• 한국통계학회:학술대회논문집
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• 한국통계학회 2002년도 춘계 학술발표회 논문집
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• pp.73-78
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• 2002

In this paper we develop a method for constructing a Bayesian HPD (highest probability density) interval of a ratio of two multivariate normal generalized variances. The method gives a way of comparing two multivariate populations in terms of their dispersion or spread, because the generalized variance is a scalar measure of the overall multivariate scatter. Fully parametric frequentist approaches for the interval is intractable and thus a Bayesian HPD(highest probability densith) interval is pursued using a variant of weighted Monte Carlo (WMC) sampling based approach introduced by Chen and Shao(1999). Necessary theory involved in the method and computation is provided.

• 응용통계연구
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• 제13권2호
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• pp.505-514
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• 2000

마코브체인 몬테칼로방법중에서 깁스 추출방법을 혼합 고장모형에 이용하였다. 베이자안 추론에서 조건부분포를 가지고 사후 분포를 결정하는데 있어서 계산 문제와 이론적인 정당성을 고려하여 감마족인 Rayleigh와 Erlang추세를 가진 혼합모형에 대하여 깁스샘플링 알고리즘을 이용하여 베이지안 계산과 신뢰도 추이를 알아보고 모의실험자료를 이용하여 수치적인 계산을 시행하고 그 결과를 제시하였다.

• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 2000년도 유체기계 연구개발 발표회 논문집
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• pp.82-87
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• 2000

The direct simulation Monte Carlo (DSMC) method is applied to investigate the flow field of a disk-type drag pump. The pumping channels are cut on both sides of a rotating disk. The rotor has 10 Archimedes' spiral blades. In the present DSMC method, the variable hard sphere model is used as a molecular model, and the no time counter method is employed as a collision sampling technique. For simulation of diatomic gas flows, the Larsen-Borgnakke phenomenological model is adopted to redistribute the translational and internal energies.

• Asian-Australasian Journal of Animal Sciences
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• 제13권3호
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• pp.413-422
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• 2000

In the class of models which include random effects, the variance component estimates are important to obtain accurate predictors and estimators. Variance component estimation is straightforward for balanced data but not for unbalanced data. Since orthogonality among factors is absent in unbalanced data, various methods for variance component estimation are available. REML estimation is the most widely used method in animal breeding because of its attractive statistical properties. Recently, Bayesian approach became feasible through Markov Chain Monte Carlo methods with increasingly powerful computers. Furthermore, advances in variance component estimation with complicated models such as generalized linear mixed models enabled animal breeders to analyze non-normal data.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집A
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• pp.459-464
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• 2001

For major nuclear power plant components periodic inspections and integrity assessments are needed for the safety. But many flaws are undetectable due to sampling inspection. Probabilistic integrity assessment is applied to take into consideration of uncertainty and variance of input parameters arise due to material properties, applied load and undetectable flaws. This paper describes a Probabilistic Fracture Mechanics(PFM) analysis based on Monte Carlo(MC) algorithms. Taking important parameters as probabilistic variables such as fracture toughness, crack growth rate and flaw shape, failure probability of major nuclear power plant components is archived as a results of MC simulation. For the verification of these analysis, a comparison study of the PFM analysis using other commercial code, mathematical method is carried out and a good agreement was observed between those results.

• 대한기계학회논문집B
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• 제28권12호
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• pp.1501-1510
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• 2004

The pumping characteristics of a single-stage disk-type drag pump (DTDP) are calculated for the variation of the vertical clearance between a rotor and stator by the three-dimensional direct simulation Monte Carlo (DSMC) method. The gas flow mainly belongs to the molecular transition flow region. Spiral channels of a DTDP are cut on the both the upper and lower sides of a rotating disk, but a stationary disk is planar. The interaction between molecules is described by the variable hard-sphere model. The no time counter method is used as a collision sampling technique. The vertical clearance has a significant effect on the pumping performance. Experiments are performed under the outlet pressure range of 0.4∼533 Pa. When the numerical results are compared with the experimental data, the numerical results agree well quantitatively

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 춘계학술대회
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• pp.481-482
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• 2022

본 논문은 MOSFET 트랜지스터로 구성된 monolithic 3D 인버터의 구조에서 하부 MOSFET 게이트 전압의 변화에 따라서 상부 MOSFET 트랜지스터의 random dopant fluctuation(RDF) 영향을 3차원 소자 시뮬레이션을 통하여 조사하였다. RDF 영향 조사를 위한 표본화는 kinetic monte carlo 방식을 통하여 진행하였으며, RDF 영향이 트랜지스터의 임계전압 변동에 영향을 주는 것을 확인하였고, 상부 트랜지스터와 하부 트랜지스터 사이에 전기적 커플링을 조사하였다.

• 터널과지하공간
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• 제22권2호
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• pp.86-92
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• 2012

점추정법은 exact probabilistic method로 간주되는 Monte Carlo simulation에 비해 계산의 정확도는 다소 떨어지지만, 성능함수의 통계 모멘트를 분석하기 위한 샘플링 수를 크게 줄일 수 있는 해석 과정에서의 간편함과 비교적 정확한 통계 모멘트의 계산으로 인해 지반 및 암반공학에서의 확률론적 신뢰성 평가에 자주 사용되고 있다. 본 연구에서는 Rosenblueth와 Zhou & Nowak의 점추정법과 Monte Carlo simulation의 계산 결과를 비교 분석하여 점추정법의 정확도와 적용성을 조사하였다. 비교 분석은 해석적 해가 주어진 탄성 지반내 원형터널의 라이닝 지보 문제를 대상으로 하였다. 분석 결과, 해석적 해가 비선형 함수임에도 불구하고, 점추정법과 Monte Carlo simulation에 의해 계산된 통계 모멘트가 평균 약 1-2%의 오차를 보여 수치해석과 연계한 지하구조물의 확률론적 신뢰성 평가를 위한 점추정법의 적용성을 확인하였다.

• International Journal of Reliability and Applications
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• 제14권2호
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• pp.71-78
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• 2013

The problem of designing an experiment to estimate the reliability of a system that has N subsystems connected in series where each subsystem n has n $T_n$ components connected in parallel is investigated both theoretically and by simulation. An accelerated sampling sheme is introduced. It is shown that the accelerated sampling scheme is asymptotically optimal as the total number of units goes to infinity. Numerical comparisons for a system that has two subsystems connected in series where each subsystem has two components connected in parallel are also given. They indicate that the accelerated sampling scheme performs better than the batch sequential sampling scheme and is nearly optimal.

• 대한산업공학회지
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• 제25권1호
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• pp.8-20
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• 1999

In this paper, a design and estimation procedure for the stochastically dependent nonstationary multiple acceptance sampling plans is developed. At first, the rough-cut acceptance and rejection numbers are given as an initial solution from the corresponding sequential sampling plan. A Monte-Carlo algorithm is used to find the acceptance and rejection probabilities of a lot. The conditional probability formula for a sample path is found. The acceptance and rejection probabilities are found when a decision boundary is given. Several decision criteria and the design procedure to select optimal plans are suggested. The formula for measuring performance of these sampling plans is developed. Type I and II error probabilities are also estimated. As a special case, by setting the stage size as 1 in a dependent sampling plan, a sequential sampling plan satisfying type I and II error probabilities is more accurate and a smaller average sample number can be found. In a numerical example, a Polya dependent process is examined. The sampling performances are shown to compare the selection scheme and the effect of the change of the dependency factor.