• Title/Summary/Keyword: 몬테카를로 모사기법

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Prediction of Probabilistic Distribution of a Loudspeaker's Performance Due to Manufacturing Tolerances by Performance Moment Integration Method (성능 모멘트 적분법을 이용한 제작공차에 의해 발생하는 스피커 성능함수의 확률분포 특성 예측)

  • Kang, Byung-su;Back, Jong Hyun;Kim, Dong-Hun
    • Journal of the Korean Magnetics Society
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    • v.26 no.3
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    • pp.81-85
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    • 2016
  • This paper introduces a performance integration method to predict variation characteristic of a performance function of electromagnetic machines or devices due to manufacturing tolerances. A normalized performance function space and a hybrid mean value technique are adapted to effectively predict mean and variance, which can identify probabilistic distribution of the performance function. To verify the effectiveness and accuracy of the proposed method, a mathematical problem and a loudspeaker model are tested, and numerical results are compared with those of existing methods such as Monte Carlo simulation and univariate dimension reduction method.

Camber Reconstruction for a Prefab PSC Girder Using Collocated Strain Measurements (병치된 변형률 계측치를 이용한 프리팹 PSC 거더 캠버 재구성)

  • Kim, Hyun Young;Ko, Do Hyeon;Park, Hyun Woo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.42 no.2
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    • pp.151-162
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    • 2022
  • Prefab members have attracted attention because they can be mass-produced in factories through smart construction technology. For prefab prestressed concrete girders, it is important to manage the shapes of the girders properly from production to the pre-installation stage for consistency with the prefab floor plate during the erection process. This paper presents a camber reconstruction method using collocated strain measurements from the top and bottom of the prefab girder. In particular, the camber reconstruction method is applied to measured strain data in which the time-dependent behavior of concrete is considered after the introduction of prestress. Through Monte Carlo numerical simulations, the statistical accuracy of the reconstructed camber for a limited number of sensors, measurement errors, and nonlinear time-dependent behaviors are analyzed and validated.

Monte Carlo Simulation of Absorbed Energy by Gold Nano-Particles for Proton (양성자에 대한 금 나노입자의 밀도에 따른 흡수 에너지의 몬테카를로 전산모사)

  • Kwon Su Chon
    • Journal of the Korean Society of Radiology
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    • v.18 no.1
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    • pp.1-9
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    • 2024
  • Proton therapy is known for its superior treatment method due to Bragg peak. To enhance the therapeutic effects of protons, research has been conducted on distributing gold nanoparticles within tumors to increase the absorbed dose. While previous studies focused on handling gold nanoparticles at micrometer and nonometer scale, this study proposes a method to computationally estimate the effect of gold nanoparticles at the millimeter scale. The Geant4 toolkit was applied to computational modeling. Assuming a uniform distribution of water, similar to the human body, and gold nanoparticles, the concentration of gold nanoparticles was adjusted using density ratios. When the density ratio was 5%, the gain in absorbed energy due to gold nanoparticles was nearly twice that of the pure water phantom at the Bragg peak. As the density ratio increased, the gain in absorbed energy linearly increased. When gold nanoparticles were distributed in only one voxel at the Bragg peak, the energy of the protons affected only the neighboring voxels. However, in cases where gold nanoparticles were distributed over a wide area, the volume showing 95% of the maximum absorbed energy (9.46 keV) for the pure water phantom (9.95 keV) exhibited an improvement in absorbed energy over a region 16 times larger, and this region increased as the density ratio increased. Further research is needed to quantify the relationship between the density ratio of gold nanoparticles and the relative biological effect (RBE) in the millimeter scale.

Determination of Dose Correction Factor for Energy and Directional Dependence of the MOSFET Dosimeter in an Anthropomorphic Phantom (인형 모의피폭체내 MOSFET 선량계의 에너지 및 방향 의존도를 고려하기 위한 선량보정인자 결정)

  • Cho, Sung-Koo;Choi, Sang-Hyoun;Na, Seong-Ho;Kim, Chan-Hyeong
    • Journal of Radiation Protection and Research
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    • v.31 no.2
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    • pp.97-104
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    • 2006
  • In recent years, the MOSFET dosimeter has been widely used in various medical applications such as dose verification in radiation therapeutic and diagnostic applications. The MOSFET dosimeter is, however, mainly made of silicon and shows some energy dependence for low energy Photons. Therefore, the MOSFET dosimeter tends to overestimate the dose for low energy scattered photons in a phantom. This study determines the correction factors to compensate these dependences of the MOSFET dosimeter in ATOM phantom. For this, we first constructed a computational model of the ATOM phantom based on the 3D CT image data of the phantom. The voxel phantom was then implemented in a Monte Carlo simulation code and used to calculate the energy spectrum of the photon field at each of the MOSFET dosimeter locations in the phantom. Finally, the correction factors were calculated based on the energy spectrum of the photon field at the dosimeter locations and the pre-determined energy and directional dependence of the MOSFET dosimeter. Our result for $^{60}Co$ and $^{137}Cs$ photon fields shows that the correction factors are distributed within the range of 0.89 and 0.97 considering all the MOSFET dosimeter locations in the phantom.

Evaluation of the Probability of Failure in Rock Slope Using Fuzzy Reliability Analysis (퍼지신뢰도(fuzzy reliability) 해석기법을 이용한 암반사면의 파괴확률 산정)

  • Park, Hyuck-Jin
    • Economic and Environmental Geology
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    • v.41 no.6
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    • pp.763-771
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    • 2008
  • Uncertainties are pervasive in engineering geological problems. Therefore, the presence of uncertainties and their significance in analysis and design of slopes have been recognized. Since the uncertainties cannot be taken into account by the conventional deterministic approaches in slope stability analysis, the probabilistic analysis has been considered as the primary tool for representing uncertainties in mathematical models. However, some uncertainties are caused by incomplete information due to lack of information, and those uncertainties cannot be handled appropriately by the probabilistic approach. For those uncertainties, the theory of fuzzy sets is more appropriate. Therefore, in this study, fuzzy reliability analysis has been proposed in order to deal with the uncertainties which cannot be quantified in the probabilistic analysis due to the limited information. For the practical example, a slope is selected in this study and both the probabilistic analysis and the fuzzy reliability analysis have been carried out for planar failure. In the fuzzy reliability analysis, the dip angle and internal friction angle of discontinuity are considered as triangular fuzzy numbers since the random properties of the variables cannot be obtained completely under the conditions of limited information. In the study, the fuzzy reliability index and the probabilities of failure are evaluated from fuzzy arithmetic and compared to those from the probabilistic approach using Monte Carlo simulation and point estimate method. The analysis results show that the fuzzy reliability analysis is more appropriate for the condition that the uncertainties arise due to incomplete information.