• 한국신재생에너지학회:학술대회논문집
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• 2009.11a
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• pp.460-464
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• 2009

This study investigates the wake effect of an island to develop the offshore wind farm. The main wind direction can be determined from the data processing of the QuikSCAT satellite data around the Wi-do island at south-west sea of the Korean peninsula. Computational fluid dynamics is adopted to analyze the wake effect. From this study the velocity defects due to the wake are revealed. In particular about 5% velocity defect is observed at 80m hub height from the sea surface.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.4
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• pp.20-29
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• 2022

The operational modal analysis (OMA) technique, which extracts the modal parameters of a structural system using ambient vibrations, has been actively developed as a field of structural health monitoring of cable-supported bridges. In this paper, the short and long-term modal parameters of a cable-stayed bridge were evaluated using the acceleration data obtained from the two ambient vibration tests (AVTs) and three years of continuous measurements. A total of 27 vertical modes and 1 lateral mode in the range 0.1 ~ 2.5 Hz were extracted from the high-resolution AVTs which were conducted in the 6th and 19th years after its completion. Existing OMA methods such as Peak-Picking (PP), Eigensystem Realization Algorithm with Data Correlation (ERADC), Frequency Domain Decomposition (FDD) and Time Domain Decomposition (TDD) were applied for modal parameters extraction, and it was confirmed that there was no significant difference between the applied methods. From the correlation analysis between long-term natural frequencies and environmental factors, it was confirmed that temperature change is the dominant factor influencing natural frequency fluctuations. It was revealed that the decreased natural frequencies of the bridge were not due to changes in structural performance and integrity, but to the environmental effects caused by the temperature difference between the two AVTs. In addition, when the TDD technique is applied, the accuracy of extracted mode shapes is improved by adding a proposed algorithm that normalizes the sequence so that the autocorrelations at zero lag equal 1.