• Journal of Radiation Protection and Research
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• 제47권1호
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• pp.50-57
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• 2022

Background: There are several proton therapy facilities in operation or planned in Taiwan, and these facilities are anticipated to not only treat cancer but also provide beam services to the industry or academia. The simplified approach based on the Monte Carlo-based data sets (source terms and attenuation lengths) with the point-source line-of-sight approximation is friendly in the design stage of the proton therapy facilities because it is intuitive and easy to use. The purpose of this study is to expand the Monte Carlo-based data sets to allow the simplified approach to cover the application of proton beams more widely. Materials and Methods: In this work, the MCNP6 Monte Carlo code was used in three simulations to achieve the purpose, including the neutron yield calculation, Monte Carlo-based data sets generation, and dose assessment in simple cases to demonstrate the effectiveness of the generated data sets. Results and Discussion: The consistent comparison of the simplified approach and Monte Carlo simulation results show the effectiveness and advantage of applying the data set to a quick shielding design and conservative dose assessment for proton therapy facilities. Conclusion: This study has expanded the existing Monte Carlo-based data set to allow the simplified approach method to be used for dose assessment or shielding design for beam services in proton therapy facilities. It should be noted that the default model of the MCNP6 is no longer the Bertini model but the CEM (cascade-exciton model), therefore, the results of the simplified approach will be more conservative when it was used to do the double confirmation of the final shielding design.

• Nuclear Engineering and Technology
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• 제50권6호
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• pp.854-859
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• 2018

Calculating minimal cut sets is a typical quantification method used to evaluate the top event probability for a fault tree. If minimal cut sets cannot be calculated or if the accuracy of the quantification result is in doubt, the Monte Carlo method can provide an alternative for fault tree quantification. The Monte Carlo method for fault tree quantification tends to take a long time because it repeats the calculation for a large number of samples. Herein, proposal is made to improve the quantification algorithm of a fault tree with circular logic. We developed a top-down iteration algorithm that combines the characteristics of the top-down approach and the iteration approach, thereby reducing the computation time of the Monte Carlo method.

• 자원환경지질
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• 제50권3호
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• pp.239-250
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• 2017

정량적인 산사태 취약성 분석 중 물리 모델 기반의 분석(physically based approach)은 산사태의 발생 메커니즘 과정을 고려할 수 있는 장점으로 인해 다양한 취약성 분석기법 중 가장 효과적인 기법으로 알려져 있다. 물리 모델 분석은 사면의 지형학적 및 지질공학적 특성과 관련된 입력 자료들을 활용하는데, 현장으로부터 지질공학적 특성을 획득하는 과정에서 지반의 공간적 변동성과 복잡한 지질조건으로 인해 불확실성이 발생하며 이는 부정확한 결과를 초래한다. 따라서 이러한 불확실성을 정량화하기 위하여 확률론적 기법이 활용되어 왔다. 그러나 확률론적 분석을 수행하기 위해 필요한 입력변수의 확률특성은 현장 조사나 실험에서의 수량 제약으로 인하여 정확하게 파악하기 힘들다는 문제가 발생한다. 따라서 본 연구에서는 이러한 원인으로 인해 발생하는 불확실성을 다루기 위하여 퍼지집합이론(fuzzy set theory)을 활용하였다. 특히, 본 연구에서는 퍼지집합이론과 몬테카를로기법(Monte Carlo simulation)을 결합한 분석기법을 제안하였고 이를 실제 산사태가 발생한 연구지역에 적용하여 적정성을 파악하였다. 이를 위하여 1998년 8월 대규모의 산사태가 발생한 경상북도 상주시 일대를 연구지역으로 선정하고 산사태 취약성 분석을 수행하였다. 또한 퍼지몬테카를로기법(Fuzzy Monte Carlo simulation)의 예측 정확도 비교를 위해, 기존의 확률론적 기법인 몬테카를로기법(Monte Carlo simulation)과 안전율 수행 결과와 비교분석 하였다. 그 결과 퍼지몬테카를로기법(Fuzzy Monte Carlo simulation)이 다른 기법에 비해 가장 좋은 예측의 정확도를 보였다.

• Nuclear Engineering and Technology
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• 제42권3호
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• pp.271-278
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• 2010

While the deterministic lattice physics/depletion codes use leakage-corrected critical spectrum (although approximate due to the B1 buckling search employed), Monte Carlo depletion codes currently in use do not have such a feature in spite of their heterogeneity and continuous-energy modeling capability. This paper describes an approach to Monte Carlo depletion with leakage-corrected critical spectrum derived from first principles. This is based on the concept of albedo eigenvalue treated as weight of the reflected neutron in Monte Carlo simulation.

• Structural Engineering and Mechanics
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• 제81권1호
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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.

• 한국정보통신학회논문지
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• 제9권6호
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• pp.1341-1345
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• 2005

비선형이고 정규분포에 따르지 않는 state-space모형분석에서 순차적 몬테 칼로(SMC)는 유용한 도구 중의 하나이다. 모수와 시그럴을 동시에 추정하기 위해 Monte Carlo particle filters를 사용할 수가 있다. 그러나 SMC는 여러단계의 반복을 요구하는 특별한 particle filtering 기법을 필요로 하게 된다. 본 논문은 particle filtering과 순차적 hybrid Monte Carlo(SHMC)을 결합하는 방법을 제시하고자 한다. 실험을 위해 짱뚱어 자료를 사용하였다.

• Nuclear Engineering and Technology
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• 제49권6호
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• pp.1181-1188
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• 2017

This paper proposes the adoption of Monte Carlo perturbation theory to approximate the Jacobian matrix of coupled neutronics/thermal-hydraulics problems. The projected Jacobian is obtained from the eigenvalue decomposition of the fission matrix, and it is adopted to solve the coupled problem via the Newton method. This avoids numerical differentiations commonly adopted in Jacobian-free Newton-Krylov methods that tend to become expensive and inaccurate in the presence of Monte Carlo statistical errors in the residual. The proposed approach is presented and preliminarily demonstrated for a simple two-dimensional pressurized water reactor case study.

• Nuclear Engineering and Technology
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• 제54권3호
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• pp.790-802
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• 2022

Large-scale reactor simulation often requires the use of Monte Carlo calculation techniques to estimate important reactor parameters. One drawback of these Monte Carlo calculation techniques is they inevitably result in some uncertainty in calculated quantities. The present study includes parametric uncertainty quantification (UQ) and sensitivity analysis (SA) on the Advanced Test Reactor Critical (ATRC) facility housed at Idaho National Laboratory (INL) and addresses some complications due to Monte Carlo uncertainty when performing these analyses. This approach for UQ/SA includes consideration of Monte Carlo code uncertainty in computed sensitivities, consideration of uncertainty from directly measured parameters and a comparison of results obtained from brute-force Monte Carlo UQ versus UQ obtained from a surrogate model. These methodologies are applied to the uncertainty and sensitivity of k_eff for two sets of uncertain parameters involving fuel plate geometry and fuel plate composition. Results indicate that the less computationally-expensive method for uncertainty quantification involving a linear surrogate model provides accurate estimations for k_eff uncertainty and the Monte Carlo uncertainty in calculated k_eff values can have a large effect on computed linear model parameters for parameters with low influence on k_eff.

• 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.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회B
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• pp.2165-2170
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• 2007

At nanoscales, the Boltzmann transport equation (BTE) can best describe the behavior of phonons which are energy carriers in crystalline materials. Through this study, the phonon transport in some micro/nanoscale problems was simulated with the Monte Carlo method which is a kind of the stochastic approach to the BTE. In the Monte Carlo method, the superparticles of which the number is the weighted value to the actual number of phonons are allowed to drift and be scattered by other ones based on the scattering probability. Accounting for the phonon dispersion relation and polarizations, we have confirmed the one-dimensional transient phonon transport in ballistic and diffusion limits, respectively. The thermal conductivity for GaAs was also calculated from the kinetic theory by using the proposed model. Besides, we simulated the electrostatic discharge event in the NMOS transistor as a two-dimensional problem by applying the Monte Carlo method.