• 제목/요약/키워드: Monte carlo method

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A MONTE CARLO METHOD FOR SOLVING HEAT CONDUCTION PROBLEMS WITH COMPLICATED GEOMETRY

  • Shentu, Jun;Yun, Sung-Hwan;Cho, Nam-Zin
    • Nuclear Engineering and Technology
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    • 제39권3호
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    • pp.207-214
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    • 2007
  • A new Monte Carlo method for solving heat conduction problems is developed in this study. Differing from other Monte Carlo methods, it is a transport approximation to the heat diffusion process. The method is meshless and thus can treat problems with complicated geometry easily. To minimize the boundary effect, a scaling factor is introduced and its effect is analyzed. A set of problems, particularly the heat transfer in the fuel sphere of PBMR, is calculated by this method and the solutions are compared with those of an analytical approach.

몬테칼로법과 생애함수를 이용한 교량의 파괴확률예측 (The Prediction of Failure Probability of Bridges using Monte Carlo Simulation and Lifetime Functions)

  • Seung-Ie Yang
    • 한국안전학회지
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    • 제18권1호
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    • pp.116-122
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    • 2003
  • 몬테칼로법은 복잡한 특히 비선형문제를 푸는데 강력한 공학도구중의 하나이다. 이 방법은 컴퓨터에서의 통계적인 표본추출방법을 이용하여 각종 공학적인 문제에 근사적인 해를 준다. 교량 하나의 요소나 전체교량의 시간 의존적 파괴확률을 예측하는 방법중의 하나로 생애함수가 있다. 이 논문에서는 교량의 요소나 전체 교량의 파괴확률을 예측하기 위하여, 시스템 신뢰성과 생애함수를 이용하여 포트란 프로그램을 개발하였다. 몬테칼로법은 생애함수의 매개변수를 생성하는데 이용되었다. 적용례로서, 개발된 프로그램은 콘크리트-강 합성 교량에 적용되어, 파괴확률을 예측하는데 이용되었다.

ANALYSIS OF UNCERTAINTY QUANTIFICATION METHOD BY COMPARING MONTE-CARLO METHOD AND WILKS' FORMULA

  • Lee, Seung Wook;Chung, Bub Dong;Bang, Young-Seok;Bae, Sung Won
    • Nuclear Engineering and Technology
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    • 제46권4호
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    • pp.481-488
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    • 2014
  • An analysis of the uncertainty quantification related to LBLOCA using the Monte-Carlo calculation has been performed and compared with the tolerance level determined by the Wilks' formula. The uncertainty range and distribution of each input parameter associated with the LOCA phenomena were determined based on previous PIRT results and documentation during the BEMUSE project. Calulations were conducted on 3,500 cases within a 2-week CPU time on a 14-PC cluster system. The Monte-Carlo exercise shows that the 95% upper limit PCT value can be obtained well, with a 95% confidence level using the Wilks' formula, although we have to endure a 5% risk of PCT under-prediction. The results also show that the statistical fluctuation of the limit value using Wilks' first-order is as large as the uncertainty value itself. It is therefore desirable to increase the order of the Wilks' formula to be higher than the second-order to estimate the reliable safety margin of the design features. It is also shown that, with its ever increasing computational capability, the Monte-Carlo method is accessible for a nuclear power plant safety analysis within a realistic time frame.

Development of a dose estimation code for BNCT with GPU accelerated Monte Carlo and collapsed cone Convolution method

  • Lee, Chang-Min;Lee Hee-Seock
    • Nuclear Engineering and Technology
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    • 제54권5호
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    • pp.1769-1780
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    • 2022
  • A new method of dose calculation algorithm, called GPU-accelerated Monte Carlo and collapsed cone Convolution (GMCC) was developed to improve the calculation speed of BNCT treatment planning system. The GPU-accelerated Monte Carlo routine in GMCC is used to simulate the neutron transport over whole energy range and the Collapsed Cone Convolution method is to calculate the gamma dose. Other dose components due to alpha particles and protons, are calculated using the calculated neutron flux and reaction data. The mathematical principle and the algorithm architecture are introduced. The accuracy and performance of the GMCC were verified by comparing with the FLUKA results. A water phantom and a head CT voxel model were simulated. The neutron flux and the absorbed dose obtained by the GMCC were consistent well with the FLUKA results. In the case of head CT voxel model, the mean absolute percentage error for the neutron flux and the absorbed dose were 3.98% and 3.91%, respectively. The calculation speed of the absorbed dose by the GMCC was 56 times faster than the FLUKA code. It was verified that the GMCC could be a good candidate tool instead of the Monte Carlo method in the BNCT dose calculations.

Research on the calculation method of sensitivity coefficients of reactor power to material density based on Monte Carlo perturbation theory

  • Wu Wang;Kaiwen Li;Yuchuan Guo;Conglong Jia;Zeguang Li;Kan Wang
    • Nuclear Engineering and Technology
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    • 제55권12호
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    • pp.4685-4694
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    • 2023
  • The ability to calculate the material density sensitivity coefficients of power with respect to the material density has broad application prospects for accelerating Monte Carlo-Thermal Hydraulics iterations. The second-order material density sensitivity coefficients for the general Monte Carlo score have been derived based on the differential operator sampling method in this paper, and the calculation of the sensitivity coefficients of cell power scores with respect to the material density has been realized in continuous-energy Monte Carlo code RMC. Based on the power-density sensitivity coefficients, the sensitivity coefficients of power scores to some other physical quantities, such as power-boron concentration coefficients and power-temperature coefficients considering only the thermal expansion, were subsequently calculated. The effectiveness of the proposed method is demonstrated in the power-density coefficients problems of the pressurized water reactor (PWR) moderator and the heat pipe reactor (HPR) reflectors. The calculations were carried out using RMC and the ENDF/B-VII.1 neutron nuclear data. It is shown that the calculated sensitivity coefficients can be used to predict the power scores accurately over a wide range of boron concentration of the PWR moderator and a wide range of temperature of HPR reflectors.

A Kinetic Monte Carlo Simulation of Individual Site Type of Ethylene and α-Olefins Polymerization

  • Zarand, S.M. Ghafelebashi;Shahsavar, S.;Jozaghkar, M.R.
    • 대한화학회지
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    • 제62권3호
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    • pp.191-202
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    • 2018
  • The aim of this work is to study Monte Carlo simulation of ethylene (co)polymerization over Ziegler-Natta catalyst as investigated by Chen et al. The results revealed that the Monte Carlo simulation was similar to sum square error (SSE) model to prediction of stage II and III of polymerization. In the case of activation stage (stage I) both model had slightly deviation from experimental results. The modeling results demonstrated that in homopolymerization, SSE was superior to predict polymerization rate in current stage while for copolymerization, Monte Carlo had preferable prediction. The Monte Carlo simulation approved the SSE results to determine role of each site in total polymerization rate and revealed that homopolymerization rate changed from site to site and order of center was different compared to copolymerization. The polymer yield was reduced by addition of hydrogen amount however there was no specific effect on uptake curve which was predicted by Monte Carlo simulation with good accuracy. In the case of copolymerization it was evolved that monomer chain length and monomer concentration influenced the rate of polymerization as rate of polymerization reduced from 1-hexene to 1-octene and increased when monomer concentration proliferate.

터보 분자 펌프(Turbomolecular pump)내의 자유 분자 유동에 관한 수치 해석적 연구 (A Numerical Study of a Free Molecular Flow in the Turbomolecular Pump)

  • 황영규;허중식
    • 설비공학논문집
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    • 제8권2호
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    • pp.219-229
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    • 1996
  • In the free molecular flow range, the pumping performance of a turbomolecular pump has been predicted by calculation of the transmission probability employing the integral method and the test particle Monte-Carlo method. The velocities of molecules incident upon a moving blade are given by the random numbers, which are sampled from the Maxwell molecular velocity distribution function. The present results agree quantitatively with the previous known numerical results. For a multi-stage pump, the velocity profile of molecules between two blade rows is not Maxwell distribution. In this case, the Monte-Carlo method is employed to calculate the overall transmission probability for the entire set of blade rows. When the results of the approximate method combining the single stage solutions are compared with those of the Monte-Carlo method for the pump having six rows at C=0.6, the approximate method overestimates as much as 36% in the maximum compression ratio and 19% in the maximum pumping speed than does the Mote-Carlo method.

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Markov Chain Monte Carlo를 이용한 반도체 결함 클러스터링 파라미터의 추정 (Estimation of Defect Clustering Parameter Using Markov Chain Monte Carlo)

  • 하정훈;장준현;김준현
    • 산업경영시스템학회지
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    • 제32권3호
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    • pp.99-109
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    • 2009
  • Negative binomial yield model for semiconductor manufacturing consists of two parameters which are the average number of defects per die and the clustering parameter. Estimating the clustering parameter is quite complex because the parameter has not clear closed form. In this paper, a Bayesian approach using Markov Chain Monte Carlo is proposed to estimate the clustering parameter. To find an appropriate estimation method for the clustering parameter, two typical estimators, the method of moments estimator and the maximum likelihood estimator, and the proposed Bayesian estimator are compared with respect to the mean absolute deviation between the real yield and the estimated yield. Experimental results show that both the proposed Bayesian estimator and the maximum likelihood estimator have excellent performance and the choice of method depends on the purpose of use.

편심측정 결과가 반영된 몬테카를로 시뮬레이션을 이용한 적외선 광학계 조립정렬 공차 할당 기법 (Tolerance Allocation Method for IR Optics Fabrication Using Monte-Carlo Simulation Based on Measured Reflective Eccentricity)

  • 유재은
    • 한국광학회지
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    • 제22권4호
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    • pp.161-169
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    • 2011
  • 본 논문에서는 광학 민감도가 큰 IR 광학계의 조립정렬과정에서 목표 성능을 만족시키기 위한 조립정렬 허용범위를 설정하는 방법을 제시하였다. 조립정렬 과정에서 편심측정기를 이용하여 각각의 광학소자에 대한 반사 편심량을 측정할 수 있다. 측정된 값을 이용하여 몬테카를로 시뮬레이션을 수행하였고 이를 이용하여 조립 정렬 이후의 광학계의 성능을 예측하였다. 시뮬레이션 결과와 실제 제작된 광학계의 광학 성능을 비교하여 본 논문에서 제시한 공차 할당 기법의 타당성을 확인하였다.

전역 최적화기법을 이용한 승객보호장치의 설계 (Design of Occupant Protection Systems Using Global Optimization)

  • 전상기;박경진
    • 한국자동차공학회논문집
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    • 제12권6호
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    • pp.135-142
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    • 2004
  • The severe frontal crash tests are NCAP with belted occupant at 35mph and FMVSS 208 with unbelted occupant at 25mph, This paper describes the design process of occupant protection systems, airbag and seat belt, under the two tests. In this study, NCAP simulations are performed by Monte Carlo search method and cluster analysis. The Monte Carlo search method is a global optimization technique and requires execution of a series of deterministic analyses, The procedure is as follows. 1) Define the region of interest 2) Perform Monte Carlo simulation with uniform distribution 3) Transform output to obtain points grouped around the local minima 4) Perform cluster analysis to obtain groups that are close to each other 5) Define the several feasible design ranges. The several feasible designs are acquired and checked under FMVSS 208 simulation with unbelted occupant at 25mph.