• 제목/요약/키워드: Monte-carlo experiment

검색결과 165건 처리시간 0.033초

Sensitivity of a control rod worth estimate to neutron detector position by time-dependent Monte Carlo simulations of the rod drop experiment

  • Jong Min Park;Cheol Ho Pyeon;Hyung Jin Shim
    • Nuclear Engineering and Technology
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    • 제56권3호
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    • pp.916-921
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    • 2024
  • The control rod worth sensitivity to the neutron detector position in the rod drop experiment is studied by the time-dependent Monte Carlo (TDMC) neutron transport calculations for AGN-201K educational reactor and the Kyoto University Critical Assembly. The TDMC simulations of the rod drop experiments are conducted by the Seoul National University Monte Carlo (MC) code, McCARD, yielding time-dependent neutron densities at detector positions. The detector-position-dependent results of the total control rod worth calculated by the extrapolation, the integral counting, and the inverse methods are compared with the numerical reference using the MC eigenvalue calculations and the experimental results. From these comparisons, it is observed that the total control rod worth can be estimated with a considerable difference depending on the detector position through the rod drop experiment. The proposed TDMC simulation of the rod drop experiment can be applied for searching a better detector position or quantifying a bias for the control rod worth measurement.

Monte Carlo 방법을 이용한 대기오염 배출률 예측의 불확실성 평가 (Uncertainty Evaluation of the Estimated Release Rate for the Atmospheric Pollutant Using Monte Carlo Method)

  • 정효준;김은한;서경석;황원태;한문희
    • 한국환경과학회지
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    • 제15권4호
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    • pp.319-324
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    • 2006
  • Release rate is one of the important items for the environmental impact assessment caused by radioactive materials in case of an accidental release from the nuclear facilities. In this study, the uncertainty of the estimated release rate is evaluated using Monte Carlo method. Gaussian plume model and linear programming are used for estimating the release rate of a source material. Tracer experiment is performed at the Yeoung-Kwang nuclear site to understand the dispersion characteristics. The optimized release rate was 1.56 times rather than the released source as a result of the linear programming to minimize the sum of square errors between the observed concentrations of the experiment and the calculated ones using Gaussian plume model. In the mean time, 95% confidence interval of the estimated release rate was from 1.41 to 2.53 times compared with the released rate as a result of the Monte Carlo simulation considering input variations of the Gaussian plume model. We confirm that this kind of the uncertainty evaluation for the source rate can support decision making appropriately in case of the radiological emergencies.

A Monte Carlo Computer Simulation Study for Blue Crab Capture Efficiency Experiment

  • ENDO Shinichi;ZHANG Chang Ik
    • 한국수산과학회지
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    • 제28권6호
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    • pp.720-727
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    • 1995
  • A Monte Carlo computer simulation study was conducted to determine the most efficient sampling design for the blue crab dredge capture efficiency experiment performed in Chesapeake Bay, Maryland, U. S. A. The input values were the number of dredge tracks in each experimental area, the number of tows per experiment, the number of experiments, the mean density of crabs per unit area, the negative binomial coefficient, the gear capture efficiency, and the tow error. As a result of the study, a four-track experiment with twenty to twenty-eight tows was estimated to be the best in terms of precision and accuracy of the gear capture efficiency.

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Comparison of Monte Carlo Simulation and Fuzzy Math Computation for Validation of Summation in Quantitative Risk Assessment

  • Im, Myung-Nam;Lee, Seung-Ju
    • Food Science and Biotechnology
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    • 제16권3호
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    • pp.361-366
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    • 2007
  • As the application of quantitative risk assessment (QRA) to food safety becomes widespread, it is now being questioned whether experimental results and simulated results coincide. Therefore, this paper comparatively analyzed experimental data and simulated data of the cross contamination, which needs summation of the simplest calculations in QRA, of chicken by Monte Carlo simulation and fuzzy math computation. In order to verify summation, the following basic operation was performed. For the experiment, thigh, breast, and a mixture of both parts were preserved for 24 hr at $20^{\circ}C$, and then the cell number of Salmonella spp. was measured. In order to examine the differences between experimental results and simulated results, we applied the descriptive statistics. The result was that mean value by fuzzy math computation was more similar to the experimental than that by Monte Carlo simulation, whereas other statistical descriptors by Monte Carlo simulation were more similar.

Asymptotic Comparison of Latin Hypercube Sampling and Its Stratified Version

  • Lee, Jooho
    • Journal of the Korean Statistical Society
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    • 제28권2호
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    • pp.135-150
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    • 1999
  • Latin hypercube sampling(LHS) introduced by McKay et al. (1979) is a widely used method for Monte Carlo integration. Stratified Latin hypercube sampling(SLHS) proposed by Choi and Lee(1993) improves LHS by combining it with stratified sampling. In this article it is shown that SLHS yields an asymptotically more accurate than both stratified sampling and LHS.

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Advances for the time-dependent Monte Carlo neutron transport analysis in McCARD

  • Sang Hoon Jang;Hyung Jin Shim
    • Nuclear Engineering and Technology
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    • 제55권7호
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    • pp.2712-2722
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    • 2023
  • For an accurate and efficient time-dependent Monte Carlo (TDMC) neutron transport analysis, several advanced methods are newly developed and implemented in the Seoul National University Monte Carlo code, McCARD. For an efficient control of the neutron population, a dynamic weight window method is devised to adjust the weight bounds of the implicit capture in the time bin-by-bin TDMC simulations. A moving geometry module is developed to model a continuous insertion or withdrawal of a control rod. Especially, the history-based batch method for the TDMC calculations is developed to predict the unbiased variance of a bin-wise mean estimate. The developed methods are verified for three-dimensional problems in the C5G7-TD benchmark, showing good agreements with results from a deterministic neutron transport analysis code, nTRACER, within the statistical uncertainty bounds. In addition, the TDMC analysis capability implemented in McCARD is demonstrated to search the optimum detector positions for the pulsed-neutron-source experiments in the Kyoto University Critical Assembly and AGN201K.

Monte Csrlo 시뮬레이션을 이용한 생체조직내의 광선량 측정 (Measuring the Light Dosimetry Within Biological Tissue Using Monte Carlo Simulation)

  • 임현수;구철희
    • 대한의용생체공학회:의공학회지
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    • 제20권2호
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    • pp.199-204
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    • 1999
  • 생체조직내의 정확한 광선량 측정이 PDT 치료의 효과에 중요한 영향을 주므로 본 연구에서는 광선량 측정을 위해서 Monte Carlo 시뮬레이션을 이용하였다. 실험에 사용한 계수는 실제 생체조직의 광학계수이고 위상함수는 Henyey-Greenstein 위상함수를 사용하였다. 결과는 깊이에 따른 Fluency rate의 변화로 나타내었으며 기존 이론과의 차이는 0.35%에 지나지 않았다. 실험에 사용한 생체조직은 인체조직, 돼지조직, 쥐간조직, 토기근육조직이다. 대부분의 생체조직은 가시광선영역에서 큰 산란계수를 가지고 있으며 이것은 투과도에 큰 영향을 미치는 것으로 밝혀졌다. 가시광선 영역에서 인체조직의 투과 깊이는 1.5~2cm이었다. Monte Carlo 시뮬레이션을 이용하여 생체조직내의 광전파(light propagation), 광선량(light dosimetry), 에너지율(fluence rate), 투과깊이(penetration depth)를 효과적으로 측정할 수 있음을 보여주었다.

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Stationary Bootstrap for U-Statistics under Strong Mixing

  • Hwang, Eunju;Shin, Dong Wan
    • Communications for Statistical Applications and Methods
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    • 제22권1호
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    • pp.81-93
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    • 2015
  • Validity of the stationary bootstrap of Politis and Romano (1994) is proved for U-statistics under strong mixing. Weak and strong consistencies are established for the stationary bootstrap of U-statistics. The theory is applied to a symmetry test which is a U-statistic regarding a kernel density estimator. The theory enables the bootstrap confidence intervals of the means of the U-statistics. A Monte-Carlo experiment for bootstrap confidence intervals confirms the asymptotic theory.

QUALITY IMPROVEMENT OF VEHICLE DRIFT USING STATISTICAL SIX SIGMA TOOLS

  • PARK T. W.;SOHN H. S.
    • International Journal of Automotive Technology
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    • 제6권6호
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    • pp.625-633
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    • 2005
  • Vehicle drift was reduced using statistical six sigma tools. The study was performed through four steps: M (measure), A (analyze), I (improve), and C (control). Step M measured the main factors which were derived from a fishbone diagram. The measurement system capabilities were analyzed and improved before measurement. Step A analyzed critical problems by examining the process capability and control chart derived from the measured values. Step I analyzed the influence of the main factors on vehicle drift using DOE (design of experiment) to derive the CTQ (critical to quality). The tire conicity and toe angle difference proved to be CTQ. This information enabled the manufacturing process related with the CTQ to be improved. The respective toe angle tolerance for the adjustment process was obtained using the Monte Carlo simulation. Step C verified and controlled the improved results through hypothesis testing and Monte Carlo simulation.