Vertical shortening prediction for super‐tall buildings considering enclosure effect and coupling effect. (21st December 2019)

• Record Type: Journal Article
• Authors: Zhao, Xin; Wang, Lilin
• Is Part Of: Structural design of tall and special buildings. Volume 29:Number 2(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-12-21
• Subjects: a combined method -- an iteration method -- coupling effect -- enclosure effect -- super‐tall building -- vertical shortening; Tall buildings -- Design and construction -- Periodicals; Structural design -- Periodicals; 690.1
• DOI: 10.1002/tal.1685
• Languages: English
• ISSNs: 1541-7794

Abstract

Summary: In this paper, the time‐dependent vertical shortening behavior of the super‐tall building is studied considering the enclosure effect and the coupling effect. A combined method to predict the overall strain of the mega section is firstly proposed by combining the B3 model and the fiber modeling approach to consider the enclosure effect of mega steel and validated by a series of in‐house experiments. An iteration method is then proposed based on the construction sequence method to consider the coupling effect of stress and strain in the vertical shortening prediction and illustrated by a super‐tall building project. Finally, the vertical shortening predictions of the super‐tall building project are compared with the field monitoring records. The results show that the strain predictions by the combined method show good agreement with experiments. Without considering the enclosure effect, the overall strain of mega section is overestimated. The coupling effect affects more on the vertical shortening of the mega column than on that of the shear wall and more on the elastic shortening than on the inelastic shortening. Without considering the coupling effect, the elastic shortening is significantly underestimated in the mega column but slightly overestimated in the shear wall. The predictions of vertical shortening in the shear wall show reasonable agreement with the measurements, whereas those in the mega column show large disagreement with the measurements, which enlightens the necessity to improve the prediction method further.