PREDICTING THE ULTIMATE BOND STRENGTH OF CFRP BONDED TO CONCRETE USING ARTIFICIAL NEURAL NETWORKS

Zhang Bin; Fan Jin

doi:10.13204/j.gyjz200703017

Volume 37 Issue 3

Dec. 2014

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Zhang Shi-qian, Chen Zong-ping, Xu Jin-jun, Wang Ni. RESEARCH ON THE BEARING CAPACITY AND REINFORCEMENT METHOD OF IN-SERVICE DAMAGED BRICK CHIMNEY[J]. INDUSTRIAL CONSTRUCTION, 2012, 42(10): 153-158,100. doi: 10.13204/j.gyjz201210032

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Zhang Bin, Fan Jin. PREDICTING THE ULTIMATE BOND STRENGTH OF CFRP BONDED TO CONCRETE USING ARTIFICIAL NEURAL NETWORKS[J]. INDUSTRIAL CONSTRUCTION, 2007, 37(3): 66-71,41. doi: 10.13204/j.gyjz200703017

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PREDICTING THE ULTIMATE BOND STRENGTH OF CFRP BONDED TO CONCRETE USING ARTIFICIAL NEURAL NETWORKS

doi: 10.13204/j.gyjz200703017

Zhang Bin,
Fan Jin

1.
Department of Civil Engineering,Nanjing University of Science and Technology Nanjing 210094

Received Date: 2006-04-04
Publish Date: 2007-03-20

Abstract

Abstract

The application of artificial neural networks (ANNs) to predict the ultimate bond strengths of CFRP bonded toconcrete is investigated. An ANN model is built, trained and tested using 118 sets of test data collected from the technicalliteratures. The data used in the ANN model are arranged in a format of 8 input parameters that cover the compressivestrength, tensile strength andwidth of cube concrete; the thickness, the width, the bond length and the elastic modulus ofthe CFRP plate. 15 sets of experimental data are usedfor predicting. The results predicted by the ANN model are comparedwith those obtained by 4 empirical equations. The results show that ANN is a feasible tool for predicting the ultimate bondstrengths of CFRP bonded to concrete.
- CFRP concrete,
- bond strength,
- artificial neural networks,
- pul-lout tests,

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References(2)

References

杨福磊,奚震勇,孙海. 上海某大厦托梁拔柱工程的设计[J].工业建筑,2005,(04).

李媛萍. 托梁拔柱法在老厂房改造中的应用[J].暨南大学学报(自然科学与医学版),2003,(03).

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