• 산업경영시스템학회지
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• 제35권4호
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• pp.1-9
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• 2012

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.

• 응용통계연구
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• 제27권3호
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• pp.475-485
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• 2014

일반화 선형모형(GLM)에 기초한 확률적 날씨 발생기(Stochastic weather generator)는 일일 날씨를 생성하는데 가장 일반적으로 사용되는 방법인다. 본 논문에서는 다층구조를 이용하여 기존의 GLM weather generator에 공간구조를 소개하였다. 계절별 총강우량의 overdispersion 현상을 효과적으로 제거하기 위해서 smoothing된 계절별 총강우량을 모형에 포함하였고 공간구조를 소개하기 위해서 Stochastic weather generator의 모형계수에 공간구조를 가지는 다변량 정규분포를 가정하였다. 그리고 제안된 공간구조를 가지는 GLM weather generator 모형을 우리나라 76개 지역에서 39년간 측정된 일별 강우량 관측자료에 적용하였다.

• Journal of Mechanical Science and Technology
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• 제14권10호
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• pp.1041-1050
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• 2000

In this paper the effect of specimen thickness on fatigue crack growth with the spatial distribution of material properties is presented. Basically, the material resistance to fatigue crack growth is treated as a spatial stochastic process, which varies randomly on the crack surface. The theoretical autocorrelation functions of fatigue crack growth resistance with specimen thickness are discussed for several correlation lengths. Constant ${\Delta}K$ fatigue crack growth tests were also performed on CT type specimens with three different thicknesses of BS 4360 steel. Applying the proposed stochastic model and statistical analysis procedure, the experimental data were analyzed for different specimen thicknesses for determining the autocorrelation functions and probability distributions of the fatigue crack growth resistance.

• Spatial Information Research
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• 제6권1호
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• pp.77-90
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• 1998

자연적이거나 인위적인 여러 요인의 복합적인 상호작용에 의해 지표는 계속 변화해간다. 자연재해는 생태계의 다양한 군집이 서로 상호작용을 하는데 결정적 영향을 미치는 요소로 이런 변화의 직접적인 원인이 되는 특정 사건의 발생과정이나 공간적 분포에 대한 연구는 환경과 자원관리 측면에서 중요하다. 본 논문에서는 지표변화에 영향을 미치는 자연화재의 경우를 중심으로 공간적 분포를 모형화하는 방법론을 설명하였다. 자연화재는 주로 번개에 의해 발생되어 몇 주에 결쳐 수만 킬로미터의 지역을 태우면서 새롭고 다양한 서식지를 만들어 가는 주된 자연재해중의 하나로 생태계관리차원에서 연구되고 있다. 오스트리아 빅토리아사막을 예로 이곳에서의 자연화재 발생지역을 20년동안의 원격탐사자료(MSS data)로부터 추출하여 이를 바탕으로 자연화재발생에 대한 공간적 모형을 개발하였고 모형에 입각한 시뮬레이션 방법을 논의하였다. 화재발생과정은 불규칙적으로 분포된 공간상의 point pattern에 의해 특징지어질 수 있는데 이의 모형화를 위해서 Nonhomogeneous Planar Poissin Process가 이용되었다.

• 대한수학회지
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• 제54권1호
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• pp.193-213
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• 2017

We investigate an efficient approximation of solution to stochastic Burgers equation driven by an additive space-time noise. We discuss existence and uniqueness of a solution through the Orstein-Uhlenbeck (OU) process. To approximate the OU process, we introduce the Karhunen-$Lo{\grave{e}}ve$ expansion, and sparse grid stochastic collocation method. About spatial discretization of Burgers equation, two separate finite element approximations are presented: the conventional Galerkin method and Galerkin-conservation method. Numerical experiments are provided to demonstrate the efficacy of schemes mentioned above.

• Journal of Advanced Marine Engineering and Technology
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• 제25권5호
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• pp.1058-1064
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• 2001

In this paper, the development of probability distribution estimation program for fatigue crack growth lives was summarize. The probability distribution estimation program of life was developed to increase the reliability of life estimation. In this study, it is considered that the cause of scatter in fatigue crack growth data is due to material inhomogeneity. The material resistance to fatigue crack growth is modelled as a spatial stochastic process, which varies randomly along the crack path. We developed the GUI program to estimate the probability distribution and reliability using the non-Gaussian stochastic process method. This program can be used for the reliability assessment.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2001년도 추계학술대회 논문집
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• pp.232-237
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• 2001

The evaluation of specimen thickness effect of fatigue crack growth life by the simulation of probabilistic fatigue crack growth is presented. In this paper, the material resistance to fatigue crack growth is treated as a spatial stochastic process, which varies randomly on the crack surface. Using the previous experimental data, the non-Gaussian(eventually Weibull, in this report) random fields simulation method is applied. This method is useful to estimate the probability distribution of fatigue crack growth life and the variability due to specimen thickness by simulating material resistance to fatigue crack growth along a crack path.

• 한국해양공학회지
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• 제8권2호
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• pp.47-55
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• 1994

The purpose of the present study is to investigate the effect of specimen thickness on statistical properties of crack growth resistance. In this study, the resistance S$\delta$$_h$(x) to fatigue crack growth was treated as a spatial stochastic process. which varies randomly on the crack surface. The theoretical autocorrelation functions of the resistance to fatigue crack growth considering specimen thickness are discussed for several correlation lengths. The main results obtained are : (1) The theoretical autocorrelation functions of S$\delta$$_h$(x) are almost independent of specimen of specimen thickness except for the origin. (2) The variance increases with decreasing specimen thickness.

• Interaction and multiscale mechanics
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• 제3권4호
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• pp.333-342
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• 2010

The Pseudo-Excitation Method (PEM) is applied to study the stochastic space vibration responses of train-bridge coupling system. Each vehicle is modeled as a four-wheel mass-spring-damper system with two layers of suspension system possessing 15 degrees-of- freedom. The bridge is modeled as a spatial beam element, and the track irregularity is assumed to be a uniform random process. The motion equations of the vehicle system are established based on the d'Alembertian principle, and the motion equations of the bridge system are established based on the Hamilton variational principle. Separate iteration is applied in the solution of equations. Comparisons with the Monte Carlo simulations show the effectiveness and satisfactory accuracy of the proposed method. The PSD of the 3-span simply-supported girder bridge responses, vehicle responses and wheel/rail forces are obtained. Based on the $3{\sigma}$ rule for Gaussian stochastic processes, the maximum responses of the coupling system are suggested.

• 품질경영학회지
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• 제34권2호
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• pp.122-128
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• 2006

One feature of a computer simulation experiment, different from a physical experiment, is that the output is often deterministic. Moreover the codes are computationally very expensive to run. This paper deals with the design and analysis of computer experiments(DACE) which is a relatively new statistical research area. We model the response of computer experiments as the realization of a stochastic process. This approach is basically the same as using a spatial linear model. Applications to the optimal mechanical designing and model calibration problems are illustrated. Algorithms for selecting the best spatial linear model are also proposed.