• Journal of the Korean Magnetics Society
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• v.23 no.2
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• pp.62-67
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• 2013

This paper introduces an effective methodology for reliability-based design optimization of electromagnetic products, where a performance measure approach is adopted to accurately assess probabilistic constrains. Two design problems consisting of a loudspeaker and a superconducting magnetic energy storage system are considered. The efficiency of the proposed method in evaluating the failure probability of performances during the optimization process are compared with the existing method based on the reliability index approach. Moreover, in term of the accuracy of probability failure values, optimized design results are examined with reference values obtained from the Monte Carlo simulation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.3
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• pp.1-9
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• 2005

The interaction between hypersonic free stream and side jet flow at high altitudes is investigated by using the direct simulation Monte Carlo (DSMC) method. In order to alleviate the difficulty associated with the large density difference between the free stream and the side jet flow and to simulate the two flows simultaneously, a weighting factor technique is applied. For validation, the corner flow over a pair of plates perpendicularly attached is calculated with and without a side jet, and the results are compared with experiment. For a more realistic configuration, the flow past a blunted cone cylinder shape is solved. The leeward or windward jet is injected into the free stream and the effect on the aerodynamic force and moment is observed at various flow angles. The lambda shock effect and the wake structure are studied in terms of the surface pressure differential. A higher interaction between the free stream and the side jet flow is observed when the side jet is injected in the windward direction.

• Tunnel and Underground Space
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• v.32 no.3
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• pp.231-242
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• 2022

In this study, we developed a robot operating system (ROS)-based autonomous driving robot that estimates the robot's position in underground mines and drives and returns through multiple waypoints. Autonomous driving robots utilize SLAM (Simultaneous Localization And Mapping) technology to generate global maps of driving routes in advance. Thereafter, the shape of the wall measured through the LiDAR sensor and the global map are matched, and the data are fused through the AMCL (Adaptive Monte Carlo Localization) technique to correct the robot's position. In addition, it recognizes and avoids obstacles ahead through the LiDAR sensor. Using the developed autonomous driving robot, experiments were conducted on indoor experimental sites that simulated the underground mine site. As a result, it was confirmed that the autonomous driving robot sequentially drives through the multiple waypoints, avoids obstacles, and returns stably.

• Journal of the Korean Society of Radiology
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• v.11 no.3
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• pp.161-169
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• 2017

The cone beam computed tomography(CBCT) which can acquire 3-dimensions images is widely used for confirmation of patient position before radiation therapy. In this study, through the simulation using the Monte Carlo technique, we will analyze the exposure dose by cone beam computed tomography and present the standardized data. For the experiment, MCNPX(ver. 2.5.0) was used and the photon beam spectrum was analyzed after Cone beam was simulated. As a result of analyzing the photon beam spectrum, the average energy ranged from 25.7 to 37.6 keV at the tube voltage of 80 ~ 120 kVp and the characteristic X-ray energy was 9, 60, 68 and 70 keV. As a result of using the water phantom, the percentage depth dose was measured, and the maximum dose appeared on the surface and decreased with depth. The absorbed dose also decreased as the depth increased. The absorbed dose of the whole phantom was 9.7 ~ 18.7 mGy. This is a dose which accounts for 0.2% of about 10 Gy, which is generally used for radiation therapy per week, which is not expected to have a significant effect on the treatment effect. However, it should not be overlooked even if it is small compared with prescription dose.

• 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.

• Journal of Korea Water Resources Association
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• v.38 no.4 s.153
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• pp.281-292
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• 2005

The water balance analysis for the long-term water resources plan is a simple calculation that compares water demands with possible water supplies. For a watershed being considered the reports on the performance of the water balance analysis, however, have shown inconsistent results and thus have not earned credibility due to the uncertainty of the data acquired and models used. In this research, uncertainties in the water scarcity estimate were assessed through probability representation based on the Monte Carlo simulation using Latin Hypercube Sampling (LHS). The natural flow, municipal demand, industrial demand, agricultural demand, and return flow rate were selected as representative input variables for the water balance analysis, and their distributions were set based on the linear regression and the entropy theory. The statistical properties of the output variable samples were analyzed in comparison with a deterministic estimate of the water scarcity of an existing study. Application of LHS to three sub-basins of the Geum river basin showed the deterministic estimate could be overestimated or underestimated. The sensitivity analysis as well as the uncertainty analysis found that the return flow rate of the agricultural water is the most uncertain but is rarely sensitive to the output of the water balance analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3B
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• pp.259-267
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• 2009

Generalized Extreme Value (GEV) distribution is recommended for flood frequency and extreme rainfall distribution in many country. L-moment method is the most common estimation procedure for the GEV distribution. In this study, the relationships between the cross-site correlations between extreme events and the cross-correlation of estimators of L-moment ratios (L-moment Coefficient of Variation (L-CV) and L-moment Coefficient of Skewness (L-CS)) for data generated from GEV distribution were derived by Monte Carlo simulation. Those relationships were fit to the simple power function. In this Monte Carlo simulation, GEV+ distribution were employed wherein unrealistic negative values were excluded. The simple power models provide accurate description of the relationships between cross-correlation of data and cross-correlation of L-moment ratios. Estimated parameters and accuracies of the power functions were reported for different GEV distribution parameters combinations. Moreover, this study provided a description about regional regression approach using Generalized Least Square (GLS) regression method which require the cross-site correlation among L-moment estimators. The relationships derived in this study allow regional GLS regression analyses of both L-CV and L-CS estimators that correctly incorporate the cross-correlation among GEV L-moment estimators.

• 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.3
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• pp.169-176
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• 2019

In the present study, a CFD/DSMC hybrid method performed by a coupled analysis between the CFD method and the DSMC method was developed to obtain the flow information on the rarefied gas flows effectively. Flow simulations around the high speed vehicles on the transition flow regimes were conducted by using the developed method. The FRESH-FX vehicle made of cone and cylinder shapes was considered for the simulations. The results of the hybrid method were compared with the results of the pure CFD and the pure DSMC method to confirm the reliability and efficiency of the hybrid method. It was found that the gradient and the intensity of the shock waves were weakened due to the relatively low density on the transition flow regime. It was confirmed that the results of the hybrid analysis were different to those of the pure CFD analysis and almost identical to those of the pure DSMC analysis. In addition, the computational time of the hybrid method was reduced than that of the pure DSMC method. As a result, it was obtained that the validity and the efficiency of the CFD/DSMC hybrid method.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.05a
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• pp.190-197
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• 2004

In order to consider statistical properties of probability variables used in the structural analysis, the conventional approach using the safety factor based on past experience usually estimated the safety of a structure. Also, the real structures could only be analyzed with the error in estimation of loads, material characters and the dimensions of the members. But the errors should be considered systematically in the structural analysis. In this paper, we estimated the probability of failure of the pressure vessel. And also, this paper presents sensitivity values of the random variable. Finally, we show that reliability index and probability of failure can present the tolerance limit of dimension of randam variables.