• Proceedings of the Korean Radioactive Waste Society Conference
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• 2004.06a
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• pp.43-51
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• 2004

In order to decommission the shielding concrete of KRR(Korea Research Reactor) -1＆2, it must be exactly determined activated level and range by neutron irradiation during operation. To determine the activated level and range, it must be sampled and analyzed the core sample. But, there are difficulties in sample preparation and determination of the measurement efficiency by self-absorption. In the study, the full energy efficiency of the HPGe detector was compared with the measured value using standard source and the calculated one using Monte Carlo simulation. Also. self-absorption effects due to the density and component change of the concrete were calculated using the Monte Carlo method. Its results will be used radioactivity analysis of the real concrete core sample in the future.

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.193-196
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• 1987

We reported that hot electron phenomena in submicron nMOSFET by Monte Carlo method. In order to predict the influence of the hot electron effects on the device reliability, either simple analytical model or a complete two dimensional numerical simulation has been adopted. Results of numerical simulation, based on the static mobility model, may be inaccurate when gate length of MOSFET is scaled down to less than 1um. Most of device simulation packages utilize the static nobility model. Monte Carlo method based on stochastic analysis of carrier movement may be a powerful tool to characterize hot electrons. In this work, energy and velocity distribution of carriers were obtained to predict the relative degree of short channel effects for different device parameters. Our analysis shows a few interesting results when $V_{ds}$ is 5 volt, average electron energy does not increase with gate bias as evidenced by substrate current.

• Journal of the Korean Geotechnical Society
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• v.23 no.11
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• pp.109-117
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• 2007

Uncertainty is pervasive in rock slope stability analysis due to various reasons and subsequently it may cause serious rock slope failures. Therefore, the importance of uncertainty has been recognized and subsequently the probability theory has been used to quantify the uncertainty since 1980's. However, some uncertainties, due to incomplete information, cannot be handled satisfactorily in the probability theory and the fuzzy set theory is more appropriate for those uncertainties. In this study the random variable is considered as fuzzy number and the fuzzy set theory is employed in rock slope stability analysis. However, the previous fuzzy analysis employed the approximate method, which is first order second moment method and point estimate method. Since previous studies used only the representative values from membership function to evaluate the stability of rock slope, the approximated analysis results have been obtained in previous studies. Therefore, the Monte Carlo simulation technique is utilized to evaluate the probability of failure for rock slope in the current study. This overcomes the shortcomings of previous studies, which are employed vertex method. With Monte Carlo simulation technique, more complete analysis results can be secured in the proposed method. The proposed method has been applied to the practical example. According to the analysis results, the probabilities of failure obtained from the fuzzy Monte Carlo simulation coincide with the probabilities of failure from the probabilistic analysis.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.203-210
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• 2003

In a standard Metropolis-type Monte Carlo simulation, the proposal distribution cannot be easily adapted to "local dynamics" of the target distribution. To overcome some of these difficulties, Duane et al. (1987) introduced the method of hybrid Monte Carlo(HMC) which combines the basic idea of molecular dynamics and the Metropolis acceptance-rejection rule to produce Monte Carlo samples from a given target distribution. In this paper, using the HMC within Gibbs sampler, an asymptotical estimate of the smoothing mean and a general solution to state space modeling in Bayesian framework is obtaineds obtained.

• Journal of the Korean Data and Information Science Society
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• v.11 no.2
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• pp.139-155
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• 2000

An exclusive simulation study is conducted in computing means for order statistics in standard normal variate. Monte Carlo moments are used in Shapiro-Francia W' statistic computation. Finally, quantiles for Shapiro-Francia W' are generated. The study shows that in computing means for order statistics in standard normal variate, complicated distributions and intensive numerical integrations can be avoided by using Monte Carlo simulation. Lack of accuracy is minimal and computation simplicity is noteworthy.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.124-131
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• 2013

The most important thing in Plasma simulation is the etching process in which etch rate is calculated based on feature profile. Although there are various components to consider in calculating etch rate such as Ion Flux, Neutral, gas, and temperature, Addressing of this paper is limited to Ion Flux. This paper propose a scan method to compute Ion Flux faster for Plasma simulation. Also, this paper experiments and compares generally used Monte Carlo method and the proposed method based on gaussian and cosine distribution. Lastly, this paper proves that the proposed method can calculate accurate Ion Flux more efficiently than Monte Carlo method.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.2
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• pp.92-99
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• 2004

The errors can cause the serious loss of the performance of a precision machine system. In this paper, we proposed the method of allocating the alignment tolerances of the parts and applied this method to get the optimal tolerances of a Confocal Scanning Microscope. In general, tight tolerances are required to maintain the performance of a system, but a high cost of manufacturing and assembling is required to preserve the tight tolerances. The purpose of allocating the optimal tolerances is minimizing the cost while keeping the high performance of the system. In the optimal problem, we maximized the tolerances while maintaining the performance requirements. The Monte Carlo Method, a statistical simulation method, is used in tolerance analysis. Alignment tolerances of optical components of the confocal scanning microscope are optimized to minimize the cost and to maintain the observation performance of the microscope. We can also apply this method to the other precision machine system.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.1 s.104
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• pp.39-44
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• 2006

This paper proposes a method of moments(MoM)/Monte-Carlo simulation and Physical Optics(PO) model to determine Bistatic Coherent Reflectivity of sea surfaces at various wind speeds. For the MoM simulation, a Gaussian random rough sea surface was generated based on the data of Tae-An ocean at various wind speeds and sea surface heights. The numerical results of the MoM/Monte Carlo simulations were used to verify the validity region of the PO model. It was found that the numerical result for a flat surface agrees quite well with the Fresnel reflection coefficient. The validity of the PO model on the rough sea surface is shown by using ray tracing method.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.131-135
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• 1989

Hot electron simulation of silicon using Monte Carlo method was carried out to investigate impact ionization characteristics near the drain of MOSFET's at 77 and 300K. We successfully characterized drift velocity and impact ionization at 77 and 300K employing a simplified energy band structure and phonon scattering mechanisms. Woods' soft energy threshold model was introduced to the Monte Carlo simulation of impact ionization, and good agreement with reported experimental results was resulted by employing threshold energy of 1.7 eV. It is suggested that the choice of the critical angle between specular reflection and diffusive scattering of surface roughness scattering may be important in determining the impact ionization charateristics of Monte Carlo simulation near the drain of MOSFET's.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.7
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• pp.657-664
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• 2011

This study proposes an inverse method for estimating the boundary temperature in a gas-filled, onedimensional parallel domain enclosed by parallel plates. The distance between the plates is considered submicron to one mm. In the current method, it is assumed that the conditions of both heat flux and temperature are simultaneously applicable to one boundary, while no conditions are applicable to the other boundary The temperature on one of the boundaries should be inversely determined from the known temperature and heat flux on the other boundary. This study proposes a procedure for estimating the unknown boundary temperature through Monte Carlo simulation. Both the forward and inverse problems employ the Monte Carlo approach. The forward (direct) problem is solved by using the direct simulation Monte Carlo while the inverse solution is obtained by the simulated annealing.