• Journal of Energy Engineering
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• v.22 no.2
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• pp.175-183
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• 2013

For the optimal design of the vehicle electric system, it is important to have a reliable modeling tool to predict the dynamic behavior of the automotive battery. In this work, a one-dimensional modeling was carried-out to predict the dynamic behaviors of a 12-V automotive lead-acid battery. The model accounted for electrochemical kinetics and ionic mass transfer in a battery cell. In order to validate the modeling, modeling results were compared with the experiment data of the dynamic behaviors of the lead-acid batteries of two different capacities that were mounted on the automobiles manufactured by Hyundai Motor Company. The discharge behaviors were measured with various discharge rates of C/3, C/5, C/10, C/20 and combination. And dynamic behaviors of charge and discharge were measured. The voltage curves from the experiment and simulation were in good agreement. Based on the modeling, the distributions of the electrical potentials of the solid and solution phases, and the current density within the electrodes could be predicted as a function of charge and discharge time.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.4
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• pp.204-211
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• 2011

A dynamic analysis procedure is developed to provide a better estimation of the dynamic responses of bridge during the passage of high speed railway vehicles. Particularly, a three dimensional numerical model including the structural interaction between high speed vehicles, bridges and railway endures to analyse accurately and evaluate with in-depth parametric studies for dynamic responses of various bridge span lengths running KTX railway locomotive up to increasing maximum speed(450km/h). Three dimensional frame element is used to model the simply supported pre-stressed concrete (PSC) box bridges for four span lengths(40~25m). Track irregularity employed as a stationary random process from the given spectral density functions and irregularities of both sides of the track are assumed to have high correlation. The high-speed railway vehicle (KTX) is used as 38-degree of freedom system. Three displacements (Vertical, lateral, and longitudinal) as well as three rotational components (Pitching, rolling, and yawing) are considered in the 38-degree of freedom model. The dynamic amplification factors are evaluated by the developed procedure under various traveling conditions, such as track irregularity camber, train speed and ballast. The dynamic analysis such as Newmark-${\beta}$ and Runge-Kutta methods which are able to analyse considering the dynamic impact factors are compared and contrasted.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.6
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• pp.48-55
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• 2009

The feedback interference channels are those made through the multipaths that are built by moving and stationary objects around transmit and receive antennas mounted at the same point. This paper describes the method to measure the feedback interference channels in the rural regions and sides of highways and the analysis on channel characteristic parameters. Using the measured samples, we estimated scattering functions, delay power spectra, and Doppler power spectra, and we analyzed the channels using eight parameters including coherence bandwidth, coherence time, maximum excess delay, average excess delay, rms delay spread, Doppler shift, Doppler spread, and spread factor, and delay and Doppler cumulative distributions. Even though many observations are made, note that the feedback signals of high Doppler frequencies and large energy are observed in the sides of highways due to high speed vehicles while low Doppler frequencies occurred in the rural region due to rare traffic.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.4
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• pp.1-9
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• 2009

A simplified model of seat-human body is presented to analyze vibrations of human body on a seat of vehicle. The theoretical model having seven degrees-of-freedom is composed of the inter-connected masses, springs and dampers. Until now, evaluation of ride comfort has been usually performed only through vehicle tests. This study aims to complement shortcomings of conventional vehicle tests in evaluation of ride comfort by using the theoretical model. The acceleration values of the human body are obtained from frequency response functions of the theoretical model. Thereafter, Ride and SEAT indexes are acquired by considering response characteristics of the human body for the 12 axes that are presented in BS 6841. A vehicle test is carried out to measure the acceleration values for the three parts of the human body such as upper body, hip and foot. Ride and SEAT indexes of the vehicle test are also obtained by considering the response characteristics of the human body, of which results are compared with the values from the theoretical model. It is found that the theoretical results are in good agreement with the experimental results.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.6
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• pp.1381-1388
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• 1993

This paper presents a method for the simultaneous optimal design of structural and control systems. Sensitivities of performance index with respect to structural design variables are analyzed. The structural design variables are optimized to minimize the performance index by use of conjugate gradient method. The method is applied to a half model of an active vehicle suspension system with elastic body moving on a randomly profiled road. The suspension control force of an optimally controlled system in the presence of measurement errors are calculated by use of linear quadratic Gaussian control theory and Kalman filter theory. The performance index contains ride comfort, road holding and working space of suspension. The structural design variables taken are stiffness, daming properties and the position of the suspension system. The random road profile considered as colored noise is shaped from white noise by use of shaping filter. The performance of an optimal simultaneous structure/control system is compared with that of an optimal controlled system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.10
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• pp.1125-1131
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• 2014

This work presents a vulnerability assessment procedure for a complex structure using vibration characteristics. The structural behavior of a three-dimensional framed structure subjected to impact forces was predicted using the spectral element method. The Timoshenko beam function was applied to simulate the impact wave propagations induced by a high-velocity projectile at relatively high frequencies. The interactions at the joints were analyzed for both flexural and longitudinal wave propagations. Simulations of the impact energy transfer through the entire structure were performed using the transient displacement and acceleration responses obtained from the frequency analysis. The kill probabilities of the crucial components for an operating system were calculated as a function of the predicted acceleration amplitudes according to the acceptable vibration levels. Following the proposed vulnerability assessment procedure, the vulnerable positions of a three-dimensional combat vehicle with high possibilities of damage generation of components by impact loading were identified from the estimated vibration responses.

• Journal of the Korean Geotechnical Society
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• v.30 no.8
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• pp.5-11
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• 2014

The objective of this paper is to develop a rational reliability analysis procedure for the LRFD design provisions of bridge substructures. A bridge abutments is considered in this study. The reliability analysis is applied to determine the relationship between the major design parameters for bridge abutment and reliability index. The considered load components include dead load, vertical and horizontal earth pressure, earth surcharge, and vehicle live load. Several limit states are considered: foundation bearing capacity, sliding, and overturning. The analysis results show that the most important parameter in the reliability analysis is the effective stress friction angle of the soil. The reliability indices are calculated using Monte Carlo simulations for a selected bridge abutment. The results of the sensitivity analysis indicate that reliability index is most sensitive with regard to resistance factor and horizontal earth pressure factor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.4
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• pp.765-773
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• 2009

Currently Telematics traffic information services have been various because we can collect real-time traffic information through Intelligent Transport System. In this paper, we proposed and implemented a short-term traffic information prediction model for giving to guarantee the traffic information with high quality in the near future. A Short-term prediction model is for forecasting traffic flows of each segment in the near future. Our prediction model gives an average speed on the each segment from 5 minutes later to 60 minutes later. We designed a Bayesian network for each segment with some casual nodes which makes an impact to the road situation in the future and found out its joint probability density function on the supposition of GMM(Gaussian Mixture Model) using EM(Expectation Maximization) algorithm with training real-time traffic data. To validate the precision of our prediction model we had conducted various experiments with real-time traffic data and computed RMSE(Root Mean Square Error) between a real speed and its prediction speed. As the result, our model gave 4.5, 4.8, 5.2 as an average value of RMSE about 10, 30, 60 minutes later, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.603-610
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• 2016

Over 12 years have passed since the first commercial operation of a Korean high-speed train. Since then, the transport capacity of the high-speed lines has become almost saturated. Therefore, studies have been carried out to increase the operating speed of the trains in order to increase their transportation capacity. This study was carried out to improve the critical speed of the KTX-Sancheon, Korean high-speed train, in order to increase its operating speed. A dynamic analysis of the KTX-Sancheon train was performed using the contact data obtained from the wheel wear profiles that were measured from a KTX-Sancheon train in commercial operation. The analysis results were verified by comparing them with the measurement acceleration data obtained from KTX-Sancheon. The suspension parameters were optimized to improve the operation speed. The critical speed of KTX-Sancheon was increased by 9.4% after the optimization by the response surface method. The optimized suspension parameters are expected to be used for the new bogie design to increase the operating speed of KTX-Sancheon from 300km/h to 350km/h.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.1
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• pp.1-12
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• 2008

In this paper, we present a real-time algorithm for recognizing the vehicle color from the indoor and outdoor vehicle images based on GPU (Graphics Processing Unit) acceleration. In the preprocessing step, we construct feature victors from the sample vehicle images with different colors. Then, we combine the feature vectors for each color and store them as a reference texture that would be used in the GPU. Given an input vehicle image, the CPU constructs its feature Hector, and then the GPU compares it with the sample feature vectors in the reference texture. The similarities between the input feature vector and the sample feature vectors for each color are measured, and then the result is transferred to the CPU to recognize the vehicle color. The output colors are categorized into seven colors that include three achromatic colors: black, silver, and white and four chromatic colors: red, yellow, blue, and green. We construct feature vectors by using the histograms which consist of hue-saturation pairs and hue-intensity pairs. The weight factor is given to the saturation values. Our algorithm shows 94.67% of successful color recognition rate, by using a large number of sample images captured in various environments, by generating feature vectors that distinguish different colors, and by utilizing an appropriate likelihood function. We also accelerate the speed of color recognition by utilizing the parallel computation functionality in the GPU. In the experiments, we constructed a reference texture from 7,168 sample images, where 1,024 images were used for each color. The average time for generating a feature vector is 0.509ms for the $150{\times}113$ resolution image. After the feature vector is constructed, the execution time for GPU-based color recognition is 2.316ms in average, and this is 5.47 times faster than the case when the algorithm is executed in the CPU. Our experiments were limited to the vehicle images only, but our algorithm can be extended to the input images of the general objects.