• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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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.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.505-514
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• 2000

A Markov Chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. For each observed failure epoch, we introduced mixture failure model of Rayleigh and Erlang(2) pattern. This data augmentation approach facilitates specification of the transitional measure in the Markov Chain. Gibbs steps are proposed to perform the Bayesian inference of such models. For model determination, we explored sum of relative error criterion that selects the best model. A numerical example with simulated data set is given.

• 유체기계공업학회:학술대회논문집
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• 2000.12a
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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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• v.13 no.3
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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.

• Proceedings of the KSME Conference
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• 2001.06a
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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.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.12
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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

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.481-482
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• 2022

In this paper, effect of random dopant fluctuation (RDF) of the top-transistor in a monolithic 3D inverter composed of MOSFET transistors is investigated with 3D TCAD simulation when the gate voltage of the bottom-transistor is changed. The sampling for investigating RDF effect was conducted through the kinetic monte carlo method, and the RDF effect on the threshold voltage variation in the top-transistor was investigated, and the electrical coupling between top-transistors and bottom-transistors was investigated.

• International Journal of Reliability and Applications
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• v.14 no.2
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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.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.1
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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.

• Nuclear Engineering and Technology
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• v.36 no.4
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• pp.338-345
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• 2004

This study examines the sensitivity of several fabrication parameters for dry process fuel, using a random sampling technique. The in-pile performance of dry process fuel with irradiation was calculated by a modified ELESTRES code, which is the CANDU fuel performance code system. The performance of the fuel rod was then analyzed using a Monte Carlo simulation to obtain the uncertainty of the major outputs, such as the fuel centerline temperature, the fission gas pressure, and the plastic strain. It was proved by statistical analysis that for both the dry process fuel and the $UO_2$ fuel, pellet density is one of the most sensitive parameters, but as for the fission gas pressure, the density of the $UO_2$ fuel exhibits insensitive behavior compared to that of the dry process fuel. The grain size of the dry process fuel is insensitive to the fission gas pressure, while the grain size of the $UO_2$ fuel is correlative to the fission gas pressure. From the calculation with a typical CANDU reactor power envelop, the centerline temperature, fission gas pressure, and plastic strain of the dry process fuel are higher than those of the $UO_2$ fuel.