‘In structural system, a certain amount of uncertainties always persists in material properties, geometric parameters and applied loads. In this study, the structure is designed to withstand the uncertainties which are caused by either measurement inaccuracy or system complexity. Random structures are modelled by using ANSYS probabilistic design module. It can be applied easily to any structural system with random parameters. The aim of this paper is to make optimal design for the beam with random input variables due to width and height and response parameters due to displacements and stresses. The probabilistic design is also carried out with ANSYS APDL and then the optimal design is sequentially solved. As the total volume of beam, stresses and displacements at the beam are treated as random parameters, the numerical results are obtained.'

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.

The modulus of beam is assumed to have spatial uncertainty. The formulation to determine the response variability of the cantilever beam due to randomness of modulus of beam is given. The randomness in elastic modulus is considered to be one-dimensional, homogeneous stochastic field. The stochastic field is represented by using spectral representation to reproduce random fields. The statistics of beam responses are investigated using Monte Carlo simulations for different kinds of fluctuations of the modulus. The influence of the uncertainty in the modulus on the beam displacement is addressed.

We develop an optimization algorithm for a periodic review inventory system under a stochastic budget constraint. While most conventional studies on the periodic review inventory system consider a simple budget limit in terms of the inventory investment being less than a fixed budget, this study adopts more realistic assumption in that purchasing costs are paid at the time an order is arrived. Therefore, probability is employed to express the budget constraint. That is, the probability of total inventory investment to be less than budget must be greater than a certain value assuming that purchasing costs are paid at the time an order is arrived. We express the budget constraint in terms of the Lagrange multiplier and suggest a numerical method to obtain optional values of the cycle time and the safety factor to the system. We also perform the sensitivity analysis in order to investigate the dependence of important quantities on the budget constraint. We find that, as the amount of budget increases, the cycle time and the average inventory level increase, whereas the Lagrange multiplier decreases. In addition, as budget increases, the safety factor increases and reaches to a certain level. In particular, we derive the condition for the maximum safety factor.

In this paper, the stochastic 1D site response analysis method using Monte Carlo simulation and considering thespatial variation of shear wave velocity profile isproposed. To consider thespatial variation of shear wave velocity profile for 1D site response analysis, the proposed method generates random shear wave velocity profiles representing the target site, and Monte Carlo simulation is used to calculate theprobability distribution of the site response analysis results such as thepeak ground acceleration. Through the field application, The applicability of the proposed method is verified through field application.

파이로처리 방사성폐기물 처분장에서 폐쇄 후 처분장의 성능에 영향을 줄 수 있는 근계 영역 내 세가지 주요 설계 관련 요 소에 대하여 주요 핵종별로 최종 피폭 선량에 주는 민감도를 확률론적인 접근을 통하여 조사하였다. 농축 피폭 집단에 방사 선 피폭을 주는 주요한 핵종들이 처분장에서 유출된 후 처분 시스템 근계 영역 내 다양한 매질을 이동하는 것에 관련되어, 이들 요소가 어느 정도의 영향을 주게 되는지 보기 위하여 처분 용기의 수명, 선원항으로서 처분 용기에서의 연간 핵종 유출 률, 그리고 처분장 주요 인공 방벽으로서 완충재의 손실도 등의 변화에 따른 결과를 검토하였다. 처분장에 대한 결정론적, 확률론적 안전성 평가를 병행 수행하여, 이 세가지 설계 요소의 물리적 변화가 통계적 분포를 가지고 일어난다고 가정하는 확률론적 접근 방법에 따른 연구 결과는 제 1 부의 이 연구에, 그리고 세가지 설계 요소가 가질 수 있는 조합을 서로 다른 시 나리오로서 비교하는 결정론적인 방법으로 접근한 결과는 별도로 제 2 부에 제시하였다. 두 가지 접근 결과와 함께 고려된 인자들에 대하여 모두 결과에 민감한 것으로 나타나 이러한 결과와 방법론은 향후 처분장 설계에 모범적인 피드백을 줄 수 있을 것으로 기대된다.

본 논문에서는 반강접을 고려한 프레임 구조에서 강재 탄성계수의 불확실성이 프레임 구조의 비선형거동에 미치는 영향을 분석하였다. 강재 탄성계수의 불확실성의 확률분포는 정규분포로 모델링 하였으며, 이러한 확률적 물성치를 반강접 프레임의 비선형 거동에 적용할 수 있는 해석 프로그램을 개발하였다. 프레임의 비선형 거동 인수인 기하학적 비선형, 재료적 비선형, 그리고 접합부의 반강접에 의한 비선형 효과를 고려하여, Monte Carlo Simulation에 기반한 확률론적 해석을 수행하였다. 확률론적 해석을 위해 확률변수를 세 종류로 생성하여 사용하였다. 확정론적 해석의 결과는 기존의 연구 결과와 잘 일치하는 결과를 보였다. 확률론적 해석의 경우, 변위의 분산계수는 구조에 작용하는 하중이 증가함에 따라 증가하는 결과를 나타냈으며, 그 값은 프레임구조의 구조적 특성에 영향을 받는 것으로 나타났다.

We estimated decreasing rate of indoor air pollutants with are airborne bacteria, airborne fungi, formaldehyde, total volatile organic compounds, PM10, and PM2.5 in 10 children’s hospitals and 6 childbirth houses located in Seoul and Gyeonggi-do from November to December in 2012. Sectional period was respectively divided for operating and non-operating the air cleaners. There was a trend that concentration of surveyed pollutants in children’s hospitals and childbirth houses during operating period decreased among indoor air. We used Monte-Calro simulation to remove uncertainty and identify efficiency of eliminated pollutants such as surveyed pollutants by the air cleaners. Average efficiency of removal were 61.39 ± 21.42% for airborne bacteria, 71.77 ± 19.65% for airborne fungi, 73.37 ± 24.62% for formaldehyde, 71.20 ± 25.96% for total volatile organic compounds, 65.16 ± 23.80% for PM10, and 71.06 ± 23.97% for PM2.5.

This study investigated viability variation of airborne bacteria in indoor environments. The survival in air as a temporal function of bioaerosol viability was reported for Escherichia coli (KCCM 12119, ATCC 11775). Bacteria suspended in distilled water were aerosolized and entered the vertical duct oriented downward. After measurement of number concentration and colony forming unit (CFU) of the bacteria at different locations of the duct, the viability function was calculated. It was found that the bacteria viability(%) decreased with time after aerosolization, 28.454e^-0.132x (x:time, min). This study demonstrated the potential application of viability function of airborne bacteria to studies of exposure assessment and infection risk analysis.

Decisions on reliability screening rules and burn-in policies are determined based on the estimated reliability. The variability in a semiconductor manufacturing process does not only causes quality problems but it also makes reliability estimation more complicated. This study investigates the nonuniformity characteristics of integrated circuit reliability according to defect density distribution within a wafer and between wafers then develops optimal burn-in policy based on the estimated reliability. New reliability estimation model based on yield information is developed using a spatial stochastic process. Spatial defect density variation is reflected in the reliability estimation, and the defect densities of each die location are considered as input variables of the burn-in optimization. Reliability screening and optimal burn-in policy subject to the burn-in cost minimization is examined, and numerical experiments are conducted.

파이로처리 방사성 폐기물 처분 시스템에 대하여 골드심을 이용하여 개발된 확률론적 평가 프로그램을 이용하여 폐쇄후 방사선적 안전성 평가를 수행하였다. 처분장으로부터 핵종이 유출되어 다양한 처분 시스템 내 매질을 이동하는 것에 관련된 정상 시나리오에 대한 평가를 위하여, 평가 결과에 대한 민감도나 일반적으로 불확실성의 범위가 큰 입력자료 중 주요하다고 판단되는 파라미터를 9개로 선정하여 평가에 고려된 핵종 중 Tc, Sn, Pa, Cs 4개의 원소에 대하여 평가 결과를 논의해 보았다. 확률론적 안전성 평가와 함께 이들 각 입력 자료에 대한 최종 방사선 피폭선량에 대한 민감도도 분석하여 결과에 대한 각 입력 파라미터의 중요도도 비교하였다.

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.

Dispersion characteristics of respiratory droplets are important in controlling transmission of airborne diseases indoors. This study investigated the spatial concentration distribution and temporal evolution of exhaled and sneezed/coughed droplets in a ventilated hospital ward. The viability function of airborne bacteria was experimentally determined and encorporated into an air infection model with calculated results to estimate exposures and infection probability to the bacteria. The diffusion, gravitational settling and deposition mechanism of particulate matter were accounted by using an Eulerian modeling approach. The simulation results indicated that the ventilation flow was found to play a significant role in aerosol transport, leading to different spatial distribution patterns in infection droplet. The smaller size of infection droplet caused higher chance of ventilation from the outlet. The possibility of the proposed exposure estimation into the dose–response model for infection risk assessment was discussed. The infection probability is broadly different from 10^-6 to 7.2% by receptor's position and location and size of infection droplet conditions.

이 논문에서는 작업의 처리시간이 임의의 확률분포를 따르고 작업의 납기일이 작업마다 별개인 상황에서의 단일기계 스케줄링문제에 관하여 살펴본다. 이 때 충분히 이른 작업의 수를 최대화시키는 데에 관심을 둔다. 이러한 스케줄링문제를 풀기 위한 두 가지 알고리즘, 즉 이진정수계획모형과 스케줄링 규칙을 제안한다. 여기서 제안하는 스케줄링 규칙은 처리시간과 납기일이 확정적인 경우에 지연작업의 수를 최소화 시켜주는 스케줄링을 제공하는 기존 알고리즘을 처리시간과 납기

The research presents a guideline for quality practitioners to provide a full comprehension of differences in theoretical and practical interpretations of assumed sampling errors of and significance probability of calculated p-value. Besides, the study recommends the use of statistical inferences methods with known parameters to identify the improvement effects. In practice, the quality practitioners obtain the known parameters through systematic quality Database (DB) activities.