• Journal of the korean Society of Automotive Engineers
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• v.13 no.5
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• pp.42-50
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• 1991

According as the members and inner and outer plates of the automobile body structure have been thinned their thickness and have become high strength, each part of the body structure has been put more severe stress condition. Therefore, it has been increasingly required to improve the fatigue strength of the spot welded structures. As one of the improving methods for such problem, the author had previously proposed the method of alleviating stress concentration at nugget edge of the spot weld part and improving its fatigue strength [1]. But, because fatigue strength of the spot welded lap joint is influenced by its geometrical and mechanical factors, welding condition and etc., there needs a quantitative and systematic estimation method of them. In this report, by considering nugget edge of the spot weld part of the spot welded lap joint subjected to tensile load to the ligament crack, fatigue strength of various spot welded lap joints was estimated with the stress intensity factor (S.I.F.) K which is fracture mechanical parameter. It is known that evaluation of fatigue strength of the spot welded lap joint by the stress intensity factor (S.I.F.) K is more effective than the maximum stress $(\sigma_{ymax}$) at edge of the spot weld part on the center line of width of the plate.

• Analytical Science and Technology
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• v.8 no.3
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• pp.335-340
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• 1995

Automatic biochemical oxygen demand(BOD) measurement system has heen developed using a microbial membrane electrode, prepared from Bacillus subtilis and polyvinyl alcohol(PVA). The automatic BOD measurement system showed a linear response curve up to BOD 60 ppm using a glucose/glutamic acid standard solution, and all the BOD measurement processes are carried out automatically to calculate BOD whithin 10 min after each sample injection. The response times of the microbial electrode was 5 minutes with a 5 min recovery time between measurements and the relative error of the BOD estimation was within 10%.

• Wind and Structures
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• v.8 no.5
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• pp.343-356
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• 2005

Overhead sign support structures number in the tens of thousands throughout the trunk-line roadways in the United States. A recent two-phase study sponsored by the National Cooperative Highway Research Program resulted in the most significant changes to the AASHTO design specifications for sign support structures to date. The driving factor for these substantial changes was fatigue related cracks and some recent failures. This paper presents the method and results of a subsequent study sponsored by the Michigan Department of Transportation (MDOT) to develop a relative performance-based procedure to rank overhead sign support structures around the United States based on a linear combination of their expected fatigue life and an approximate measure of cost. This was accomplished by coupling a random vibrations approach with six degree-of-freedom linear dynamic models for fatigue life estimation. Approximate cost was modeled as the product of the steel weight and a constructability factor. An objective function was developed and used to rank selected steel sign support structures from around the country with the goal of maximizing the objective function. Although a purely relative approach, the ranking procedure was found to be efficient and provided the decision support necessary to MDOT.

• Journal of electromagnetic engineering and science
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• v.1 no.1
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• pp.30-36
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• 2001

Whereas it is well known that microwave propagation around corners of urban area is estimated well by the uniform geometrical theory of diffraction (UTD), it is not clear how much depolarization occurs at a given receiver position and how much transmission through walls affects to total path loss. This paper presents the results of the ray tracing simulation to answer these questions. Simulations of microwave propagation around corners were performed for various line-of-sight (LOS) and out-of-sight(OOS) positions of a receiver, by summing the electrical fields of reflected, diffracted and transmitted rays coherently. Since height difference between transmitter and receiver, as well as ground plane, causes depolarization, the ray tracing simulation estimates the cross-polarization coupling. It was found that the cross-polarization coupling decreases as receiver moves away from transmitter. Another part of the study focused on the signal transmitted through building walls of the corner. It was found that the transmitted field is dominant at OOS region when the conductivity of the walls is low (for example, lower than 0.0l S/m). The simulation results of the ray tracing technique in this study agreed well with an experimental measurement around corners.

• Journal of Power Electronics
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• v.14 no.5
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• pp.1008-1027
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• 2014

An electric scooter with a V-belt continuously variable transmission (CVT) driven by a permanent magnet synchronous motor (PMSM) has a lot of nonlinear and time-varying characteristics, and accurate dynamic models are difficult to establish for linear controller designs. A PMSM servo-drive electric scooter controlled by a novel hybrid modified recurrent Legendre neural network (NN) control system is proposed to solve difficulties of linear controllers under the occurrence of nonlinear load disturbances and parameters variations. Firstly, the system structure of a V-belt CVT driven electric scooter using a PMSM servo drive is established. Secondly, the novel hybrid modified recurrent Legendre NN control system, which consists of an inspector control, a modified recurrent Legendre NN control with an adaptation law, and a recouped control with an estimation law, is proposed to improve its performance. Moreover, the on-line parameter tuning method of the modified recurrent Legendre NN is derived according to the Lyapunov stability theorem and the gradient descent method. Furthermore, two optimal learning rates for the modified recurrent Legendre NN are derived to speed up the parameter convergence. Finally, comparative studies are carried out to show the effectiveness of the proposed control scheme through experimental results.

• KIEAE Journal
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• v.14 no.5
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• pp.75-80
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• 2014

An attempt has been made to prove the so-called 'feature accumulation theory'. It is the theory describing that people tend to feel the same space with more identifiable objects much larger than that with fewer objects. Applying this theory to our cognition of spatial size, this paper made an experiment. Students were asked that if the lecture room they are sitting becomes a module (module 1), then how large are the questioned spaces in the campus. The result was striking. Through the mental image processing, they answered that the library and the architecture building looks much smaller than they actually are, and more surprisingly the basketball field much more smaller than it really is. This experiment shows that there is a strong tendency by which people regard the space much larger when there are more occupiable or behavior-causing elements in the space. In the case of basketball field, since there is nothing that can be occupied, this open space is seen as a small space for the subjects. This line of cognitive perception can be applied to the practice of urban planning and architectural planning. With the same size of given space, we can make it feel more rich and larger.

• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.225-227
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed artificial intelligent-PI(AIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.4
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• pp.660-668
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• 1994

In this paper, a new approach to estimate nonmlinear distortions (second-harmonic, second-intermodulation, third-harmonic, and third-intermodulation) in digital communication systems is proposed. In contrast to the relatively common sine-wave input approach which requires repetition of the same experiments by changing frequencies of oscillators and filters over the band of frequencies of interest, the proposed approach uses digital random input (transmitted signal in digital communication system) to adaptively estimate parameters of a nonlinear channel in time-domain. Nonlinear distortion of the channel is estimated on line by transforming the estimated parameters into frequency-domain. Comparison between the classical two-tone input approach and the proposed approach is made through computer simulation.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.420-423
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed hybrid intelligent-PI(HIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.

• Journal of Korean Society of Water and Wastewater
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• v.16 no.6
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• pp.686-699
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• 2002

The purpose of this study is to estimate deterioration factors and weighting factors in pipe network which each local self-governments takes rehabilitation and replacement work present time. Deterioration factors in pipe network are able to effected of specific province or location related with water supply. Most of water supply pipes are laid under the ground, it is hard to quantify deterioration degree of water system. Moreover, the timing and economic limitation and insufficient information on the spot survey gives a difficulty to look over how old water supply system is. Accordingly, this study collects and analyses five data as the laying environment, visual analysis, analysis of soil contents, analysis of pipe material, and questionary survey data in water pipe of A city. The deterioration factor estimates 14 factors with excavation and experimental analysis and 9 factors without excavation and experimental analysis. Also, the weighting factors are estimated by using the multiple linear regressions and the linear programming. The estimated deterioration factor and weighting results are compared the analysis result of visual, pipe material, and soil contents with the Probabilistic Neural Network Model. Consequently, the model results of estimated 9 factors in this study and 14 factors show the 1-2% difference. The result show that the proposed model could be used to decide the deterioration condition of pipe line with real excavation and experimental analysis.