• Proceedings of the Korean Vacuum Society Conference
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• 1999.07a
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• pp.186-186
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• 1999

시뮬레이션 모델 및 AES, SIMS에 의한 깊이방향 분석의 유용성을 확인하기 위해 이체 충돌모델에 기초한 몬테칼로 시뮬레이션을 수행하였다. 이를 위해, 현 시뮬레이션에서는 충돌 캐스캐이드에 의한 interstitial 및 vacancy 원자의 발생과 각 원자 층이 일정한 원자농도를 유지하도록 interstitial에 의한 vacancy의 소멸을 고려하였다. 이 모델은 AES 깊이 방향 분석에서는 AsAs/GaAs 초격자에, SIMS 깊이 방향 분석에는 Ta2O5/SiO2 초격자에 적용되었고, 실험으로부터 얻어진 결과들을 잘 나타냈다. 0.5keV Ar+ 이온 스퍼터링에 의한 AES 깊이방향 분석의 경우 AlAs 층에서 Al의 선택 스퍼터링에 의해 AlAs 층에서 As(MVV-32eV)의 Auger 강도는 GaAs 층에서보다 약 1.2배 크게 나타났다. 이 시뮬레이션은 Ta2O5(18nm)/SiO2(0.5nm)에 대한 SIMS 깊이방향 분석에서 표면 쪽으로의 1-3nm 정도의 피크(SiO+) 이동 및 decay length도 또한 잘 설명할 수 있었다. 이때, 낮은 에너지에서 보다 더 깊은 이온빔 믹싱이 발생하기 때문에 높은 에너지에서 오히려 더 좋은 분해능을 얻을 수 있었다.

• Journal of the Korean Society of Radiology
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• v.12 no.3
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• pp.289-295
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• 2018

Most diagnostic devices in the medical field use X-ray sources, which emit energy spectra. In radiological diagnosis, the quantitative and qualitative analyses of X-rays are essential for maintaining the image quality and minimizing the radiation dose to patients. This work aims to obtain the X-ray energy spectra used in diagnostic imaging by Monte Carlo simulation. Various X-ray spectra are simulated using a Monte Carlo simulation tool. These spectra are then compared to the reference data obtained with a tungsten anode spectral model using the interpolating polynomial (TASMIP) code. The X-ray tube voltages used are 50, 60, 80, 100, and 110 kV, respectively. CdTe and a-Se detector are used as the detectors for obtaining the X-ray spectra. Simulation results demonstrate that the various X-ray spectra are well matched with the reference data. Based on the simulation results, an appropriate X-ray spectrum, in accordance with the tube voltage, can be selected when generating an image for diagnostic imaging. The dose to be delivered to the patient can be predicted prior to examination in the diagnostic field.

• The Journal of the Korea Contents Association
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• v.15 no.4
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• pp.350-356
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• 2015

The aim of this study is to perform simulations to design the detector module with crystal array by Monte Carlo simulation. For this purpose, a small animal PET scanner, employing module with 1~8 crystal array discrimination scheme, was designed. The proposed scanner has an inner diameter of 100 mm with detector modules in crystal array. Each module is composed of a 5.0 mm LSO crystal with a $2.0{\times}2.0mm^2$ sensitive area with a pitch 2.1 mm and 10.0 mm thickness. The LSO crystals are attached to the SiPM which has a dimension of $2.0{\times}2.0mm^2$. The detector module with crystal array of the designed PET detector was simulated using the Monte Carlo code GATE(Geant4 Application for Tomographic Emission). The detector is enough compensation for the loss of data in sinogram due to gaps between modules. The results showed that the high sensitivity and effectively reduced the problem about the missing data were greatly improved by using the detector module with 1 crystal array.

• Journal of Radiation Protection and Research
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• v.32 no.1
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• pp.21-26
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• 2007

This study is performed to evaluate the dose rate and to analyze the dose distribution of the gamma irradiation facility (IR-221) by using a Monte Calro simulation, which is helpful of upgrading the radiation processing qualification. Monte Cairo simulation is performed by MCNP4B code. Dose rates were measured at total 369 points with alanine dosimeters to compare the calculation results and the measurements data. The results have shown that the MCNP4B code is very useful to determine the dose distribution of the IR-221 gamma irradiation facility, as the calculation dose rate is within about ${\pm}5%$ of the measurement data. Dosimetry about the gamma irradiation facility usually needs enormous manpower and time. However Monte Cairo calculation method can reduce the tedious dosimetry jobs and improve the irradiation processing qualification, which will probably contribute to obtain the reliability of the irradiation products.

• Journal of the Korean Chemical Society
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• v.42 no.1
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• pp.16-21
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• 1998

The adsorption of ethane and propane in $K^{+}$ ion exchanged zeolite L has been studied using grand canonical ensemble Monte Carlo simulation. $CH_3$ and $CH_2$ groups of sorbate molecule were considered as pseudoatoms in calculation of potential, and the bond lengths and bond angles within a molecule were fixed during simulation. Average number of molecules per unit cell, number density of molecules in zeolite, distribution of molecules per unit cell, average potential per sorbate molecule, and isosteric heats of adsorption were calculated, and these results were compared with experimental results. For ethane the simulation results agreed considerably well with experimental ones over a wide range of temperature. The average potential of sorbate molecule decreased slowly with the increase of amounts sorbed in zeolite.

• Aerospace Engineering and Technology
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• v.4 no.1
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• pp.95-102
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• 2005

This paper introduces the LAE(Liquid Apogee Engine) and station acquisition fuel budget estimation method for the COMS(Communication, Ocean and Meteorological Satellite) of Korea which is planned to be launched in 2008. And the estimation results are also presented. A statistical approach, more specifically, the Monte-Carlo method was employed to have the estimation include the effect of the launch vehicle GTO injection accuracies. A case study was conducted for several potential launch vehicles to compare the fuel requirements.

• Progress in Medical Physics
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• v.8 no.1
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• pp.47-52
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• 1997

Simulations were performed using a Monte Carlo technique in order to show physical phenomena occurring when a heavy charged particle such as proton or alpha particle traverses the medium. It was confirmed that the sharp Bragg peak occurred deeper in the water with the increasing proton energy. It is found that the use of such a sharp Bragg peak due to heavy charged particles would be far superior to the case of the photon or electron, since the absorbed dose in the target tissues would be better localized, thereby minimizing the damage to the surrounding tissues.

• Journal of Korea Technology Innovation Society
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• v.7 no.3
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• pp.533-554
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• 2004

Real option valuation considers the managerial flexibility to make ongoing decisions regarding implementation of investment projects and deployment of real assets. The appeal of the framework is natural given the high degree of uncertainty that firms face in their technology investment decisions. This paper suggests an algorithm for estimating volatility of logarithmic cash flow returns of real asset based on Monte Carlo simulation. This research uses a binomial model to obtain point estimate of real option value with embedded expansion option case and provides also an array of numerical results to show the interval estimation of option value using Monte Carlo simulation.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.669-677
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• 2013

Quasi-Monte Carlo method is known to have lower convergence rate than the standard Monte Carlo method. Quasi-Monte Carlo methods are using low discrepancy sequences as quasi-random numbers. They include Halton sequence, Faure sequence, and Sobol sequence. In this article, we compared standard Monte Carlo method, quasi-Monte Carlo methods and three scrambling methods of Owen, Faure-Tezuka, Owen-Faure-Tezuka in valuation of multi-asset European call option through simulations. Moro inversion method is used in generating random numbers from normal distribution. It has been shown that three scrambling methods are superior in estimating option prices regardless of the number of assets, volatility, and correlations between assets. However, there are no big differences between them.

• Korean Journal of Construction Engineering and Management
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• v.1 no.1 s.1
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• pp.63-71
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• 2000

The paper considers two non-deterministic methods of analysing the risk exposure in a cost estimate The fist method(referred to as the 'conventional statistical' method) analyses cost data directly, to describe a probability distribution for total cost. The second method(referred to as the 'Monte Carlo simulation' method) interprets cost data directly, to generate a probability distribution for total costs from the descriptions of elemental cost distribution. The common practice of allowing for risk through an all-embracing contingency sum or percentage addition is challenged. Rather than excluding conventional, non-deterministic methods, they are here presented as possibly the only of effective foundation on which to risk management in cost estimating.