• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.4
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• pp.243-248
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• 2022

Weight optimization was performed for a rotorcraft shaft system using one-dimensional Euler-Bernoulli beam elements. Torsion, shaft support stiffness such as bearings, flange mass are all considered. To guarantee structural dynamic stability, eigenvalue analysis was performed to avoid critical speed and tooth mesh excitation form the gearbox. The weight optimization was performed by adjusting the thickness and radius while the length of the shaft was fixed, and the optimization process was divided into two stages. In the first, the weight is optimized with the torsional strength constraint. In the second, the difference between the primary mode of shaft and the critical speed is maximized so that the primary mode of the shaft can avoid the critical speed while the constraint on the torsional strength of the shaft is satisfied according to the standard for shaft system stability (AMC P 706-201, 1974). The proposed method was verified by comparing the results of the optimal design using the given one-dimensional beam elements with the stress results of the 3D finite element and the actual manufactured shaft.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.421-430
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• 2004

Clinically, it is almost impossible for a physician to distinguish subtle changes of frequency spectrum by using a stethoscope alone especially in the early stage of thrombus formation. Considering that reliability of mechanical valve is paramount because the failure might end up with patient death, early detection of valve thrombus using noninvasive technique is important. Thus the study was designed to provide a tool for early noninvasive detection of valve thrombus by observing shift of frequency spectrum of acoustic signals with computer aid diagnosis system. A thrombus model was constructed on commercialized mechanical valves using polyurethane or silicon. Polyurethane coating was made on the valve surface, and silicon coating on the sewing ring of the valve. To simulate pannus formation, which is fibrous tissue overgrowth obstructing the valve orifice, the degree of silicone coating on the sewing ring varied from 20％, 40％, 60％ of orifice obstruction. In experiment system, acoustic signals from the valve were measured using microphone and amplifier. The microphone was attached to a coupler to remove environmental noise. Acoustic signals were sampled by an AID converter, frequency spectrum was obtained by the algorithm of spectral analysis. To quantitatively distinguish the frequency peak of the normal valve from that of the thrombosed valves, analysis using a neural network was employed. A return map was applied to evaluate continuous monitoring of valve motion cycle. The in-vivo data also obtained from animals with mechanical valves in circulatory devices as well as patients with mechanical valve replacement for 1 year or longer before. Each spectrum wave showed a primary and secondary peak. The secondary peak showed changes according to the thrombus model. In the mock as well as the animal study, both spectral analysis and 3-layer neural network could differentiate the normal valves from thrombosed valves. In the human study, one of 10 patients showed shift of frequency spectrum, however the presence of valve thrombus was yet to be determined. Conclusively, acoustic signal measurement can be of suggestive as a noninvasive diagnostic tool in early detection of mechanical valve thrombosis.