• Title/Summary/Keyword: Monte Carlo simulation

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Monte Carlo Simulation for the Measurement of Entrance Skin Dose on Newborn and Infants (영·유아의 입사피부선량 측정을 위한 몬테카를로 시뮬레이션)

  • Kim, Sang-Tae
    • The Journal of the Korea Contents Association
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    • v.12 no.6
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    • pp.346-352
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    • 2012
  • Radiation dose estimation on the newborn and infants during radiation examinations, unlike for the adults, is not actively being progressed. Therefore, as an index to present exposure dose during radiation examinations on newborn and infants, entrance skin dose was measured, and the result was compared with results of monte carlo simulation to raise reproducibility of entrance skin dose measurement, and it was proved that various geometry implementation was possible. The resulting values through monte carlo simulation was estimated using normalization factors for entrance skin dose to calibrate radiation dose and then normalized to a unit X ray radiation field size. Average entrance skin dose per one time exposure was $78.41{\mu}Gy$ and the percentage error between measurement by dosimeter and by monte carlo simulation was found to be -4.77%. Entrance skin dose assessment by monte carlo simulation provides possible alternative method in difficult entrance skin dose estimation for the newborn and infants who visit hospital for actual diagnosis.

A Study on the Development of Stress Testing Model for Korean Banks: Optimal Design of Monte Carlo Simulation and BIS Forecasting (국내은행 스트레스테스트 모형개선에 관한 연구: 최적 몬테카를로 시뮬레이션 탐색과 BIS예측을 중심으로)

  • Chaehwan Won;Jinyul Yang
    • Asia-Pacific Journal of Business
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    • v.14 no.1
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    • pp.149-169
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    • 2023
  • Purpose - The main purpose of this study is to develop the stress test model for Korean banks by exploring the optimal Monte Carlo simulation and BIS forecasting model. Design/methodology/approach - This study selects 15 Korean banks as sample financial firms and collects relevant 76 quarterly data for the period between year 2000 and 2018 from KRX(Korea Excange), Bank of Korea, and FnGuide. The Regression analysis, Unit-root test, and Monte Carlo simulation are hired to analyze the data. Findings - First, most of the sample banks failed to keep 8% BIS ratio for the adverse and severely Adverse Scenarios, implying that Korean banks must make every effort to realize better BIS ratios under adverse market conditions. Second, we suggest the better Monte Carlo simulation model for the Korean banks by finding that the more appropriate volatility should be different depending on variables rather than simple two-sigma which has been used in the previous studies. Third, we find that the stepwise regression model is better fitted than simple regression model in forecasting macro-economic variables for the BIS variables. Fourth, we find that, for the more robust and significant statistical results in designing stress tests, Korean banks are required to construct more valid time-series and cross-sectional data-base. Research implications or Originality - The above results all together show that the optimal volatility in designing optimal Monte Carlo simulation varies depending on the country, and many Korean banks fail to pass sress test under the adverse and severely adverse scenarios, implying that Korean banks need to make improvement in the BIS ratio.

6MV Photon Beam Commissioning in Varian 2300C/D with BEAM/EGS4 Monte Carlo Code

  • Kim, Sangroh;Jason W. Sohn;Cho, Byung-Chul;Suh, Tae-Suk;Choe, Bo-Yong;Lee, Hyoung-Koo
    • Proceedings of the Korean Society of Medical Physics Conference
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    • 2002.09a
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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.

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Monte Carlo Study of Layered Heisenberg Ferromagnet

  • Lee, Kyuwon
    • Journal of Magnetics
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    • v.6 no.4
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    • pp.119-121
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    • 2001
  • Monte Carlo simulation was employed to study the phase transition in the classical Heisenberg ferromagnet with variable interlayer interactions. The measured transition temperatures show a strong logarithmic dependence on J/J'where J and J'are the intralayer and the interlayer exchange interaction, respectively. The results were compared with the theoretical expectations and an empirical formula for the critical coupling was stained.

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Decision of Error Tolerance in Weighted Array by Hybrid Method of Monte-Carlo Simulation and Deterministic Simulation (Monte-Carlo Simulation 과 Deterministic Simulation의 합성적 방법에 의한 배열소자 가중치에 따른 오차의 규정)

  • Choi Choelmin;Lee Yongbeum;Kim Hyeongdong
    • Proceedings of the Acoustical Society of Korea Conference
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    • autumn
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    • pp.333-336
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    • 2000
  • 본 논문에서는 Monte-Carlo simulation과 deterministic simulation을 합성한 방법으로 특성허용 패턴을 만족하는 개별소자의 오차범위를 가중치에 따라 차별적으로 규정을 하였다. 일반적으로 사용되는 통계적인 방법은 불규칙한 특성을 갖는 랜덤오차를 정규분포를 갖는 랜덤변수로 모델링을 하여 허용 패턴으로부터 오차의 범위를 규정하는데, 이렇게 구해진 범위는 개별소자의 가중치의 영향을 고려하지 않고 일률적인 특성을 나타낸다는 단점이 있다. 이에 반해 deterministic simulation을 통해서 얻어진 오차의 범위는 가중치에 따라서 상대적인 범위를 결정할 수 있지만 해석 하고자하는 배열소자의 개수에 따라서 계산량이 지수승으로 증가하는 단점이 있어 10개 이상의 소자를 갖는 배열에는 적합하지 않다. 이러한 단점을 보완하기 위해서는 본 논문에서는 Monte-Carlo simulation과 deterministic simulation의 합성적 방법을 사용해서 배열소자의 증가에 따른 계산량의 증가를 줄이면서 각 가충치에 따라 상대적인 개별오차의 허용범위를 결정하였다. 그리고 이렇게 규정된 오차의 범위를 간단한 모의 실험을 통해서 검증하였다.

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Monte Carlo Simulation of the Molecular Properties of Poly(vinyl chloride) and Poly(vinyl alcohol) Melts

  • Moon, Sung-Doo;Kang, Young-Soo;Lee, Dong-J.
    • Macromolecular Research
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    • v.15 no.6
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    • pp.491-497
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    • 2007
  • NPT Monte Carlo simulations were performed to calculate the molecular properties of syndiotactic poly(vinyl chloride) (PVC) and syndiotactic poly(vinyl alcohol) (PVA) melts using the configurational bias Monte Carlo move, concerted rotation, reptation, and volume fluctuation. The density, mean square backbone end-to-end distance, mean square radius of gyration, fractional free-volume distribution, distribution of torsional angles, small molecule solubility constant, and radial distribution function of PVC at 0.1 MPa and above the glass transition temperature were calculated/measured, and those of PVA were calculated. The calculated results were compared with the corresponding experimental data and discussed. The calculated densities of PVC and PVA were smaller than the experimental values, probably due to the very low molecular weight of the model polymer used in the simulation. The fractional free-volume distribution and radial distribution function for PVC and PVA were nearly independent of temperature.

Impact Ionization Characteristics Near the Drain of Silicon MOSFET's at 77 and 300 K Using Monte Carlo Method (몬데 칼로 방법을 이용한 실리콘 MOSFET의 드레인영역에서 77 K와 300 K의 Impact Ionization 특성)

  • Rhee, Jun-Koo;Park, Young-June;Han, Min-Koo
    • 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.

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Three Dimensional Direct Monte Carlo Simulation on OLED Evaporation Process (유기EL 증착 공정에 대한 3차원 Monte Carlo 해석)

  • Lee, Eung-Ki
    • Journal of the Semiconductor & Display Technology
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    • v.8 no.4
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    • pp.37-42
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    • 2009
  • The performance of an OLED(organic luminescent emitting device) fabrication system strongly depends on the design of the evaporation cell-source. Trends in display sizes have hauled the enlargement of mother glass substrates. The enlargement of substrates requires the improvement and the enlargement of the effusion cell-source for OLED evaporation process. The deposited layers should be as uniform as possible, and therefore it is important to know the effusion profile of the molecules emitted from the cell-source. Conventional 2D DSMC algorithm cannot be used for simulating the new concept cell-source design, such as a linear source. This work concerns the development of 3D DSMC (direct simulation Monte Carlo) analysis for simulating the behavior of the evaporation cell-sources. In this paper, the 3D DSMC algorithm was developed and the film thickness profiles were obtained by the numerical analysis.

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Development of an Evaluation Technique for Incentive Level of Direct Load Control using Sequential Monte Carlo Simulation (몬테카를로 시뮬레이션을 이용한 직접부하제어의 적정 제어지원금 산정기법 개발)

  • Jeong, Yun-Won;Kim, Min-Soo;Park, Jong-Bae;Shin, Joong-Rin;Kim, Byung-Seop
    • Proceedings of the KIEE Conference
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    • 2003.07a
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    • pp.636-638
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    • 2003
  • This paper presents a new approach which is able to determine the reasonable incentive levels of direct load control using sequential Monte Carlo simulation techniques. The economic analysis needs to determine the reasonable incentive level. However, the conventional methods have been based on the scenario methods because they had not considered all cases of the direct load control situations. To overcome there problems, this paper proposes a new technique using sequential Monte Carlo simulation. The Monte Carlo method is a simple and flexible tool to consider large scale systems and complex models for the components of the system. To show its effectiveness, numerical studies were performed to indicate the possible applications of the proposed technique.

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Application of Markov Chains and Monte Carlo Simulations for Pavement Construction Engineering

  • Nega, Ainalem;Gedafa, Daba
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.1043-1050
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    • 2022
  • Markov chains and Monte Carlo Simulation were applied to account for the probabilistic nature of pavement deterioration over time using data collected in the field. The primary purpose of this study was to evaluate pavement network performance of Western Australia (WA) by applying the existing pavement management tools relevant to WA road construction networks. Two approaches were used to analyze the pavement networks: evaluating current pavement performance data to assess WA State Road networks and predicting the future states using past and current pavement data. The Markov chains process and Monte Carlo Simulation methods were used to predicting future conditions. The results indicated that Markov chains and Monte Carlo Simulation prediction models perform well compared to pavement performance data from the last four decades. The results also revealed the impact of design, traffic demand, and climate and construction standards on urban pavement performance. This study recommends an appropriate and effective pavement engineering management system for proper pavement design and analysis, preliminary planning, future pavement maintenance and rehabilitation, service life, and sustainable pavement construction functionality.

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