• Journal of the Korean Ceramic Society
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• v.31 no.3
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• pp.241-248
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• 1994

The ionic conductivity in glassy systems were calculated as functions of temperature and ion concentration using Monte-Carol method considering interaction between neighbouring ion-site occupancies, {{{{ rho }}'s. Also the vacancy availability factor, V, the effective jump frequency factor, W, and the charge correlation factor, fc, have been investigated. The Arrhenius plot could be obtained from the ln {{{{ sigma }}T vs. 1/T* plots and was in exellent agreement with the experimental observations. The effects of the various types of potential well on the ionic conductivity have been considered. The activation energy Eg for ion motion in the glass was 1.3│ε│from the ln {{{{ sigma }}T vs. 1/T* plots.

• Land and Housing Review
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• v.15 no.2
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• pp.73-87
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• 2024

To evaluate the efficiency of commuting patterns, various commuting indicators such as excess commute and commuting potential utilized have been developed and used. It is crucial to calculate these indicators reasonably to reveal the differences in commuting patterns among metropolitan areas and to consider these in the process of formulating commuting policies. However, commuting indicators are generally calculated at the administrative district level, and thus, they are not free from the problem of the modifiable areal unit problem (MAUP). This issue can undermine the rationality of comparing commuting efficiency between metropolitan areas, making it necessary to handle the calculation of commuting indicators carefully. Therefore, this study utilises Monte Carlo Simulation to calculate optimal, actual, and maximum commuting distances, and thereby presents the excess commute and the commuting potential utilized. To apply Monte Carlo Simulation to the context of South Korea, a constrained Monte Carlo Simulation is conducted, where residential and workplace locations used in the simulation are selected based on the actual locations of buildings. The analysis is conducted on 13 metropolitan areas with established metropolitan plans using the 2016 Household Travel Survey data. The commuting indicators calculated through the simulation showed minimal differences compared to the results obtained through conventional methods. The comparison of commuting efficiency among metropolitan areas revealed that even if the degree of spafial balance between residential and workplace locations is similar, the actual commuting patterns can differ significantly. It is suggested that further research considering characteristics such as the area of each metropolitan region will be necessary in the future.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.12
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• pp.566-574
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• 2002

In this paper, the scattered field from a perfectly conducting fractal surface by the Monte-Carlo moment method was computed. An one-dimensional fractal surface was generated by using the fractional Brownian motion model. Back scattering coefficients are calculated with different values of the spectral parameter(S$\_$0/), and fractal dimension(D) which determine characteristics of the fractal surface. The number of surface realization for the computed field, the point number, and the width of surface realization are set to be 80, 2048, and 64L, respectively. In order to verify the computed results these results are compared with those of small perturbation methods, which show good agreement between them.

• Journal of Sensor Science and Technology
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• v.25 no.3
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• pp.229-234
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• 2016

Self-powered neutron detector (SPND) is being widely used to monitor the reactor core of the nuclear power plants. The SPND contains a neutron-sensitive metallic emitter surrounded by a ceramic insulator. Currently, the vanadium (V) SPND has been being developed to be used in OPR1000 nuclear power plants. Some Monte Carlo simulations were accomplished to calculate the initial sensitivity of vanadium emitter material and alumina insulator with a cylindrical geometry. An MCNP code was used to simulate some factors (neutron self-shielding factor and beta escape probability from the emitter) and space charge effect of an insulator necessary to calculate the sensitivity of vanadium detector. The simulation results were compared with some theoretical and experimental values. The method presented here can be used to analyze the optimum design of the vanadium SPND and contribute to the development of TMI (Top-mount In-core Instrumentation) which might be used in the SMART and SMR.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.8
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• pp.24-32
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• 2006

Using a deterministic design optimization, the effect of uncertainty can result in violation of constraints and deterioration of performances. For this reason, design optimization is required to guarantee reliability for constraints and ensure robustness for an objective function under uncertainty. Therefore, this study drew Monte Carlo Simulation(MCS) for the evaluation of reliability and robustness, and selected an artificial neural network as an approximate model that is suitable for MCS. Applying to the aero-structural optimization problem of aircraft wing, we can explore robuster optima satisfying the sigma level of reliability than the baseline.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.4
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• pp.401-406
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• 2003

This paper deals with stress analysis of single-lap adhesive joints which have uncertain material properties. Basically, material properties have a certain amount of scatter and such uncertainties can affect the performance of joints. In this paper, the convex modeling is introduced to consider such uncertainties in calculating peel and shear stress of adhesive joints and the results are compared with those from the Monte Carlo simulation. Numerical results show that stresses increase when uncertainties considered, which indicates that such uncertainties should not be ignored for estimation of structural safety. Also, the results obtained by the convex modeling and the Monte Carlo simulation show good agreement, which demonstrates the effectiveness of convex modeling.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.104-110
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• 2014

This paper considers two reconstruction schemes of structured-sparse signals, turbo inference and Markov chain Monte Carlo (MCMC) inference, in compressed sensing(CS) technique that is recently getting an important issue for an efficient video wireless transmission system using multi-copter as an unmanned aerial vehicle. Proposed reconstruction algorithms are setting importance on reduction of image data sizes, fast reconstruction speed and errorless reconstruction. As a result of experimentation with twenty kinds of images, we can find turbo reconstruction algorithm based on loopy belief propagation(BP) has more excellent performances than MCMC algorithm based on Gibbs sampling as aspects of average reconstruction computation time, normalized mean squared error(NMSE) values.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.5
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• pp.992-1002
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• 1988

The dynamic response of rotor-bearing systems subjected to six-component nonststionary earthquake ground accelerations is analyzed. The governing equations of motion for the rotor are derived using Lagrangian approach. The six-component earthquake inputs result in both inhomogeneous and parametric excitations, so that the conventional spectral analysis of random vibration is not applicable. The method of Monte Carlo simulation is utilized to simulate the six-component nonstationary earthquake ground motions and to determine the response statistics of rotor-bearing systems. The significant influences due to rotational motions of seismic base on the overall structural response is demonstrated by a numerical example.

• Journal of Korea Water Resources Association
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• v.37 no.9
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• pp.719-727
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• 2004

Water quality models can be applied to manage the regional water quality problems and to estimate the target and allowable pollution load in watershed effectively. The optimization of state variables in the given water quality model Is necessary to build up more effective model. The least-squares method is applied to fit field observations in QUAL2E developed by U.S. EPA, which is most widely used one in the world to simulate the stream water quality, and the optimization model with constraints is constructed to estimate the parameters. The objective function of the optimization model is solved by Solver in Microsoft Excel and Monte Carlo simulation is conducted to know the influence of parameter in conventional pollutants. It is found that this technique is easily implemented and rapidly convergent computational procedure to calibrate the parameters after appling this approach in Anyang stream located in Kyonggi province mainly.

• Journal of IKEEE
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• v.23 no.4
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• pp.1366-1372
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• 2019

In this paper, we designed a revised neural network to remove the Monte Carlo Rendering noise contained in the ray tracing graphics. The Monte Carlo Rendering is the best way to enhance the graphic's realism, but because of the need to calculate more than thousands of light effects per pixel, rendering processing time has increased rapidly, causing a major problem with real-time processing. To improve this problem, the number of light used in pixels is reduced, where rendering noise occurs and various studies have been conducted to eliminate this noise. In this paper, a deep learning is used to remove rendering noise, especially by separating the rendering image into diffuse and specular light, so that the structure of the dual neural network is designed. As a result, the dual neural network improved by an average of 0.58 db for 64 test images based on PSNR, and 99.22% less light compared to reference image, enabling real-time race-tracing rendering.