계에 사용된 계수 및 공칭강도를 이용하여 신뢰성 해석을 수행하였으며 2단계 신뢰성 해석에서는 교량 실험 결과를 신뢰성 해석에 포함하였다. 해석 결과를 비교해 본 결과 교량실험을 통한 각종 구조적 계수의 불확실성 제거를 통해 교량의 안전성을 저해하지 않고도 대상 교량의 신뢰성이 대폭 증가하는 결과를 얻을 수 있었다.