Mobile QR Code QR CODE : Journal of the Korean Society of Civil Engineers
Title Characteristics of Aerodynamic Damping on Helical-Shaped Super Tall Building
Authors 김원술(Kim, Wonsul) ; 이진학(Yi, Jin-Hak) ; 타무라 유키오(Tamura, Yukio)
DOI https://doi.org/10.12652/Ksce.2017.37.1.0009
Page pp.9-17
ISSN 10156348
Keywords 공력감쇠;구조감쇠;초고층건물;공력진동실험;풍동실험 Aerodynamic damping;Structural damping;Random decrement technique;Super tall building;Aeroelastic model test;Wind tunnel test
Abstract Characteristics of aerodynamic damping ratios of a helical $180^{\circ}$ model which shows better aerodynamic behavior in both along-wind and across-wind responses on a super tall building was investigated by an aeroelastic model test. The aerodynamic damping ratio was evaluated from the wind-induced responses of the model by using Random Decrement (RD) technique. Further, various triggering levels in evaluation of aerodynamic damping ratios using RD technique were also examined. As a result, it was found that when at least 2000 segments were used for evaluating aerodynamic damping ratio for ensemble averaging, the aerodynamic damping ratio can be obtained more consistently with lower irregular fluctuations. This is good agreement with those of previous studies. Another notable observation was that for square and helical $180^{\circ}$ models, the aerodynamic damping ratios in along-wind direction showed similar linear trends with reduced wind speeds regarding of building shapes. On the other hand, for the helical $180^{\circ}$ model, the aerodynamic damping ratio in across-wind direction showed quite different trends with those of the square model. In addition, the aerodynamic damping ratios of the helical $180^{\circ}$ model showed very similar trends with respect to the change of wind direction, and showed gradually increasing trends having small fluctuations with reduced wind speeds. Another observation was that in definition of triggering levels in RD technique on aerodynamic damping ratios, it may be possible to adopt the triggering levels of "standard deviation" or "${\sqrt{2}}$ times of the standard deviation" of the response time history if RD functions have a large number of triggering points. Further, these triggering levels may result in similar values and distributions with reduced wind speeds and either may be acceptable.