Papers by Author: Yeon Sun Choi

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Authors: In Pil Kang, Gyeong Rak Choi, Joo Yung Jung, Yong Hoon Chang, Yeon Sun Choi, Mark J. Schulz
Abstract: This paper experimentally investigates the power generation property of carbon nanotubes in an aqueous environment. Carbon nanotube based films are investigated in this paper as a new method for power generation based on ionic conductivity of the fluid. It is demonstrated that a carbon nanotube film that is bonded onto a structure vibrating with an electrolyte on the surface produces an alternating current without a net fluid flow. The power produced is smaller than for a piezoelectric material of the same size, but the CNT power generator is lightweight and has no moving parts, and does not require the structure to be immersed in an electrolyte. There are various possible applications for nanotube power generators.
Authors: Bum Won Bae, In Pil Kang, Yeon Sun Choi
Abstract: A fault diagnosis method based on wavelet and adaptive interference canceling is presented for the identification of a damaged gear tooth. A damaged tooth of a certain gear chain generates impulsive signals that could be informative to fault detections. Many publications are available not only for the impulsive vibration signal analysis but the application of signal processing techniques to the impulsive signal detections. However, most of the studies about the gear fault detection using the impulsive vibration signals of a driving gear chain are limited to the verification of damage existence on a gear pair. Requirements for more advanced method locating damaged tooth in a driving gear chain should be a motivation of further studies. In this work an adaptive interference canceling combined with wavelet method is used for a successful identification of the damaged tooth location. An application of the wavelet technique provides a superior resolution for the damage detection to the traditional frequency spectrum based methods. An analysis and experiment with three pair gear chain show the feasibility of this study yielding a precise location of the damaged gear tooth.
Authors: Yeon Sun Choi, Won Ho Yang, Young Jig Kim, Chang Sung Seok
Authors: Dong Ho Oh, Nam Hoon Lee, Ja Choon Koo, Hyeon Ki Choi, Yeon Sun Choi
Abstract: As the fluid dynamic bearing spindles are to be actively adopted to various small form factor mobile applications, mechanical specifications for the motors have been aggressively changed to pursue the fierce information technology sector market trend. One of the major technological challenges for the spindles to be successfully employed in the applications is the reduction of power consumption since the most of the mobile applications operate with a limited power source at relatively lower voltage. Recognizing implication of the power consumption that of course affects stiffness of the spindle, few of options for mechanical designers are available but either lowering rotational speed or adopting thinner lubricant. In the present work, a novel design solution for alleviating side effect of the lower stiffness spindle is introduced and verified.
Authors: Ja Choon Koo, Sean W. Kang, Y.S. Han, Yeon Sun Choi
Abstract: This article presents a modeling method for air flow analysis of a hard disk drive. Air flow excitation causes disk vibration that aggravates TMR budget of the design of modern high performance hard drives. And it is the most expensive budget consumer so that controlling of the flutter becomes the primary design issue of the data storage industry. In the presented work, air flow excitation forces are characterized by LES modeling and the results are verified with experiments. A squeeze-film-type disk damper is employed in the experiments and it is applied for a hardware design improvement for disk flutter reduction. LES and RANS are compared and alternately used in a calculation in order to minimize computational efforts.
Authors: In Pil Kang, Jong Won Lee, Gyeong Rak Choi, Joo Yung Jung, Sung Ho Hwang, Yeon Sun Choi, Kwang Joon Yoon, Mark J. Schulz
Abstract: This paper introduces a new sensor design based on a carbon nanotube structural neuron for structural health monitoring applications. The carbon nanotube neuron is a thin and narrow polymer film sensor that is bonded or deposited onto a structure. The electrochemical impedance (resistance and capacitance) of the neuron changes due to deterioration of the structure where the neuron is located. A network of the long carbon nanotube neurons can form a structural neural system to provide large area coverage and an assurance of the operational health of a structure without the need for actuators and complex wave propagation analyses that are used with other SHM methods. The neural system can also reduce the cost of health monitoring by using biomimetic signal processing to minimize the number of channels of data acquisition needed to detect damage. The carbon nanotube neuron is lightweight and easily applied to the structural surface, and there is no stress concentration, no piezoelectrics, no amplifier, and no storage of high frequency waveforms. The carbon nanotube neuron is expected to find applications in detecting damage and corrosion in large complex structures including composite and metallic aircraft and rotorcraft, bridges, and almost any type of structure with almost no penalty to the structure.
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