Research on Vibration Control of Landscape Tower-TMDI Based on Colliding Bodies Optimization
School of Civil Engineering and Architecture, Chongqing University of Science and Technology, Chongqing 401331, China
| Abstract: | Wind load will cause significant vibration of landscape towers, thus bringing strong discomfort to visitors. In order to control structural vibration and reduce this discomfort, in order to study the wind-induced vibration control ability of tuned mass inertial damper (TMDI) on landscape towers, the motion equation of tuned mass damper under wind load is deduced, and the accelerated response spectrum is derived by frequency domain analysis method. The TMDI parameters are optimized by using CBO optimization algorithm to minimize the acceleration of TMDI system of landscape tower, and discussing the ability of TMDI to control wind-induced vibration of structures. The structure is shown as follows: Acceleration response will vary with mass ratio, apparent mass ratio, damping ratio, and frequency ratio. In this paper, dimensionless acceleration is the ratio of acceleration amplitude of the platform equipped with TMDI to that of the platform without TMDI. Within the recommended interval, the control effect of acceleration amplitude is between 16.55% and 26.48%. The acceleration amplitude at the platform still meets the acceleration limit in the specification under the design wind speed, and the vibration reduction of the bent-torsion column - spiral beam landscape tower is realized. The results show that TMDI can effectively control the acceleration response at landscape tower platform. |
| Keywords: | Tuned-mass-damper-inerter; Wind-induced-vibration; Collision Bodies Optimization; Vibration Control Performance; Frequency Domain Analysis Method |
| DOI: | 10.57237/j.cear.2023.02.003 |
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Received: 28 April 2023
Accepted: 6 July 2023
Published Online: 24 July 2023
Funding
| 1. | Open Research Project of University-Enterprise Collaborative Innovation Center of Chongqing University of Science and Technology (Grant No: YKJCX2220622) |
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