• Title, Summary, Keyword: Monte-Carlo simulations

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Stabilization effect of fission source in coupled Monte Carlo simulations

  • Olsen, Borge;Dufek, Jan
    • Nuclear Engineering and Technology
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    • v.49 no.5
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    • pp.1095-1099
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    • 2017
  • A fission source can act as a stabilization element in coupled Monte Carlo simulations. We have observed this while studying numerical instabilities in nonlinear steady-state simulations performed by a Monte Carlo criticality solver that is coupled to a xenon feedback solver via fixed-point iteration. While fixed-point iteration is known to be numerically unstable for some problems, resulting in large spatial oscillations of the neutron flux distribution, we show that it is possible to stabilize it by reducing the number of Monte Carlo criticality cycles simulated within each iteration step. While global convergence is ensured, development of any possible numerical instability is prevented by not allowing the fission source to converge fully within a single iteration step, which is achieved by setting a small number of criticality cycles per iteration step. Moreover, under these conditions, the fission source may converge even faster than in criticality calculations with no feedback, as we demonstrate in our numerical test simulations.

Application of Fuzzy Math Simulation to Quantitative Risk Assessment in Pork Production (돈육 생산공정에서의 정량적 위해 평가에 fuzzy 연산의 적용)

  • Im, Myung-Nam;Lee, Seung-Ju
    • Korean Journal of Food Science and Technology
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    • v.38 no.4
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    • pp.589-593
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    • 2006
  • The objective of this study was to evaluate the use of fuzzy math strategy to calculate variability and uncertainty in quantitative risk assessment. We compared the propagation of uncertainty using fuzzy math simulation with Monte Carlo simulation. The risk far Listeria monocytogenes contamination was estimated for carcass and processed pork by fuzzy math and Monte Carlo simulations, respectively. The data used in these simulations were taken from a recent report on pork production. In carcass, the mean values for the risk from fuzzy math and Monte Carlo simulations were -4.393 log $CFU/cm^2$ and -4.589 log $CFU/cm^2$, respectively; in processed pork, they were -4.185 log $CFU/cm^2$ and -4.466 log $CFU/cm^2$ respectively. The distribution of values obtained using the fuzzy math simulation included all of the results obtained using the Monte Carlo simulation. Consequently, fuzzy math simulation was found to be a good alternative to Monte Carlo simulation in quantitative risk assessment of pork production.

Homogenized limit analysis of masonry structures with random input properties: polynomial Response Surface approximation and Monte Carlo simulations

  • Milani, G.;Benasciutti, D.
    • Structural Engineering and Mechanics
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    • v.34 no.4
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    • pp.417-447
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    • 2010
  • The uncertainty often observed in experimental strengths of masonry constituents makes critical the selection of the appropriate inputs in finite element analysis of complex masonry buildings, as well as requires modelling the building ultimate load as a random variable. On the other hand, the utilization of expensive Monte Carlo simulations to estimate collapse load probability distributions may become computationally impractical when a single analysis of a complex building requires hours of computer calculations. To reduce the computational cost of Monte Carlo simulations, direct computer calculations can be replaced with inexpensive Response Surface (RS) models. This work investigates the use of RS models in Monte Carlo analysis of complex masonry buildings with random input parameters. The accuracy of the estimated RS models, as well as the good estimations of the collapse load cumulative distributions obtained via polynomial RS models, show how the proposed approach could be a useful tool in problems of technical interest.

6MV Photon Beam Commissioning in Varian 2300C/D with BEAM/EGS4 Monte Carlo Code

  • Kim, Sangroh;Jason W. Sohn;Cho, Byung-Chul;Suh, Tae-Suk;Choe, Bo-Yong;Lee, Hyoung-Koo
    • Proceedings of the Korean Society of Medical Physics Conference
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    • pp.113-115
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    • 2002
  • The Monte Carlo simulation method is a numerical solution to a problem that models objects interacting with other objects or their environment based upon simple object-object or object-environment relationships. In spite of its great accuracy, It was turned away because of long calculation time to simulate a model. But, it is used to simulate a linear accelerator frequently with the advance of computer technology. To simulate linear accelerator in Monte Carlo simulations, there are many parameters needed to input to Monte Carlo code. These data can be supported by a linear accelerator manufacturer. Although the model of a linear accelerator is the same, a different characteristic property can be found. Thus, we performed a commissioning process of 6MV photon beam in Varian 2300C/D model with BEAM/EGS4 Monte Carlo code. The head geometry data were put into BEAM/EGS4 data. The mean energy and energy spread of the electron beam incident on the target were varied to match Monte Carlo simulations to measurements. TLDs (thermoluminescent dosimeter) and radiochromic films were employed to measure the absorbed dose in a water phantom. Beam profile was obtained in 40cm${\times}$40cm field size and Depth dose was in 10cm${\times}$10cm. At first, we compared the depth dose between measurements and Monte Carlo simulations varying the mean energy of an incident electron beam. Then, we compared the beam profile with adjusting the beam radius of the incident electron beam in Monte Carlo simulation. The results were found that the optimal mean energy was 6MV and beam radius of 0.1mm was well matched to measurements.

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Monte Carlo Studies on an Amorphous Silicon (a-Si:H) Digital X-Ray Imaging Device (무정형 실리콘(a-Si : H) 디지털 X-선 영상기기의 개발을 위한 Monte Carlo 컴퓨터 모의실험연구)

  • 이형구;신경섭
    • Journal of Biomedical Engineering Research
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    • v.19 no.3
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    • pp.225-232
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    • 1998
  • Results of Monte Carlo simulations on amorphous silicon based x-ray imaging arrays are described. In order to investigate the characteristics of amorphous silicon x-ray imaging devices and to provide the optimum design parameter, Monte Carlo simulations were performed. Monte Carlo simulation codes for our purpose were developed and various combinations of x-ray peak voltages, aluminum filter thicknesses, CsI(TI) thicknesses, and amorphous silicon photodiode pixel sizes were tested in connection with detection efficiency and spatial resolution of the amorphous silicon based x-ray imager. With usual Csl(TI) thickness of 300${\mu}{\textrm}{m}$-500${\mu}{\textrm}{m}$, detection efficiency was in the range of 70%-95% and energy absorption efficiency was in the range of 40%-70% for 60kVp-120kVp x-ray. From the simulations it was found that amorphous silicon pixel size and Csl(TI) thickness were the most important parameters which determine the resolution of the imager. By use of our simulation results we could provide proper combinations of Csl(TI) thicknesses and pixels sizes for optimum sensitivity and resolution.

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Domain Decomposition Strategy for Pin-wise Full-Core Monte Carlo Depletion Calculation with the Reactor Monte Carlo Code

  • Liang, Jingang;Wang, Kan;Qiu, Yishu;Chai, Xiaoming;Qiang, Shenglong
    • Nuclear Engineering and Technology
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    • v.48 no.3
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    • pp.635-641
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    • 2016
  • Because of prohibitive data storage requirements in large-scale simulations, the memory problem is an obstacle for Monte Carlo (MC) codes in accomplishing pin-wise three-dimensional (3D) full-core calculations, particularly for whole-core depletion analyses. Various kinds of data are evaluated and quantificational total memory requirements are analyzed based on the Reactor Monte Carlo (RMC) code, showing that tally data, material data, and isotope densities in depletion are three major parts of memory storage. The domain decomposition method is investigated as a means of saving memory, by dividing spatial geometry into domains that are simulated separately by parallel processors. For the validity of particle tracking during transport simulations, particles need to be communicated between domains. In consideration of efficiency, an asynchronous particle communication algorithm is designed and implemented. Furthermore, we couple the domain decomposition method with MC burnup process, under a strategy of utilizing consistent domain partition in both transport and depletion modules. A numerical test of 3D full-core burnup calculations is carried out, indicating that the RMC code, with the domain decomposition method, is capable of pin-wise full-core burnup calculations with millions of depletion regions.

Monte Carlo Simulation Codes for Nuclear Medicine Imaging (핵의학 영상연구를 위한 몬테칼로 모사코드)

  • Chung, Yang Hyun;Beak, Cheal-Ha;Lee, Seung-Jae
    • Nuclear Medicine and Molecular Imaging
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    • v.42 no.2
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    • pp.127-136
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    • 2008
  • Monte Carlo simulation methods are especially useful in studying a variety of problems difficult to calculate by experimental or analytical approaches. Nowadays, they are extensively applied to simulate nuclear medicine instrumentations such as single photon emission computed tomography (SPECT) and positron emission tomography (PET) for assisting system design and optimizing imaging and processing protocols. The goal of this paper is to address the practical issues, a potential user of Monte Carlo simulations for nuclear medicine can encounter, to help them to choose a code. This review introduces the different types of Monte Carlo codes currently available for nuclear medicine, comments main features and properties for a code to be proper for a given purpose, and discusses current research trends in Monte Carlo codes.

Development of Ion Beam Monte Carlo Simulation and Analysis of Focused Ion Beam Processing (이온빔 몬테 카를로 시물레이션 프로그램 개발 및 집속 이온빔 공정 해석)

  • Kim, Heung-Bae
    • Journal of the Korean Society for Precision Engineering
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    • v.29 no.4
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    • pp.479-486
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    • 2012
  • Two of fundamental approaches that can be used to understand ion-solid interaction are Monte Carlo (MC) and Molecular Dynamic (MD) simulations. For the simplicity of simulation Monte Carlo simulation method is widely preferred. In this paper, basic consideration and algorithm of Monte Carlo simulation will be presented as well as simulation results. Sputtering caused by incident ion beam will be discussed with distribution of sputtered particles and their energy distributions. Redeposition of sputtered particles that are experienced refraction at the substrate-vacuum interface additionally presented. In addition, reflection of incident ions with reflection coefficient will be presented together with spatial and energy distributions. This Monte Carlo simulation will be useful in simulating and describing ion beam related processes such as Ion beam induced deposition/etching process, local nano-scale distribution of focused ion beam implanted ions, and ion microscope imaging process etc.

Photon dose calculation of pencil beam kernel based treatment planning system compared to the Monte Carlo simulation

  • Cheong, Kwang-Ho;Suh, Tae-Suk;Kim, Hoi-Nam;Lee, Hyoung-Koo;Choe, Bo-Young;Yoon, Sei-Chul
    • Proceedings of the Korean Society of Medical Physics Conference
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    • pp.291-293
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    • 2002
  • Accurate dose calculation in radiation treatment planning is most important for successful treatment. Since human body is composed of various materials and not an ideal shape, it is not easy to calculate the accurate effective dose in the patients. Many methods have been proposed to solve the inhomogeneity and surface contour problems. Monte Carlo simulations are regarded as the most accurate method, but it is not appropriate for routine planning because it takes so much time. Pencil beam kernel based convolution/superposition methods were also proposed to correct those effects. Nowadays, many commercial treatment planning systems, including Pinnacle and Helax-TMS, have adopted this algorithm as a dose calculation engine. The purpose of this study is to verify the accuracy of the dose calculated from pencil beam kernel based treatment planning system Helax-TMS comparing to Monte Carlo simulations and measurements especially in inhomogeneous region. Home-made inhomogeneous phantom, Helax-TMS ver. 6.0 and Monte Carlo code BEAMnrc and DOSXYZnrc were used in this study. Dose calculation results from TPS and Monte Carlo simulation were verified by measurements. In homogeneous media, the accuracy was acceptable but in inhomogeneous media, the errors were more significant.

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Prediction of Chiral Discrimination by β-Cyclodextrins Using Grid-based Monte Carlo Docking Simulations

  • Choi, Young-Jin;Kim, Dong-Wook;Park, Hyung-Woo;Hwang, Sun-Tae;Jeong, Karp-Joo;Jung, Seun-Ho
    • Bulletin of the Korean Chemical Society
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    • v.26 no.5
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    • pp.769-775
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    • 2005
  • An efficiency of Monte Carlo (MC) docking simulations was examined for the prediction of chiral discrimination by cyclodextrins. Docking simulations were performed with various computational parameters for the chiral discrimination of a series of 17 enantiomers by $\beta$-cyclodextrin ($\beta$-CD) or by 6-amino-6-deoxy-$\beta$-cyclodextrin (am-$\beta$-CD). A total of 30 sets of enantiomeric complexes were tested to find the optimal simulation parameters for accurate predictions. Rigid-body MC docking simulations gave more accurate predictions than flexible docking simulations. The accuracy was also affected by both the simulation temperature and the kind of force field. The prediction rate of chiral preference was improved by as much as 76.7% when rigid-body MC docking simulations were performed at low-temperatures (100 K) with a sugar22 parameter set in the CHARMM force field. Our approach for MC docking simulations suggested that the conformational rigidity of both the host and guest molecule, due to either the low-temperature or rigid-body docking condition, contributed greatly to the prediction of chiral discrimination.