• Nuclear Engineering and Technology
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• v.56 no.3
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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.

• Journal of Environmental Science International
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• v.15 no.4
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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.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.28 no.6
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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.

• Food Science and Biotechnology
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• v.16 no.3
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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.

• Journal of the Korean Statistical Society
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• v.28 no.2
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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.

• Nuclear Engineering and Technology
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• v.55 no.7
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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.

• Journal of Biomedical Engineering Research
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• v.20 no.2
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• pp.199-204
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• 1999

As the correct measuring of the light dosimetry in biological tissues give the important affection to the effect of PDT treatment we used Monte Carlo simulation to measure the light dosimetry on this study. The parameters using in experiments are the optical properties of the real biological tissue, and we used Henyey-Greenstein phase function among the phase functions. As we results, we displayed the result the change of Fluence rate and the difference against the previous theory was at least 0.35%. Biological tissues using in experiment were Human tissue, pig tissue, rat liver tissue and rabbit muscle tissue. The most of biological tissue have big scattering coefficient in visible wavelength which influences penetration depth. The penetration depth of human tissue in visible region is 1.5~2cm. We showed that it is possible to measure fluence rate and penetration depth within the biological tissues by Monte Carlo simulation very well.

• Communications for Statistical Applications and Methods
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• v.22 no.1
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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.

• ETRI Journal
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• v.35 no.2
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• pp.332-335
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• 2013

In this letter, the acoustic noise due to long term evolution (LTE) user equipment (UE) is investigated with various transmitting powers of the LTE UE by using the Monte Carlo method in a practical acoustic noise experiment.

• International Journal of Automotive Technology
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• v.6 no.6
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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.