• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.6
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• pp.41-48
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• 2002

This study is on the structural control experiment for a small scale three-story building structure employing on active mass damper subjected to earthquake loading. $\mu$-synthesis controllers, which belong to robust control strategies, were designed and their performance were experimentally verified. Frequency-dependent weighting functions corresponding to disturbance input and controlled output were defined and combined to produce optimal $\mu$-synthesis controllers. The experiment result shows 60-70% reduction in RMS responses under the band-limited white noise excitation and 30-45% reduction in peak responses under the scaled earthquake excitations. Good agreement was obtained between the simulations based on the identified mathematical model and experimental results. And the simulations for the system with uncertainties show that the designed controllers are robust within a specified range of uncertainties.

• Smart Structures and Systems
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• v.24 no.3
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• pp.333-343
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• 2019

The possibility of adopting vibration-powered wireless nodes has been largely investigated in the last years. Among the available technologies based on the piezoelectric effect, the most common ones consist of a vibrating beam covered by electroactive layers. Another energy harvesting strategy is based on the use of piezoelectric strips attached to a hosting structure subjected to dynamic loads. The hosting structure, for example, can be the system to be equipped with wireless nodes. Such strategy has received few attentions so far and no analytical studies have been presented yet. Hence, the original contribution of the present paper is concerned with the development of analytical solutions for the electrodynamic analysis and design of piezoelectric polymeric strips attached to relatively large linear elastic structural systems subjected to random vibrations at the base. Specifically, it is assumed that the dynamics of the hosting structure is dominated by the fundamental vibration mode only, and thus it is reduced to a linear elastic single-degree-of-freedom system. On the other hand, the random excitation at the base of the hosting structure is simulated by filtering a white Gaussian noise through a linear second-order filter. The electromechanical force exerted by the polymeric strip is negligible compared with other forces generated by the large hosting structure to which it is attached. By assuming a simplified electrical interface, useful new exact analytical expressions are derived to assess the generated electric power and the integrity of the harvester as well as to facilitate its optimum design.

• Journal of the Korean Society of Radiology
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• v.14 no.2
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• pp.157-168
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• 2020

Advancements in segmentation methodology has made automatic segmentation of brain structures using structural images accurate and consistent. One method of automatic segmentation, which involves registering atlas information from template space to subject space, requires a high quality atlas with accurate boundaries for consistent segmentation. The Allen Mouse Brain Atlas, which has been widely accepted as a high quality reference of the mouse brain, has been used in various segmentations and can provide accurate coordinates and boundaries of mouse brain structures for tractography. Through probabilistic tractography, diffusion tensor images can be used to map comprehensive neuronal network of white matter pathways of the brain. Comparisons between neural networks of mouse and human brains showed that various clinical tests on mouse models were able to simulate disease pathology of human brains, increasing the importance of clinical mouse brain studies. However, differences between brain size of human and mouse brain has made it difficult to achieve the necessary image quality for analysis and the conditions for sufficient image quality such as a long scan time makes using live samples unrealistic. In order to secure a mouse brain image with a sufficient scan time, an Ex-vivo experiment of a mouse brain was conducted for this study. Using FSL, a tool for analyzing tensor images, we proposed a semi-automated segmentation and tractography analysis pipeline of the mouse brain and applied it to various mouse models. Also, in order to determine the useful signal-to-noise ratio of the diffusion tensor image acquired for the tractography analysis, images with various excitation numbers were compared.