• Current Optics and Photonics
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• 제5권4호
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• pp.421-430
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• 2021

The multifocal multiphoton microscopy (MMM) enables high-speed imaging by the concurrent scanning and detection of multiple foci generated by lenslet array or diffractive optical element. The MMM system mainly suffers from crosstalk generated by scattered emission photons that form ghost images among adjacent channels. The ghost image which is a duplicate of the image acquired in sub-images significantly degrades overall image quality. To eliminate the ghost image, the photon reassignment method was established using maximum likelihood estimation. However, this post-processing method generally takes a longer time than image acquisition. In this regard, we propose a novel strategy for rapid noise reduction in the MMM system based upon Monte-Carlo (MC) simulation. Ballistic signal, scattering signal, and scattering noise of each channel are quantified in terms of photon distribution launched in tissue model based on MC simulation. From the analysis of photon distribution, we successfully eliminated the ghost images in the MMM sub-images. If the priori MC simulation under a certain optical condition is established at once, our simple, but robust post-processing technique will continuously provide the noise-reduced images, while significantly reducing the computational cost.

• 대한전자공학회논문지SD
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• 제41권6호
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• pp.25-31
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• 2004

본 논문에서는 나노 스케일 확산 공정 모사를 위한 방법으로 동력학적 몬테칼로(kinetic Monte Carlo)를 소개하고자 한다. 먼저 동력학적 몬테칼로의 이론과 배경을 살펴보고 실제적인 이해를 돕기 위하여 실리콘 기판에 이온(전자) 주입 후 열처리과정에서 일어나는 점결함의 확산을 동력학적 몬테칼로를 이용하여 모사하는 간단한 예를 보여주고 있다. 동력학적 몬테칼로는 몬테칼로의 일종이지만 기존의 몬테칼로에서 구현하지 못하였던 물리적인 시간을 포아송 확률 과정을 통하여 구현하였다. 동력학적 몬테칼로 확산 공정 모사에서는 연속 확산 미분 방정식의 해를 구하는 기존의 유한 요소 수치 해석적 방법과 달리원자 상호간 혹은 원자와 결함 또는 결함들 간의 화학적 반응과 입자들의 확산 과정을 포아송 확률 과정에 따라 일어나는 화학적 반응, 입자들의 확산 사건의 연속으로 본다. 사건마다 고유의 사건 발생 확률을 갖고 이 사건 발생 확률에 따라 일어나는 확률적 사건의 연속적 발생으로 실제의 반도체 확산 공정을 시간에 따라 직접적으로 모사할 수 있다. 입자들 간의 화학적 반응 사건 확률과 입자들의 확산 공정에 필요한 확률적 인자들은 분자 동역학, 양자 역학적 계산, 흑은 실험으로 얻어진다.

• Nuclear Engineering and Technology
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• 제54권11호
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• pp.4272-4279
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• 2022

In this study, a cross section stochastic sampling (S.S.) capability is implemented into both the McCARD continuous energy Monte Carlo code and MIG multiple-correlated data sampling code. The ENDF/B-VII.1 covariance data based 30 group cross section sets and the SCALE6 covariance data based 44 group cross section sets are sampled by the MIG code. Through various uncertainty quantification (UQ) benchmark calculations, the McCARD/MIG results are verified to be consistent with the McCARD stand-alone sensitivity/uncertainty (S/U) results and the XSUSA S.S. results. UQ analyses for Three Mile Island Unit 1, Peach Bottom Unit 2, and Kozloduy-6 fuel pin problems are conducted to provide the uncertainties of k_eff and microscopic and macroscopic cross sections by the McCARD/MIG code system. Moreover, the SNU S/U formulations for uncertainty propagation in a MC depletion analysis are validated through a comparison with the McCARD/MIG S.S. results for the UAM Exercise I-1b burnup benchmark. It is therefore concluded that the SNU formulation based on the S/U method has the capability to accurately estimate the uncertainty propagation in a MC depletion analysis.

• Nuclear Engineering and Technology
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• 제54권10호
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• pp.3803-3810
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• 2022

OpenMC is a community-driven open-source Monte Carlo neutron and photon transport simulation code. The Weight Window Mesh (WWM) function and an automatic Global Variance Reduction (GVR) method was recently developed and implemented in a developmental branch of OpenMC. This WWM function and GVR method broaden OpenMC's usage in general purposes deep penetration shielding calculations. However, the Local Variance Reduction (LVR) method, which suits the source-detector problem, is still missing in OpenMC. In this work, the Weight Window Generator (WWG) function has been developed and benchmarked for the same branch. This WWG function allows OpenMC to generate the WWM for the source-detector problem on its own. Single-material cases with varying shielding and sources were used to benchmark the WWG function and investigate how to set up the particle histories utilized in WWG-run and WWM-run. Results show that there is a maximum improvement of WWM generated by WWG. Based on the above results, instructions on determining the particle histories utilized in WWG-run and WWM-run for optimal computation efficiency are given and tested with a few multi-material cases. These benchmarks demonstrate the ability of the OpenMC WWG function and the above instructions for the source-detector problem. This developmental branch will be released and merged into the main distribution in the future.

• Nuclear Engineering and Technology
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• 제55권6호
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• pp.2112-2124
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• 2023

With the rise of economic and safety standards for nuclear reactors, new concepts of Gen-IV reactors and modular reactors showed more complex designs that challenge current tools for reactor physics analysis. A Monte Carlo (MC) two-step method was proposed in this work. This calculation scheme uses the continuous-energy MC method to generate multi-group cross-sections from heterogeneous models. The multi-group MC method, which can adapt locally-heterogeneous models, is used in the core calculation step. This calculation scheme is verified using a Gen-IV modular lead-based fast reactor (LFR) benchmark case. The influence of homogenized patterns, scatter approximations, flux separable approximation, and local heterogeneity in core calculation on simulation results are investigated. Results showed that the cross-sections generated using the 3D assembly model with a locally heterogeneous representation of control rods lead to an accurate estimation with less than 270 pcm bias in core reactivity, 0.5% bias in control rod worth, and 1.5% bias on power distribution. The study verified the applicability of multi-group cross-sections generated with the MC method for LFR analysis. The study also proved the feasibility of multi-group MC in core calculation with local heterogeneity, which saves 85% time compared to the continuous-energy MC.

• 한국통신학회논문지
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• 제27권4B호
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• pp.345-352
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• 2002

본 논문에서는 백색잡음과 페이딩환경에서 IS-95 시스템 역방향의 성능을 평가하는데 있어 컴퓨터 수행시간을 개선할 수 있는 획기적인 방법을 제안하고 제안된 방법의 효율성은 샘플수의 형태로 입증된다. 현재 통신 시스템의 성능분석에 가장 많이 사용되는 MC(Monte Carlo) 시뮬레이션 기법은 낮은 에러율에서 많은 시뮬레이션 수행시간을 요구한다. 때문에 MC 방법은 컴퓨터 수행속도의 한계를 피할 수 없게 된다. 이러한 문제점을 해결하기 위해 제안된 방식인 센트랄 모멘트 기법을 IS-95 시스템 역방향에 적용하여 MC 방법에서 요구되는 데이터 샘플수보다 적은 수신신호의 N차 센트랄 모멘트로부터 이산 확률밀집함수를 얻을 수 있다. 연속된 누적확률분포 함수는 보간법을 통해 정확하게 되고 샘플수에서의 개선 효과가 입증된다.

• Nuclear Engineering and Technology
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• 제55권4호
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• pp.1428-1438
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• 2023

A novel Fission Diffusion Synthetic Acceleration (FDSA) method is developed and implemented as a part of a hybrid neutronics method for source convergence acceleration and variance reduction in Monte Carlo (MC) criticality calculations. The acceleration of the MC calculation stems from constructing a synthetic operator and solving a low-order problem using information obtained from previous MC calculations. By applying the P₁ approximation, two correction terms, one for the scalar flux and the other for the current, can be solved in the low-order problem and applied to the transport solution. A variety of one-dimensional (1-D) and two-dimensional (2-D) numerical tests are constructed to demonstrate the performance of FDSA in comparison with the standalone MC method and the coupled MC and Coarse Mesh Finite Difference (MC-CMFD) method on both intended purposes. The comparison results show that the acceleration by a factor of 3-10 can be expected for source convergence and the reduction in MC variance is comparable to CMFD in both slab and full core geometries, although the effectiveness of such hybrid methods is limited to systems with small dominance ratios.

• 천문학회보
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• 제41권1호
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• pp.49.3-50
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• 2016

Two major radiative transfer (RT) techniques have been developted to model late-type galaxies: approximate RT and Monte Carlo (MC) RT. In the approximate RT, first proposed by Kylafis & Bahcall, only two terms of unscattered (direct) and single-scattered intensities are computed and higher-order multiple scattering components are approximated, saving computing time and cost compared to MC RT. However, the approximate RT can yield errors in regions where multiple scattering effect is significant. In order to examine how significant the errors of the approximate RT are, we compare results of the approximate RT with those of SKIRT, a state-of-the-art MC RT code, which is basically free from the approximation errors by fully incorporating all the multiple scattered intensities. In this study, we present quantitative errors in the approximate RT for late type galaxy models with various optical depths and inclination angles. We report that the approximate RT is not reliable if the central face-on optical depth is intermediate or high (${\tau}_V$ > 3).

• 인터넷정보학회논문지
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• 제21권5호
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• pp.1-7
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• 2020

강화학습에서 근사함수로써 사용되는 딥 인공 신경망은 이론적으로도 실제와 같은 근접한 결과를 나타낸다. 다양한 실질적인 성공 사례에서 시간차 학습(TD) 은 몬테-칼로 학습(MC) 보다 더 나은 결과를 보여주고 있다. 하지만, 일부 선행 연구 중에서 리워드가 매우 드문드문 발생하는 환경이거나, 딜레이가 생기는 경우, MC 가 TD 보다 더 나음을 보여주고 있다. 또한, 에이전트가 환경으로부터 받는 정보가 부분적일 때에, MC가 TD보다 우수함을 나타낸다. 이러한 환경들은 대부분 5-스텝 큐-러닝이나 20-스텝 큐-러닝으로 볼 수 있는데, 이러한 환경들은 성능-퇴보를 낮추는데 도움 되는 긴 롤-아웃 없이도 실험이 계속 진행될 수 있는 환경들이다. 즉, 긴롤-아웃에 상관없는 노이지가 있는 네트웍이 대표적인데, 이때에는 TD 보다는 시간적 에러에 견고한 MC 이거나 MC와 거의 동일한 학습이 더 나은 결과를 보여주고 있다. 이러한 해당 선행 연구들은 TD가 MC보다 낫다고 하는 기존의 통념에 위배되는 것이다. 다시 말하면, 해당 연구들은 TD만의 사용이 아니라, MC와 TD의 병합된 사용이 더 나음을 이론적이기 보다 경험적 예시로써 보여주고 있다. 따라서, 본 연구에서는 선행 연구들에서 보여준 결과를 바탕으로 하고, 해당 연구들에서 사용했던 특별한 리워드에 의한 복잡한 함수 없이, MC와 TD의 밸런스를 랜덤하게 맞추는 좀 더 간단한 방법으로 MC와 TD를 병합하고자 한다. 본 연구의 MC와 TD의 랜덤 병합에 의한 DQN과 TD-학습만을 사용한 이미 잘 알려진 DQN과 비교하여, 본 연구에서 제안한 MC와 TD의 랜덤 병합이 우수한 학습 방법임을 OpenAI Gym의 시뮬레이션을 통하여 증명하였다.

• 한국정밀공학회지
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• 제29권5호
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• pp.554-562
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• 2012

Processing of Scanning electron microscope imaging has been analyzed in both secondary electron (SE) imaging and backscattered electron (BSE) image. Because of unique characteristics of both secondary electron and backscattered electron image, mechanism of imaging process and image quality are quite different each other. For the sake of characterize imaging process, Monte Carlo simulation code have been developed. It simulates electron penetration and depth profile in certain material. In addition, secondary electron and backscattered electron generation process as well as their spatial distribution and energy characteristics can be simulated. Geometries that has fundamental feature have been imaged using the developed Monte Carlo code. Two, SE and BSE images generation process will be discussed. BSE imaging process can be readily used to discriminate in both material and geometry by simply changing position and direction of BSE detector. The developed MC code could be useful to design BSE detector and their position. Furthermore, surface reconstruction technique is possibly developed at the further research efforts. Basics of Monte Carlo simulation method will be discussed as well as characteristics of SE and BSE images.