Evaluation of the dynamic characteristics of a super tall building using data from ambient vibration and shake table tests by a Bayesian approach

Evaluation of the dynamic characteristics of a super tall building using data from ambient... The Shanghai Tower is a newly built 127‐story and 632 m high super tall building. As of April 2017, it was ranked as the second tallest building in the world. Its main structural system is a mega‐frame‐tube‐outrigger system with six outrigger trusses along the height. Due to its unique structural configuration, a series of field and laboratory model tests have been conducted to better understand its dynamic characteristics. Before its construction, a scaled model of the tower was tested on a shake table, and the results were used to refine the design of the tower. At the completion of the construction, full‐scale ambient vibration tests were performed. A Bayesian method was used to perform operational modal analysis from the shake table and full‐scale ambient vibration tests. The most probable value of the modal parameters and the associated posterior uncertainties were calculated using this method. The first eight modes were identified, including three translational modes in each principal direction and two torsional modes. Using these results, the dynamic characteristics and associated uncertainties obtained from the two tests were investigated and compared in this paper. Due to the scaling of the model, there are some discrepancies between the natural frequencies obtained from two different tests, but the identified mode shapes matched very well. Although the structure was designed in a very innovative manner, its dynamic characteristics are similar to regular tall buildings. The results from this investigation provide valuable information for an ongoing condition assessment of this super tall building. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Structural Control and Health Monitoring Wiley

Evaluation of the dynamic characteristics of a super tall building using data from ambient vibration and shake table tests by a Bayesian approach

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Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
Copyright © 2018 John Wiley & Sons, Ltd.
ISSN
1545-2255
eISSN
1545-2263
D.O.I.
10.1002/stc.2121
Publisher site
See Article on Publisher Site

Abstract

The Shanghai Tower is a newly built 127‐story and 632 m high super tall building. As of April 2017, it was ranked as the second tallest building in the world. Its main structural system is a mega‐frame‐tube‐outrigger system with six outrigger trusses along the height. Due to its unique structural configuration, a series of field and laboratory model tests have been conducted to better understand its dynamic characteristics. Before its construction, a scaled model of the tower was tested on a shake table, and the results were used to refine the design of the tower. At the completion of the construction, full‐scale ambient vibration tests were performed. A Bayesian method was used to perform operational modal analysis from the shake table and full‐scale ambient vibration tests. The most probable value of the modal parameters and the associated posterior uncertainties were calculated using this method. The first eight modes were identified, including three translational modes in each principal direction and two torsional modes. Using these results, the dynamic characteristics and associated uncertainties obtained from the two tests were investigated and compared in this paper. Due to the scaling of the model, there are some discrepancies between the natural frequencies obtained from two different tests, but the identified mode shapes matched very well. Although the structure was designed in a very innovative manner, its dynamic characteristics are similar to regular tall buildings. The results from this investigation provide valuable information for an ongoing condition assessment of this super tall building.

Journal

Structural Control and Health MonitoringWiley

Published: Jan 1, 2018

Keywords: ; ; ; ; ;

References

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