• Nuclear Engineering and Technology
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• 제49권5호
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• pp.1095-1099
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• 2017

A fission source can act as a stabilization element in coupled Monte Carlo simulations. We have observed this while studying numerical instabilities in nonlinear steady-state simulations performed by a Monte Carlo criticality solver that is coupled to a xenon feedback solver via fixed-point iteration. While fixed-point iteration is known to be numerically unstable for some problems, resulting in large spatial oscillations of the neutron flux distribution, we show that it is possible to stabilize it by reducing the number of Monte Carlo criticality cycles simulated within each iteration step. While global convergence is ensured, development of any possible numerical instability is prevented by not allowing the fission source to converge fully within a single iteration step, which is achieved by setting a small number of criticality cycles per iteration step. Moreover, under these conditions, the fission source may converge even faster than in criticality calculations with no feedback, as we demonstrate in our numerical test simulations.

• 한국식품과학회지
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• 제38권4호
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• pp.589-593
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• 2006

돈육 가공 공정에 대한 QRA에 Monte Carlo simulation이 적용된 바 있는데, 새로운 방법으로 fuzzy 연산을 적용하여 Monte Carlo simulation과 비교 분석하였다. Carcass단계에 대한 오염 예측치인 fuzzy 값과 Monte Carlo simulation 확률분포 값의 기술통계량인 평균값은 각각 -4.393 log $CFU/cm^2$, -4.589 log $CFU/cm^2$ 로 나타났으며, processing 단계에서는 -4.185 log $CFU/cm^2$, -4.466 log $CFU/cm^2$으로 두 가지 접근 방법들이 비슷한 경향을 보였다. Fuzzy 값은 Monte Carlo simulation 확률분포 값을 포함하는 것으로 나타났다. 한편 최근 국내에서는 위해 평가에 대한 연구가 많이 이루어지고 있는데 대부분 데이터 분석은 Monte Carlo simulation에만 의존하고 있고, 다른 접근 방법에 대한 연구는 미진한 실정이다. 따라서 본 연구는 위해 평가를 위한 방법적 도구들을 개발하는데 새로운 접근 방향을 제시하였다 또한 향후 fuzzy 연산법은 데이터가 불충분한 위해 평가의 초기 단계에서 유용하게 사용될 수 있는 방법이 될 것이다.

• Structural Engineering and Mechanics
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• 제34권4호
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• pp.417-447
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• 2010

The uncertainty often observed in experimental strengths of masonry constituents makes critical the selection of the appropriate inputs in finite element analysis of complex masonry buildings, as well as requires modelling the building ultimate load as a random variable. On the other hand, the utilization of expensive Monte Carlo simulations to estimate collapse load probability distributions may become computationally impractical when a single analysis of a complex building requires hours of computer calculations. To reduce the computational cost of Monte Carlo simulations, direct computer calculations can be replaced with inexpensive Response Surface (RS) models. This work investigates the use of RS models in Monte Carlo analysis of complex masonry buildings with random input parameters. The accuracy of the estimated RS models, as well as the good estimations of the collapse load cumulative distributions obtained via polynomial RS models, show how the proposed approach could be a useful tool in problems of technical interest.

• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 2002년도 Proceedings
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• pp.113-115
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• 2002

The Monte Carlo simulation method is a numerical solution to a problem that models objects interacting with other objects or their environment based upon simple object-object or object-environment relationships. In spite of its great accuracy, It was turned away because of long calculation time to simulate a model. But, it is used to simulate a linear accelerator frequently with the advance of computer technology. To simulate linear accelerator in Monte Carlo simulations, there are many parameters needed to input to Monte Carlo code. These data can be supported by a linear accelerator manufacturer. Although the model of a linear accelerator is the same, a different characteristic property can be found. Thus, we performed a commissioning process of 6MV photon beam in Varian 2300C/D model with BEAM/EGS4 Monte Carlo code. The head geometry data were put into BEAM/EGS4 data. The mean energy and energy spread of the electron beam incident on the target were varied to match Monte Carlo simulations to measurements. TLDs (thermoluminescent dosimeter) and radiochromic films were employed to measure the absorbed dose in a water phantom. Beam profile was obtained in 40cm${\times}$40cm field size and Depth dose was in 10cm${\times}$10cm. At first, we compared the depth dose between measurements and Monte Carlo simulations varying the mean energy of an incident electron beam. Then, we compared the beam profile with adjusting the beam radius of the incident electron beam in Monte Carlo simulation. The results were found that the optimal mean energy was 6MV and beam radius of 0.1mm was well matched to measurements.

• 대한의용생체공학회:의공학회지
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• 제19권3호
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• pp.225-232
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• 1998

무정형 실리콘을 기반으로 한 X-선 영상기기에 대한 Monte Carlo 시뮬레이션 결과를 기술하였다. 무정형 실리콘 X-선 영상기기의 특성을 조사하고 최적의 설계변수들을 제공하기 위하여 Monte Carlo 시뮬레이션을 수행하였다. 본 연구의 목적에 맞도록 Monte Carlo simulation codes를 개발하였고, X-선 최대전압, 알루미늄 필터 두께, Cal(T1)두께, 그리고 무정형 실리콘 광다이오우드 픽셀 크기들을 변화시키면서 무정형 실리콘 X-선 영상기기의 계측 효율과 해상도의 변화를 연구하였다. 60kVP-120kVp의 X-선에 대하여, CsI(TI)의 두께가 300um-500um일 때 계측효율은 70%-95% 였고 에너지 흡수효율은 40%-70%였다. 시뮬레이션 결과로부터, 무정형 실리콘 픽셀크기와 Csl(TI) 두께가 해상도를 결정하는 가장 주된 요소임이 밝혀졌다. 본 연구에서 개발한 시뮬레이션을 사용하여 감도와 해상도를 최적화할 수 있는 적절한 픽셀 크기와 CsI(TI) 두께를 찾아낼 수 있었다.

• 한국정밀공학회지
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• 제29권4호
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• pp.479-486
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• 2012

Two of fundamental approaches that can be used to understand ion-solid interaction are Monte Carlo (MC) and Molecular Dynamic (MD) simulations. For the simplicity of simulation Monte Carlo simulation method is widely preferred. In this paper, basic consideration and algorithm of Monte Carlo simulation will be presented as well as simulation results. Sputtering caused by incident ion beam will be discussed with distribution of sputtered particles and their energy distributions. Redeposition of sputtered particles that are experienced refraction at the substrate-vacuum interface additionally presented. In addition, reflection of incident ions with reflection coefficient will be presented together with spatial and energy distributions. This Monte Carlo simulation will be useful in simulating and describing ion beam related processes such as Ion beam induced deposition/etching process, local nano-scale distribution of focused ion beam implanted ions, and ion microscope imaging process etc.

• Nuclear Medicine and Molecular Imaging
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• 제42권2호
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• pp.127-136
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• 2008

Monte Carlo simulation methods are especially useful in studying a variety of problems difficult to calculate by experimental or analytical approaches. Nowadays, they are extensively applied to simulate nuclear medicine instrumentations such as single photon emission computed tomography (SPECT) and positron emission tomography (PET) for assisting system design and optimizing imaging and processing protocols. The goal of this paper is to address the practical issues, a potential user of Monte Carlo simulations for nuclear medicine can encounter, to help them to choose a code. This review introduces the different types of Monte Carlo codes currently available for nuclear medicine, comments main features and properties for a code to be proper for a given purpose, and discusses current research trends in Monte Carlo codes.

• Nuclear Engineering and Technology
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• 제53권9호
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• pp.3044-3050
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• 2021

This study offers a Monte Carlo alternative for computing mass energy absorption coefficients of any material through calculation of photon energy deposited per mass of the sample and the energy flux obtained inside a sample volume. This approach is applied in this study to evaluate mass energy absorption coefficients of some amino acids found in human body at twenty-eight different photon energies between 10 keV and 20 MeV. The simulations involved a pencil beam source modeled to emit a parallel beam of mono-energetic photons toward a 1 mean free path thick sample of rectangular parallelepiped geometry. All the components in the problem geometry were surrounded by a 100 cm vacuum sphere to avoid any interactions in materials other than the absorber itself. The results computed using the Monte Carlo radiation transport packages MCNP6.2 and GAMOS5.1 were checked against the theoretical values available from the tables of XMUDAT database. These comparisons indicate very good agreement and support the conclusion that Monte Carlo technique utilized in this fashion may be used as a computational tool for determining the mass energy absorption coefficients of any material whose data are not available in the literature.

• Bulletin of the Korean Chemical Society
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• 제26권5호
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• pp.769-775
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• 2005

An efficiency of Monte Carlo (MC) docking simulations was examined for the prediction of chiral discrimination by cyclodextrins. Docking simulations were performed with various computational parameters for the chiral discrimination of a series of 17 enantiomers by $\beta$-cyclodextrin ($\beta$-CD) or by 6-amino-6-deoxy-$\beta$-cyclodextrin (am-$\beta$-CD). A total of 30 sets of enantiomeric complexes were tested to find the optimal simulation parameters for accurate predictions. Rigid-body MC docking simulations gave more accurate predictions than flexible docking simulations. The accuracy was also affected by both the simulation temperature and the kind of force field. The prediction rate of chiral preference was improved by as much as 76.7% when rigid-body MC docking simulations were performed at low-temperatures (100 K) with a sugar22 parameter set in the CHARMM force field. Our approach for MC docking simulations suggested that the conformational rigidity of both the host and guest molecule, due to either the low-temperature or rigid-body docking condition, contributed greatly to the prediction of chiral discrimination.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.122-128
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• 2013

Computer simulations designed to predict technical and financial returns of wind turbine installations are used to make informed investment decisions. These simulations used fixed values to represent real-world variables, while the actual projects can be highly uncertain, resulting in predictions that are less accurate and less useful. In this article, by modifying a popular wind power simulation sourced from the American Wind Energy Association to use Monte Carlo techniques in its calculations, the authors have proposed a way to improve simulation usability by producing probability distributions of likely outcomes, which can be used to draw broader, more useful conclusions about the simulated project.