• Journal of the Korean Chemical Society
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• v.47 no.1
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• pp.31-37
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• 2003

The expanded uncertainties calculated by the application of GUM -approximation and Monte-Carlo simulation were compared about the model equation of one-point calibration which is widely used for the measurements and chemical analysis. For the comparisons, we assumed a set of artificial data at the various level of concentration and dispersion of t or normal distribution. Mistakes of more then 50 % was revealed at the values calculated by GUM-approximation in comparison with those of Monte-Carlo simulation because of the excess dispersion from t-distribution and non-linearity by division in the equation. In contrary, the mistake of calculation due to non-linearity of the equation was not observed in the level of detection limits with the equation of one-point calibration, because of the relatively large values of uncertainty in response.

• Progress in Medical Physics
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• v.11 no.2
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• pp.91-99
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• 2000

This is a preliminary study for developing the method of the dose reconstruction in the patients, irradiated by mega-voltage photon beams from the linear accelerator, using the transit dose distributions. In this study we present the method of three-dimensional dose reconstruction and evaluate the method by computer simulation. To acquire the dose distributions in the patients (or phantoms) we first calculate the differences between the doses at the arbitrary points in the patients and the doses at the corresponding points where the transit doses are measured. Then, we can get the dose in the patients from the measured transit dose and the calculated value of the difference. The dose differences are calculated by applying the inverse square law and using the linear attenuation coefficient. The scatter to primary dose ratios, which are calculated by the Monte Carlo program using the CT data of the patient (or phantoms), are also used in the calculations. For the evaluation of this method we used various kinds of homogeneous and inhomogeneous phantoms and calculated the transit dose distributions with the Monte Carlo program. From the distributions we reconstructed the dose distributions in the phantom. We used mono-energy Photon beam of 1.5MeV and Monte Carlo program EGS4. The comparison between the dose distributions reconstructed using the method and the distributions calculated by the Monte Carlo program was done. They agreed within errors of -4%∼+2%. This method can be used to predict the dose distributions in the patient

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2004.06a
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• pp.43-51
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• 2004

In order to decommission the shielding concrete of KRR(Korea Research Reactor) -1＆2, it must be exactly determined activated level and range by neutron irradiation during operation. To determine the activated level and range, it must be sampled and analyzed the core sample. But, there are difficulties in sample preparation and determination of the measurement efficiency by self-absorption. In the study, the full energy efficiency of the HPGe detector was compared with the measured value using standard source and the calculated one using Monte Carlo simulation. Also. self-absorption effects due to the density and component change of the concrete were calculated using the Monte Carlo method. Its results will be used radioactivity analysis of the real concrete core sample in the future.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.135-140
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• 2000

베이지안 신경망 모형(Bayesian Neural Networks Models)에서 주어진 입력값(input)은 블랙 박스(Black-Box)와 같은 신경망 구조의 각 층(layer)을 거쳐서 출력값(output)으로 계산된다. 새로운 입력 데이터에 대한 예측값은 사후분포(posterior distribution)의 기대값(mean)에 의해 계산된다. 주어진 사전분포(prior distribution)와 학습데이터에 의한 가능도함수(likelihood functions)를 통해 계산되어진 사후분포는 매우 복잡한 구조를 갖게 됨으로서 기대값의 적분계산에 대한 어려움이 발생한다. 이때 확률적 추정에 의한 근사 방법인 몬테칼로 적분을 이용한다. 이러한 방법으로서 Hybrid Monte Carlo 알고리즘은 우수한 결과를 제공하여준다(Neal 1996). 본 논문에서는 Hybrid Monte Carlo 알고리즘과 기존에 많이 사용되고 있는 Gibbs sampling, Metropolis algorithm, 그리고 Slice Sampling등의 몬테칼로 방법들을 비교한다.

• Progress in Medical Physics
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• v.16 no.3
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• pp.138-147
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• 2005

The Monte Carlo method cannot have been used for routine treatment planning because of heavy time consumption for the acceptable accuracy. Since calculation time is proportional to particle histories, we can save time by decreasing the number of histories. However, a small number of histories can cause serious uncertainties. In this study, we proposed Monte Carlo dose computation time and uncertainty reduction method using specially designed filters and adaptive denoising process. Proposed algorithm was applied to 6 MV photon and 21 MeV electron dose calculations in homogeneous and heterogeneous phantoms. Filtering time was negligible comparing to Monte Carlo simulation time. The accuracy was improved dramatically in all situations and the simulation of 1 $\%$ to 10$\%$ number of histories of benchmark in photon and electron dose calculation showed the most beneficial result. The empirical reduction of necessary histories was about a factor of ten to fifty from the result.

• The Journal of the Acoustical Society of Korea
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• v.21 no.3
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• pp.221-229
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• 2002

In thin paper, error tolerance of each array element which satisfies error tolerance of beam pattern is decided by using the Monte-Carlo method. Conventional deterministic method decides the error tolerance of each element from the acceptance pattern by testing all cases, but this method is not suitable for the analysis of large number of array elements because the computation resources increase exponentially as the number of array elements increases. To alleviate this problem, we applied new algorithm which reduces the increment of calculation time increased by the number of the array elements. We have validates the determined error tolerance region through several simulation.

• Progress in Medical Physics
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• v.14 no.4
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• pp.240-248
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• 2003

The Monte Carlo calculation is the most accurate means of predicting radiation dose, but its accuracy is accompanied by an increase in the amount of time required to produce a statistically meaningful dose distribution. In this study, the effects on calculation time by introducing variance reduction techniques and increasing computing power, respectively, in the Monte Carlo dose calculation for a 6 MV photon beam from the Varian 600 C/D were estimated when maintaining accuracy of the Monte Carlo calculation results. The EGSnrc­based BEAMnrc code was used to simulate the beam and the EGSnrc­based DOSXYZnrc code to calculate dose distributions. Variance reduction techniques in the codes were used to describe reduced­physics, and a computer cluster consisting of ten PCs was built to execute parallel computing. As a result, time was more reduced by the use of variance reduction techniques than that by the increase of computing power. Because the use of the Monte Carlo dose calculation in clinical practice is yet limited by reducing the computational time only through improvements in computing power, introduction of reduced­physics into the Monte Carlo calculation is inevitable at this point. Therefore, a more active investigation of existing or new reduced­physics approaches is required.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.1 s.104
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• pp.39-44
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• 2006

This paper proposes a method of moments(MoM)/Monte-Carlo simulation and Physical Optics(PO) model to determine Bistatic Coherent Reflectivity of sea surfaces at various wind speeds. For the MoM simulation, a Gaussian random rough sea surface was generated based on the data of Tae-An ocean at various wind speeds and sea surface heights. The numerical results of the MoM/Monte Carlo simulations were used to verify the validity region of the PO model. It was found that the numerical result for a flat surface agrees quite well with the Fresnel reflection coefficient. The validity of the PO model on the rough sea surface is shown by using ray tracing method.

• Journal of Radiation Protection and Research
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• v.26 no.2
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• pp.51-58
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• 2001

In the low level radioactivity measurement, such as environmental radioactivity, there were used commonly cylindrical and Marinelli type beakers by means of measurement container. If there are differences in the matrix density or sample height between standard source and sample, it must be determined full energy peak efficiency considering self absorption effect. In this paper, we compared measured efficiency with calculated full energy peak efficiencies in the HPGe detector using the Monte Carlo method. For cylindrical container, we calculated the variation of the efficiency with sample height. Also, we calculated the variation of the detection efficiency with apparent density in the cylindrical and Marinelli container. It was seen that it need to be corrected for self absorption in the energy range of below 1000keV. Also, in order to verify the validity of calculation, we compared the calculated value with reference value using NIST SRM 4353 reference soil.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.124-131
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• 2013

The most important thing in Plasma simulation is the etching process in which etch rate is calculated based on feature profile. Although there are various components to consider in calculating etch rate such as Ion Flux, Neutral, gas, and temperature, Addressing of this paper is limited to Ion Flux. This paper propose a scan method to compute Ion Flux faster for Plasma simulation. Also, this paper experiments and compares generally used Monte Carlo method and the proposed method based on gaussian and cosine distribution. Lastly, this paper proves that the proposed method can calculate accurate Ion Flux more efficiently than Monte Carlo method.