Structural Engineering and Mechanics

  • 제56권4호
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  • Pages.625-648
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  • 2015
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  • 1225-4568(pISSN)
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  • 1598-6217(eISSN)
테크노프레스 (Techno-Press)
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DOI QR코드

DOI QR Code

Wind load estimation of super-tall buildings based on response data

  • Zhi, Lun-hai (School of Civil Engineering and Architecture, Wuhan University of Technology) ;
  • Chen, Bo (Key Laboratory of Roadway Bridge and Structural Engineering, Wuhan University of Technology) ;
  • Fang, Ming-xin (School of Civil Engineering and Architecture, Wuhan University of Technology)
  • 투고 : 2015.02.07
  • 심사 : 2015.11.06
  • 발행 : 2015.11.25
⟨ 이전 논문 다음 논문 ⟩

초록

Modern super-tall buildings are more sensitive to strong winds. The evaluation of wind loads for the design of these buildings is of primary importance. A direct monitoring of wind forces acting on super-tall structures is quite difficult to be realized. Indirect measurements interpreted by inverse techniques are therefore favourable since dynamic response measurements are easier to be carried out. To this end, a Kalman filtering based inverse approach is developed in this study so as to estimate the wind loads on super-tall buildings based on limited structural responses. The optimum solution of Kalman filter gain by solving the Riccati equation is used to update the identification accuracy of external loads. The feasibility of the developed estimation method is investigated through the wind tunnel test of a typical super-tall building by using a Synchronous Multi-Pressure Scanning System. The effects of crucial factors such as the type of wind-induced response, the covariance matrix of noise, errors of structural modal parameters and levels of noise involved in the measurements on the wind load estimations are examined through detailed parametric study. The effects of the number of vibration modes on the identification quality are studied and discussed in detail. The made observations indicate that the proposed inverse approach is an effective tool for predicting the wind loads on super-tall buildings.

키워드

과제정보

연구 과제 주관 기관 : National Natural Science Foundation of China, Fok Ying Tong Education Foundation

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