• Nuclear Engineering and Technology
• /
• 제54권3호
• /
• pp.790-802
• /
• 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
• /
• 제54권5호
• /
• pp.1769-1780
• /
• 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.

• Journal of Electrical Engineering and Technology
• /
• 제8권4호
• /
• pp.780-786
• /
• 2013

In the reliability-based design optimization of electromagnetic devices, the accurate and efficient reliability assessment method is very essential. The first-order sensitivity-assisted Monte Carlo Simulation is proposed in the former research. In order to improve its accuracy for wide application, in this paper, the second-order sensitivity analysis is presented by using the hybrid direct differentiation-adjoint variable method incorporated with the finite element method. By combining the second-order sensitivity with the Monte Carlo Simulation method, the second-order sensitivity-assisted Monte Carlo Simulation algorithm is proposed to implement reliability calculation. Through application to one superconductor magnetic energy storage system, its accuracy is validated by comparing calculation results with other methods.

• Nuclear Engineering and Technology
• /
• 제51권4호
• /
• pp.954-962
• /
• 2019

It is well known that the variance of tally is biased in a Monte Carlo calculation based on the power iteration method. Several studies have been conducted to estimate the real variance. Among them, the batch method, which was proposed by Gelbard and Prael, has been utilized actively in many Monte Carlo codes because the method is straightforward, and it is easy to implement the method in the codes. However, there is a problem when utilizing the batch method because the estimated variance varies depending on batch size. Often, the appropriate batch size is not realized before the completion of several Monte Carlo calculations. This study recognizes this shortcoming and addresses it by permitting selection of an appropriate batch size.

• Nuclear Engineering and Technology
• /
• 제54권5호
• /
• pp.1902-1908
• /
• 2022

In many of the complex systems modeled in the field of nuclear engineering, it is often useful to use linear regression-based analyses to analyze relationships between model parameters and responses of interests. In cases where the response of interest is calculated by a simulation which uses Monte Carlo methods, there will be some uncertainty in the responses. Further, the reduction of this uncertainty increases the time necessary to run each calculation. This paper presents some discussion on how the Monte Carlo error in the response of interest influences the error in computed linear regression coefficients. A mathematical justification is given that shows that when performing linear regression in these scenarios, the error in regression coefficients can be largely independent of the Monte Carlo error in each individual calculation. This condition is only true if the total number of calculations are scaled to have a constant total time, or amount of work, for all calculations. An application with a simple pin cell model is used to demonstrate these observations in a practical problem.

• 한국의학물리학회:학술대회논문집
• /
• 한국의학물리학회 2002년도 Proceedings
• /
• pp.116-118
• /
• 2002

It has been noted that Monte Carlo simulations are the most accurate method to calculate dose distributions in any material and geometry. Monte Carlo transport algorithms determine the absorbed dose by following the path of representative particles as they travel through the medium. Accurate Monte Carlo dose calculations rely on detailed modeling of the radiation source. We modeled the effects of beam modifiers such as collimators, blocks, wedges, etc. of our accelerator, Varian Clinac 600C/D to ensure accurate representation of the radiation source using the EGSnrc based BEAM code. These were used in the EGSnrc based DOSXYZ code for the simulation of particles transport through a voxel based Cartesian coordinate system. Because Monte Carlo methods use particle-by-particle methods to simulate a radiation transport, more particle histories yield the better representation of the actual dose. But the prohibitively long time required to get high resolution and accuracy calculations has prevented the use of Monte Carlo methods in the actual clinical spots. Our ultimate aim is to develop a Monte Carlo dose calculation system designed specifically for radiation therapy planning, which is distinguished from current dose calculation methods. The purpose of this study in the present phase was to get dose calculation results corresponding to measurements within practical time limit. We used parallel processing and some variance reduction techniques, therefore reduced the computational time, preserving a good agreement between calculations of depth dose distributions and measurements within 5% deviations.

• 한국의학물리학회지:의학물리
• /
• 제14권4호
• /
• pp.240-248
• /
• 2003

몬테칼로 계산은 다른 어떤 알고리즘보다 정확한 선량 계산 결과를 주지만 계산 시간이 오래 걸리는 단점이 있다. 본 연구에서는 Varian 600 C/D 선형가속기로부터지 6 MV 광자선에 대해 몬테칼로 계산을 사용하여 얻은 선량 분포가 측정에 의해 얻은 선량 분포와 2％ 이내에서 서로 잘 일치하도록 하며 분산 감소 기법을 사용하여 계산 시간 단축 정도를 평가하였다. 그리고 연산 능력을 높여 계산 시간 단축 정도를 평가하여 분산 감소 기법을 사용한 경우와 연산 능력을 높인 경우 간에 계산 시간 단축 정도를 비교하였다. 몬테칼로 계산 코드로는 빔 모사를 위해 BEAMnrc 코드, 선량 계산을 위해 DOSXYZnrc 코트를 각각 사용하였는데 분산 감소 기법은 이 코드들에서 지원하는 방법들을 사용하였고 연산 능력을 높이는 방법으로는 컴퓨터 클러스터를 이용한 병렬 처리를 사용하였다. 비교 결과, 분산 감소 기법을 사용하여 계산 시간을 최대 1/25 이상 단축시킬 수 있었고 9대의 컴퓨터를 이용한 병렬 처리 결과 계산 시간을 1/9로 단축시킬 수 있었다. 계산 곁과의 정확성을 만족할 만한 수준으로 유지할 수 있다면 분산감소 기법을 포함한 간략화된 물리의 적용은 현 시점에서 몬테칼로 선량 계산 시간을 획기적으로 단축시킬 대안이 될 수 있다.

• 대한방사선기술학회지:방사선기술과학
• /
• 제22권2호
• /
• pp.53-56
• /
• 1999

A Gaussian distribution was parametrized for the initial distribution of the electron beam emitted from a 6MeV medical linear accelerator. A percent depth dose was measured in a water phantom and the corresponding Monte Carlo calculations were performed starting from a Gaussian distribution for a range of standard deviations, ${\sigma}=0.1$, 0.15, 0.2, 0.25, and 0.3 with being the mean value for the Incident beam energy. When measurement and calculation were compared, the calculation with the Gaussian distribution for ${\sigma}=0.25$ turned out to agree best with the measurement. The results from the present work can be utilized as input energy data in planning an electron beam therapy with a Monte Carlo calculation.

• 전자공학회논문지D
• /
• 제34D권7호
• /
• pp.37-44
• /
• 1997

A dadaptive refinement tetrahedron mesh has been presented for using in full band GaAs monte carlo simulation. A uniform tetrahedron mesh is used without regard to energy values and energy variety in case of the past full band simulation. For the uniform tetrahedron mesh, a fine tetrahedron is demanded for keeping up accuracy of calculation in the low energy region such as .GAMMA.-valley, but calculation time is vast due to usin gthe same tetrahedron in the high energy region. The mesh of this study, thererfore, is consisted of the fine mesh in the low energy and large variable energy region and rough mesh n the high energy. The density of states (DOS) calculated with this mesh is compared with the one of the uniform mesh. The DOS of this mesh is improved th efive times or so in root mean square error and the ten times in the correlation coefficient than the one of a uniform mesh. This refinement mesh, therefore, can be used a sthe basic mesh for the full band GaAs monte carlo simulation.

• 한국대기환경학회:학술대회논문집
• /
• 한국대기환경학회 1999년도 춘계학술대회 논문집
• /
• pp.293-294
• /
• 1999