Seismic assessment of reinforced concrete (RC) buildings heavily relies on the deformation capacity predictions of members. Similarly, the prediction of the deformation capacity of retrofitted RC columns has the utmost importance for seismic retrofit design. In this paper, a new unified drift model is proposed in order to estimate the rotation capacity of RC columns retrofitted with concrete jacketing, steel jacketing and fibre-reinforced polymer (FRP) wrapping. In order to generate the model, an extensive database was compiled consisting of 269 columns composed of 39 concrete-jacketed, 91 steel-jacketed and 139 FRP-wrapped RC columns failing in flexure mode. In the proposed drift model, the key model parameters are the confinement stress ratio, the axial load ratio and the lap splice length. The accuracy and scatter of the estimations with regard to the previous models were studied. For all of the column retrofitting options, the proposed unified model was observed to have rotation predictions better than the previous models in terms of the mean of the predicted to experimental rotation capacity ratios and with a reduced standard deviation.
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March 2022
Research Article|
May 15 2020
A drift capacity prediction model for retrofitted reinforced concrete columns
Okan Özcan;
Okan Özcan
Associate Professor, Department of Civil Engineering, Akdeniz University, Antalya, Turkey (corresponding author: ookan@akdeniz.edu.tr)
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Barış Binici
Barış Binici
Professor, Department of Civil Engineering, Middle East Technical University, Ankara, Turkey
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Publisher: Emerald Publishing
Received:
November 21 2019
Revision Received:
March 06 2020
Accepted:
April 06 2020
Online ISSN: 1751-763X
Print ISSN: 0024-9831
ICE Publishing: All rights reserved
2020
Magazine of Concrete Research (2022) 74 (5): 236–250.
Article history
Received:
November 21 2019
Revision Received:
March 06 2020
Accepted:
April 06 2020
Citation
Özcan O, Binici B (2022), "A drift capacity prediction model for retrofitted reinforced concrete columns". Magazine of Concrete Research, Vol. 74 No. 5 pp. 236–250, doi: https://doi.org/10.1680/jmacr.19.00553
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