• Title/Summary/Keyword: Monte Carlo

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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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    • v.54 no.5
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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.

Markov Chain Monte Carlo simulation based Bayesian updating of model parameters and their uncertainties

  • Sengupta, Partha;Chakraborty, Subrata
    • Structural Engineering and Mechanics
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    • v.81 no.1
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    • pp.103-115
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    • 2022
  • The prediction error variances for frequencies are usually considered as unknown in the Bayesian system identification process. However, the error variances for mode shapes are taken as known to reduce the dimension of an identification problem. The present study attempts to explore the effectiveness of Bayesian approach of model parameters updating using Markov Chain Monte Carlo (MCMC) technique considering the prediction error variances for both the frequencies and mode shapes. To remove the ergodicity of Markov Chain, the posterior distribution is obtained by Gaussian Random walk over the proposal distribution. The prior distributions of prediction error variances of modal evidences are implemented through inverse gamma distribution to assess the effectiveness of estimation of posterior values of model parameters. The issue of incomplete data that makes the problem ill-conditioned and the associated singularity problem is prudently dealt in by adopting a regularization technique. The proposed approach is demonstrated numerically by considering an eight-storey frame model with both complete and incomplete modal data sets. Further, to study the effectiveness of the proposed approach, a comparative study with regard to accuracy and computational efficacy of the proposed approach is made with the Sequential Monte Carlo approach of model parameter updating.

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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    • v.55 no.12
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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.

Monte Carlo Simulation of Densification during Liquid-Phase Sintering

  • Lee, Jae Wook
    • Journal of the Korean Ceramic Society
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    • v.53 no.3
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    • pp.288-294
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    • 2016
  • The densification process during liquid-phase sintering was simulated by Monte Carlo simulation. The Potts model, which had been applied to coarsening during liquid-phase sintering, was modified to include vapor particles. The results of two- and threedimensional simulations showed a temporal decrease in porosity, in other words, densification, and an increase in the average size of pores. The results also showed growth of solid grains and the effect of wetting angle on microstructure.

The Estimation of Analytical Method for Axial Force-Moment Relationships of High-Strength Concrete Structures using Reliability Theory (신뢰성 이론을 이용한 고강도콘크리트 구조물의 축력-모멘트관계에 있어서의 해석방법에 대한 평가)

  • 최광진;장일영;송재호;홍원기
    • Proceedings of the Korea Concrete Institute Conference
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    • 1998.04b
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    • pp.447-454
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    • 1998
  • The main object of the study is that axial force-moment relationships for high strength concrete structures using reliability theory(Linear statstical method, Monte Carlo Simulation) including probability conception. And mean stress factors and centroid factors proposed to high strength concrete structures using reliability theory(Linear statstical method, Monte Carlo Simulation). Finally, The established experimental data for axial force-moment relationships are compared to the analytical data(data for Linear statstical method and Monte Carlo Simulation) for axial force-moment relationships in this analytical method.

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Monte-Carlo Approach to Develop Probabilistic Reliability Assessment Program (확률 기반의 신뢰도평가 기법 개발: Monte-Carlo 접근법)

  • Kim, Tai-Hyun;Chung, Koo-Hyung;Oh, Tae-Kyoo
    • Proceedings of the KIEE Conference
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    • 2008.11a
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    • pp.330-332
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    • 2008
  • 본 논문에서는 전력계통의 신뢰도를 평가하는 새로운 패러다임인 확률론에 근거한 신뢰도 평가에 대하여 살펴보았다. 확률론 신뢰도 평가 기법의 적용을 통하여 기존 결정론 접근법에서 다루지 못하였던 전력계통에서 발생하는 여러 가지 불확실성을 고려한 신뢰도 평가가 가능 하였으며 확률 신뢰도 평가 기법 중 시뮬레이션 기반 Monte-Carlo 기법을 적용하여 발전 및 부하의 블확실성까지 고려한 통합적인 신뢰도 평가 틀을 개발하였다. 더하여 개발된 신뢰도 평가 틀을 시험 계통에 적용하여 검증을 수행하였다.

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RADIATIVE TRANSFER IN ANISOTROPICALLY SCATTERING MEDIUM: A MONTE CARLO APPROACH (비등방 산란 매질에서의 복사전달 문제의 몬테카를로 해법)

  • PARK CHAN;HONG SEUNG SOO
    • Publications of The Korean Astronomical Society
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    • v.14 no.1
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    • pp.23-32
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    • 1999
  • We have developed a Monte Carlo code, which solves the problem of radiative transfer in anisotropically scattering atmosphere. The radiative code is flexible in handlings of the system geometry, the distribution of scattering particles, and the source-particle geometry. This code treats the case of highly forward throwing scattering. As performance tests, we have compared the result of Monte Carlo calculations with that of Quasi-Diffusion method for a spherically symmetric cloud model.

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alysis of ion motion in fusion plasma by Monte Carlo Simulation (Monte Carlo 법을 이용한 플라즈마 내의 이온 운동 해석)

  • Lee, Hong-Sik;Whang, Ki-Woong
    • Proceedings of the KIEE Conference
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    • 1989.07a
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    • pp.447-450
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    • 1989
  • Single particle orbit in plasma is obtained by drift Hamiltonian formulation in magnetic coordinate. The collisional effect is implied by Monte Carlo Method and the velocity space diffusion, energy transfer to the back ground plasma and the variation of energy distribution of test particles are investigated from many particles analysis.

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Two Dimensional MOSFET Simulator using Mixed Particle Monte Carlo Method (Mixed Particle Monte Carlo 방법을 이용한 2차원 MOSFET 시뮬레이터)

  • 진교영;박영준;민홍식
    • Journal of the Korean Institute of Telematics and Electronics A
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    • v.31A no.5
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    • pp.134-148
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    • 1994
  • A full two-dimensional MOSFET simulator utilizing the Mixed Particle Monte Carlo method is introduced. Particle simulation for both electrons and holes are self-consistently coupled with Poisson 's equation. To demonstrate the performance of the simulator, steady state and transient state solutions of the terminal characteristics and the internal physical quantities are obtained for 0.25$\mu$m MOSFETs with three different structures` conventional single drain, LDD and GOLD MOSFET structures.

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