Technical Papers
Aug 1, 2018

Probabilistic Model for Long-Term Time-Dependent Compressive Strength of Concrete in Existing Buildings

Publication: Journal of Performance of Constructed Facilities
Volume 32, Issue 5

Abstract

In this paper, in order to develop a novel probabilistic model for the time-dependent compressive strength of concrete for existing reinforced concrete buildings, 1923 data sets were obtained by applying a rebound hammer in 33 buildings. In addition, 172 data sets were obtained using core drilling in 27 (out of 33) buildings with service-ages varying from 1 to 60 years and located in Shanghai, China. By analyzing the experimental data, it is found that the normal distribution appropriately describes the distribution of normalized concrete compressive strength. The conjugate prior distribution was used to update the mean value of the normalized compressive strength of concrete by rebound hammer. Then the time-dependent mean value of the normalized compressive strength by rebound hammer and core drilling was proposed. The results of the numerical models agree well with the measured data. The compressive strength conversion factors of the concrete tested by rebound hammer and core drilling methods are provided as well. The proposed probabilistic model for the time-dependent compressive strength of concrete and the conversion factors can be used to efficiently predict the compressive strength of concrete for existing reinforced concrete buildings.

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Acknowledgments

The authors would like to express their gratitude to the Natural Science Foundation of China for financially supporting this research (Grant Nos. 51538010 and 51678439).

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Go to Journal of Performance of Constructed Facilities
Journal of Performance of Constructed Facilities
Volume 32Issue 5October 2018

History

Received: Jan 1, 2018
Accepted: Apr 24, 2018
Published online: Aug 1, 2018
Published in print: Oct 1, 2018
Discussion open until: Jan 1, 2019

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Xiangling Gao, Ph.D. [email protected]
Associate Professor, Dept. of Structural Engineering, Tongji Univ., Shanghai 200092, China. Email: [email protected]
Jie Li, Ph.D., Aff.M.ASCE [email protected]
Professor, Dept. of Structural Engineering, Tongji Univ., Shanghai 200092, China. Email: [email protected]
Associate Professor, Dept. of Structural Engineering, Tongji Univ., Shanghai 200092, China (corresponding author). ORCID: https://orcid.org/0000-0002-0357-4515. Email: [email protected]

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