• Title/Summary/Keyword: 몬테칼로 모사

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An Introduction to Kinetic Monte Carlo Methods for Nano-scale Diffusion Process Modeling (나노 스케일 확산 공정 모사를 위한 동력학적 몬테칼로 소개)

  • Hwang, Chi-Ok;Seo, Ji-Hyun;Kwon, Oh-Seob;Kim, Ki-Dong;Won, Tae-Young
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.41 no.6
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    • pp.25-31
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    • 2004
  • In this paper, we introduce kinetic Monte Carlo (kMC) methods for simulating diffusion process in nano-scale device fabrication. At first, we review kMC theory and backgrounds and give a simple point defect diffusion process modeling in thermal annealing after ion (electron) implantation into Si crystalline substrate to help understand kinetic Monte Carlo methods. kMC is a kind of Monte Carlo but can simulate time evolution of diffusion process through Poisson probabilistic process. In kMC diffusion process, instead of. solving differential reaction-diffusion equations via conventional finite difference or element methods, it is based on a series of chemical reaction (between atoms and/or defects) or diffusion events according to event rates of all possible events. Every event has its own event rate and time evolution of semiconductor diffusion process is directly simulated. Those event rates can be derived either directly from molecular dynamics (MD) or first-principles (ab-initio) calculations, or from experimental data.

Development of Reference Korean Organ and Effective Dose Calculation Online System (웹 기반 표준한국인 장기 흡수선량 및 유효선량 평가 시스템 개발)

  • Park, Sooyeun;Yeom, Yeon Soo;Kim, Jae Hyeon;Lee, Hyun Su;Han, Min Cheol;Jeong, Jong Hwi;Kim, Chan Hyeong
    • Journal of Radiation Protection and Research
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    • v.39 no.1
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    • pp.30-37
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    • 2014
  • Recently High-Definition Reference Korean-Man (HDRK-Man) and High-Definition Reference Korean-Woman (HDRK-Woman) were constructed in Korea. The HDRK phantoms were designed to represent respectively reference Korean male and female to calculate effective doses for Korean by performing Monte Carlo dose calculation. However, the Monte Carlo dose calculation requires detailed knowledge on computational human phantoms and Monte Carlo simulation technique which regular researchers in radiation protection dosimetry and practicing health physicists do not have. Recently the UFPE (Federal University of Pernambuco) research group has developed, and opened to public, an online Monte Carlo dose calculation system called CALDOSE_X(www.caldose.org). By using the CALDOSE_X, one can easily perform Monte Carlo dose calculations. However, the CALDOSE_X used caucasian phantoms to calculate organ doses or effective doses which are limited for Korean. The present study developed an online reference Korean dose calculation system which can be used to calculate effective doses for Korean.

Monte Carlo Simulation of a Varian 21EX Clinac 6 MV Photon Beam Characteristics Using GATE6 (GATE6를 이용한 Varian 21EX Clinac 선형가속기의 6 MV X-선 특성모사)

  • An, Jung-Su;Lee, Chang-Lae;Baek, Cheol-Ha
    • Journal of radiological science and technology
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    • v.39 no.4
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    • pp.571-575
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    • 2016
  • Monte Carlo simulations are widely used as the most accurate technique for dose calculation in radiation therapy. In this paper, the GATE6(Geant4 Application for Tomographic Emission ver.6) code was employed to calculate the dosimetric performance of the photon beams from a linear accelerator(LINAC). The treatment head of a Varian 21EX Clinac was modeled including the major geometric structures within the beam path such as a target, a primary collimator, a flattening filter, a ion chamber, and jaws. The 6 MV photon spectra were characterized in a standard $10{\times}10cm^2$ field at 100 cm source-to-surface distance(SSD) and subsequent dose estimations were made in a water phantom. The measurements of percentage depth dose and dose profiles were performed with 3D water phantom and the simulated data was compared to measured reference data. The simulated results agreed very well with the measured data. It has been found that the GATE6 code is an effective tool for dose optimization in radiotherapy applications.

방사성 핵종 측정 평가를 위한 감마 스케닝 자동화 장치 개발 및 몬테칼로 핵종 모사 코드 검증

  • 정우태;고덕준;이명찬
    • Proceedings of the Korean Nuclear Society Conference
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    • 1995.05b
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    • pp.821-826
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    • 1995
  • 방사성 폐기물 드럼 내에 함유된 핵종의 종류 및 농도를 비파괴적으로 평가하기 위하여 드럼 이 상하 또는 회전 운동을 하게 한 후 감마선을 검출하는 감마 스케닝 자동화 장치 및 관련평가 기술을 개발하였다. 자동화 장치를 컴퓨터로 제어하기 위한 컴퓨터 프로그램은 사용자가 사용하기에 편리하도록 컴퓨터 화면에 나타난 여러가지 기능 키들을 마우스를 사용하여 간단하게 조작할 수 있게 하였다. 또한 본 연구에서 개발한 몬테칼로 전산 코드의 검증 작업도 수행하였다.

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즉발감마선을 이용한 70MeV 양성자선량 급락지점 위치 측정에 관한 연구

  • Seo, Gyu-Seok;Kim, Jong-Won;Kim, Ju-Yeong;Min, Cheol-Hui;Jo, Seong-Gu;Kim, Chan-Hyeong
    • Proceedings of the Korean Society of Medical Physics Conference
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    • 2005.04a
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    • pp.100-102
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    • 2005
  • 양성자 빔을 이용한 치료는 종양부위에 높은 선량을 균일하게 전달하고 정상세포에는 적은 선량을 전달할 수 있어 암치료 효과가 높으나 정확한 치료와 환자의 안전을 위해서는 양성자선량의 급락지점을 정확히 아는 것이 중요하다. 본 연구에서는 양성자와 물질과의 핵반응으로 직각방향으로 방출되는 즉발감마선을 측정하여 양성자선량 급락지점을 측정할 수 있는 검출시스템을 몬테칼로 전산코드로 전산모사하였으며, 70MeV 단일에너지 빔과 최대에너지가 70MeV인 SOBP 빔을 모의피폭체인 물팬텀에 조사하고 검출시스템을 통해 직각방향으로 방출되는 즉발감마선의 분포를 계산하였다. 모의피폭체 안에서의 양성자선량의 분포와 측정된 즉발감마선의 분포를 서로 비교하여 두 분포 사이의 상관관계를 찾고 이 상관관계를 이용하여 양성자선량 급락지점을 결정할 수 있음을 확인할 수 있었다.

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A Study on Counting Statistics of the Hybrid G-M Counter Dead Time Model Using Monte Carlo Simulations (몬테칼로 전산모사를 이용한 복합 G-M 계수기 불감시간 모형의 계측 통계 연구)

  • Lee, Sang-Hoon;Jae, Moo-Sung
    • Journal of Radiation Protection and Research
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    • v.29 no.4
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    • pp.269-273
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    • 2004
  • The hybrid dead time model adopting paralyzable (or extendable) and non-paralyzable (or non-extendable) dead times has been introduced to extend the usable range of G-M counters in high counting rate environment and the relationship between true and observed counting rates is more accurately expressed in the hybrid model. GMSIM, dead time effects simulator, has been developed to analyze the counting statistics of G-M counters using Monte Carlo simulations. GMSIM accurately described the counting statistics of the paralyzable and non-paralyzable models. For G-M counters that follow the hybrid model, the counting statistics behaved in between two idealized models. In the future, GMSIM may be used in predicting counting statistics of three G-M dead time models, which are paralyzable, non-paralyzable and hybrid models.