• Macromolecular Research
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• v.11 no.5
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• pp.393-397
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• 2003

By applying a configurational-bias Gibbs ensemble Monte Carlo algorithm, priority simulation results regarding the conformation of non-dilute polyelectrolytes in solvents are obtained. Solutions of freely-jointed chains are considered, and a new method termed strandwise configurational-bias sampling is developed so as to effectively overcome a difficulty on the transfer of polymer chains. The structure factors of polyelectrolytes in the bulk as well as in the confined space are estimated with variations of the polymer charge density.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.22 no.2
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• pp.112-119
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• 2010

A Monte-Carlo simulation method is proposed which can evaluate the target failure/safety levels on any failure modes of harbor structures as a function of central safety factor. Unlike the calibration method based on the average safety level of conventional design criteria, the target failure/safety level can be directly evaluated by only using central safety factors of the harbor structures which have been designed by safety factor method during the past several decade years. Several mathematical relationships are represented to straightforwardly connect the conventional safety factor design method with reliability-based design method. Even though limited data have been used in applying Monte-Carlo simulation method to sliding failure mode of the vertical breakwaters, it is found that target reliability indices evaluated by the suggested method in this paper is satisfactorily agreement with new criteria of reliability index of Japan.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.1
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• pp.6-11
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• 2011

This paper proposes a new collision risk assessment system for pedestrians's safety. Monte Carlo Simulation (MCS) method is a one of the most popular method that rely on repeated random sampling to compute their result, and this method is also proper to get the results when it is unfeasible or impossible to compute an exact result. Nevertheless its advantages, it spends much time to calculate the result of some situation, we apply not only MCS but also Neural Networks in this problem. By Monte carlo method, we make some sample data for input of neural networks and by using this data, neural networks can be trained for computing collision probability of whole area where can be measured by sensors. By using this trained networks, we can estimate the collision probability at each positions and velocities with high speed and low error rate. Computer simulations will be shown the validity of our proposed method.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.10
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• pp.107-114
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• 1996

Monte carlo method is especially a useful method for the analysis of thermal noise of semiconductor devices since the time dependence of microscopic details is simulated directly. Recently, a mthod for the calculation of the instantaneous currents of 2-dimensional devices, which is numerically more accurate than the conventional method, has been proposed using the generalized ramo-shockley theorem. Using this mehtod we investage the validity of the existing thermal noise theories of field-effect transistors. First, the 1-dimensional analysis of thermal noise theories of field-effect transistors. First, the 1-dimensional analysis of thermal noise theories of field-effect transistors. First, the 1-dimensional analysis of thermal noise using ramo-shockley theorem is shown to be applicable to 2 dimensional devices if the frequency of interest is low enough. The correlation between electrons in different regions of th echannel is shown not to be negligible. And we also obtian the spatial map of the noise in the channel region. By doing so, we show that the steady state nyquist theorem is the correct theory rather than the theory by van der ziel et.al.

• Nuclear Engineering and Technology
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• v.18 no.1
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• pp.38-47
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• 1986

A statistical procedure, which uses response surface method and Monte Carlo simulation technique, is proposed for analyzing the thermal margin of light water reactor core. The statistical thermal margin analysis method performs the best.estimate thermal margin evaluation by the probabilistic treatment of uncertainties of input parameters. This methodology is applied to KNU-1 core thermal margin analysis under the steady state nominal operating condition. Also discussed are the comparisons with conventional deterministic method and Improved Thermal Design Procedure of Westinghouse. It is deduced from this study that the response surface method is useful for performing the statistical thermal margin analysis and that thermal margin improvement is assured through this procedure.

• ETRI Journal
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• v.38 no.1
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• pp.141-148
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• 2016

This paper proposes a method to estimate directly the incoherent scattered intensity and radar cross section (RCS) from the effective permittivity of a random media. The proposed method is derived from the original concept of incoherent scattering. The incoherent scattered field is expressed as a simple formula. Therefore, to reduce computation time, the proposed method can estimate the incoherent scattered intensity and RCS of a random media. To verify the potential of the proposed method for the desired applications, we conducted a Monte-Carlo analysis using the method of moments; we characterized the accuracy of the proposed method using the normalized mean square error (NMSE). In addition, several medium parameters, such as the density of scatterers and analysis volume, were studied to understand their effect on the scattering characteristics of a random media. The results of the Monte-Carlo analysis show good agreement with those of the proposed method, and the NMSE values of the proposed method and Monte-Carlo analysis are relatively small at less than 0.05.

• Nuclear Engineering and Technology
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• v.16 no.2
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• pp.97-105
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• 1984

A method and computer code for the uncertainty analysis in the top event unavailability are developed and tested by combining Monte Carlo Method and Moments method with fault tree reduction technique. Using system fault trees and unavailability data selected in WASH-1400, the efficiency of the proposed method is tested and these results are compared with those obtained by Monte Carlo method. It is shown that the results are sufficiently good in accuracy and computation time is considerably reduced compared with those by Monte Carlo method.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.12 s.189
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• pp.72-79
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• 2006

Vibration of a non-linear system under random parametric excitations was evaluated by probabilistic methods. The non-linear characteristic terms of a system structure were quasi-linearized and excitation terms were remained as they were An analytical method where the square mean of error was minimized was used An alternative method was an energy method where the damping energy and restoring energy of the linearized system were equalized to those of the original non-linear system. The numerical results were compared with those obtained by Monte Carlo simulation. The comparison showed the results obtained by Monte Carlo simulation located between those by the analytical method and those by the energy method.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.785-790
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• 2008

Vibration of a non-linear system under random parametric excitations was evaluated by probablistic methods. The non-linear characteristic terms of a system were quasi-linearized and excitation terms were remained as they were given. An analytical method where the square mean of error was minimized was ysed. An alternative method was an energy method where the damping energy and rstoring energy of the linearized system were equalized to those of the original non-linear system. The numerical results were compared with those obtained by Monte Carlo simulation. The comparison showed the results obtained by Monte Carlo simulation located between those by the analytical method and those by the energy method.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.305-313
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• 2002

Regarding to inference about a scalar measure of internal scatter of Ρ-variate normal population, this paper considers an interval estimation of the generalized variance, │$\Sigma$│. Due to complicate sampling distribution, fully parametric frequentist approach for the interval estimation is not available and thus Bayesian method is pursued to calculate the highest probability density (HPD) interval for the generalized variance. It is seen that the marginal posterior distribution of the generalized variance is intractable, and hence a weighted Monte Carlo method, a variant of Chen and Shao (1999) method, is developed to calculate the HPD interval of the generalized variance. Necessary theories involved in the method and computation are provided. Finally, a simulation study is given to illustrate and examine the proposed method.