Reliability analysis of the components frequently starts with the data that manufacturer provides. If enough failure data are collected from the field operations, the reliability should be recomputed and updated on the basis of the field failure data. However, when the failure time record for a component contains only a few observations, all statistical methodologies are limited. In this case, where the failure records for multiple number of identical components are available, a valid alternative is combining all the data from each component into one data set with enough sample size and utilizing the useful information in the censored data. The ROK Navy has been operating multiple Patrol Killer Guided missiles (PKGs) for several years. The Korea Multi-Function Control Console (KMFCC) is one of key components in PKG combat system. The maintenance record for the KMFCC contains less than ten failure observations and a censored datum. This paper proposes a Bayesian approach with a Dirichlet mixture model to estimate failure time density for KMFCC. Trends test for each component record indicated that null hypothesis, that failure occurrence is renewal process, is not rejected. Since the KMFCCs have been functioning under different operating environment, the failure time distribution may be a composition of a number of unknown distributions, i.e. a mixture distribution, rather than a single distribution. The Dirichlet mixture model was coded as probabilistic programming in Python using PyMC3. Then Markov Chain Monte Carlo (MCMC) sampling technique employed in PyMC3 probabilistically estimated the parameters’ posterior distribution through the Dirichlet mixture model. The simulation results revealed that the mixture models provide superior fits to the combined data set over single models.

It is known that the growth and development of the mosquito are greatly affected by the change of the meteorological factors. In particular, temperature and precipitation are closely related to the life cycle of the mosquito, and their effects have different characteristics for each species of mosquito. Therefore, to develop a mosquito activity index based on mosquito density, it is essential to develop a prediction model based on weather data. In this study, we developed a functional formula that can estimate the change of mosquito density according to the change of meteorological factors using the mosquito classification data of Incheon region collected from 2011 to 2017. Also, using the data of the digital mosquito monitoring system (DMS) from April to October 2018, mosquito activity index according to characteristics of space in city was developed. In order to reflect the temporal characteristics of the mosquito life-cycle, we used data of temperature and precipitation prior to 1-2 weeks, and used land cover data to reflect the spatial characteristics of mosquito density. Density of Culex pipiens collected in the Incheon area were gradually increased when the average temperature increased two weeks ago after adjusting the precipitation. However, when the average temperature reached 22°C, the density of Culex pipiens marked a peak, and above the 22°C, the density was decreased. The predicted mosquito activity index calculated by applying the machine learning method to the DMS data of the Incheon area is designed to calculate from 1 to 10 grades. The accuracy of the mosquito activity index was 87% when the one grade error was allowed.

This study identified effects of forest density and placed on the fluid flow in the canopy using a computational fluid dynamics model, ENVI_met model. In addition, change of the fluid flow for each point was observed by selecting the impact prediction point. As a result, the density of the forest gave a direct effect on the fluid flow in height below the tree height and inside crown. In case of height below the tree height, the strongest physical changes appeared in CASE1 of dense forest. On the other hand, in case of crown height, distinct fluid flow changes appeared in CASE 2 and 3. After calculating fluid change of the impact prediction point according to altitude, the more dense height below the tree height appear significant changes in the fluid. On the other hand, in case of crown, from the moment outside the interference of the tree, the result showed that the wind path formed distinctly in CASE 2 and 3.

PURPOSES: This study deals with the traffic accidents classified by the traffic analysis zone. The purpose is to develop the accident density models by using zonal traffic and socioeconomic data. METHODS : The traffic accident density models are developed through multiple linear regression analysis. In this study, three multiple linear models were developed. The dependent variable was traffic accident density, which is a measure of the relative distribution of traffic accidents. The independent variables were various traffic and socioeconomic variables. CONCLUSIONS : Three traffic accident density models were developed, and all models were statistically significant. Road length, trip production volume, intersections, van ratio, and number of vehicles per person in the transportation-based model were analyzed to be positive to the accident. Residential and commercial area ratio and transportation vulnerability ratio obtained using the socioeconomic-based model were found to affect the accident. The major arterial road ratio, trip production volume, intersection, van ratio, commercial ratio, and number of companies in the integrated model were also found to be related to the accident.

뛰어난 단열성능을 가지는 폴리우레탄 폼(polyurethane foam, PUF)은 다양한 구조물에서 다른 재료들과 함께 사용되고 있다. 현재 LNG 운반선의 단열시스템에는 유리섬유로 강화된 폴리우레탄 폼(reinforced-polyurethane foam, R-PUF)이 사용되고 있으며, 이는 단열재 역할뿐만 아니라 슬로싱 하중을 포함한 다양한 압축하중에 대한 구조부재 기능을 수행하고 있다. 폴리우레탄 폼은 혼합과 발포를 통해 제작되는 다공성 재료이기 때문에, 본 연구에서는 기공체적비율을 통해 재료의 거동을 모사할 수 있는 Gurson damage model을 사용하여 폴리우레탄 폼의 비선형 압축거동을 모사하였으며, 폴리우레탄 폼의 기계적 성질에 영향을 미치는 영향변수로서 기공체적비율에 의존적으로 알려져 있는 밀도를 설정하였다.

본 연구에서는 두루미류의 개체군 및 서식밀도에 영향을 주는 요인 중 자연적 요인과 함께, 인간에 의한 직 간접적인 교란의 영향에 의한 서식분포모델을 도출하고자 하였다. 대상지역은 강원도 철원군의 민간인통제지역이며, 2009년부터 2014년까지 매년 1월의 두루미와 재두루미의 분포를 대상으로 하였다. 두루미류의 서식밀도는 거주지, 군사시설, 통행량이 빈번한 도로와 가까울수록 서식밀도가 감소하였고, 거리가 멀어질수록 서식밀도는 증가하였다. 통행량이 적은 도로, 잠자리와의 거리 및 비닐하우스의 밀도가 증가할수록 두루미류의 서식밀도는 감소하는 경향을 보였다. 또한, 두루미류의 서식밀도는 민간인통제지역 외부보다 내부의 밀도가 높게 나타났다. 전체 요인을 이용해 단계적 진입을 통한 회귀분석의 결과, 두루미는 3.4×AVFE (이용이 가능한 농경지의 면적 ha)+1.27×NRES (거주지와의 거리 km)-0.54×CCZ0 (민통선 내:0-외:1)+0.4×NHTR (통행량이 많은 도로와의 거리)-1.40이었다. 재두루미는 9.0×AVFE-5.47×NLTR (통행량이 낮은 도로와의 거리 km)+0.49×NLake (저수지와의 거리 km)+1.02이었다. 두루미와 재두루미 모두 공통적으로 이용 가능한 농경지의 면적이 중요하였고, 두루미에서는 거주지와의 거리 및 통행량이 많은 도로와의 거리가, 재두루미에서는 통행량이 낮은 도로와의 거리가 중요한 요인으로 나타났다. 두 가지 종 모두에서 모델에 의한 추정값과 실제 분포를 이용한 밀도 사이에 유의미한 상관관계가 나타났다.

A new model and resultant equation for the coagulation of acrylonitrile monomers in precipitation polymerization are suggested in consideration of the surface tension (γ) and cohesive energy density (ECED). The equation was proven to be quite favorable by considering figure fittings from known surface tensions and cohesive energy densities of certain organic solvents. The relationship between scale value of surface tension (γ/M) and cohesive energy density of monomers can be obtained by changing the coagulation bath component for effective precipitation polymerization of acrylonitrile in wet spinning.

The existing reliability evaluation models which have already developed by the corporations are so various because of using Maximum Likelihood Method. The existing models are very complicated owing to using system designing methods Therefore, it is very d

Numerical simulations of the powder extrusion need an appropriate pressure-dependent constitutive model for densification modeling of the magnesium powders. The present research investigated the effect of representative powder yield function of the critical relative density model. We could obtain reasonable physical properties of pure magnesium powders using cold isostatic pressing. The proposed densification model was implemented into the finite element code. The finite element analysis was applied to simulation of powder extrusion of pure magnesium powder in order to investigate the densification and processing load at room temperature.

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

In this study, bottom-up powder processing and top-down severe plastic deformation processing approaches were combined in order to achieve both full density and grain refinement with least grain growth. The numerical modeling of the powder process requires the appropriate constitutive model for densification of the powder materials. The present research investigates the effect of representative powder yield function of the Shima-Oyane model and the critical relative density model. It was found that the critical relative density model is better than the Shima-Oyane model for powder densification behavior, especially for initial stage.

  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

본 연구는 식품의 동결시 동결기구의 설계 및 동결에너지의 효율적인 운용등을 위하여 동결상태에서 과일쥬스의 농도 및 온도변화에 따른 밀도변화를 예측하기 위하여 수행되었다. 10, 15, 20, 25, 30, 35, 40%농도의 Orange Juice, Apple Juice, Grape Juice 및 Sucrose Solation을 시료로 하여 온도강하에 의해 동결팽창되는 부위를 제거하므로써 거기에 따른 무게변화를 에서 까지의 온도범위에서 간격으로 각각 측정하여 밀도를 산출하였다. 그리고, Heldman의 식을 이용하여, 위의 농도와 온도범위에서 각 과일쥬스와 Sucrose Solution의 Unfrozen water fraction을 계산하였다. 실험을 통해 측정된 밀도데이타와 Unfrozen water fraction 데이타를 최적화 컴퓨터 프로그램을 이용하여 10%에서 40%까지의 농도범위와 에서 까지의 온도범위에서 Orange Juice, Apple Juice, Grape Juice 및 Sucrose Solution의 밀도를 예측할 수 있는 모델을 수립하였다.