Modeling of mechanical properties and bond relationship using data mining process

Authors:
Kemal TuşAt YüCel;Cengiz ÖZel
Affiliations:
Civil Engineering Department, Faculty of Engineering and Architectural, Suleyman Demirel University, 32260 Isparta, Turkey;Department of Construction Education, Faculty of Technical Education, Suleyman Demirel University, 32260 Isparta, Turkey
Venue:
Advances in Engineering Software
Year:
2012

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Abstract

Reinforced concrete is a widely used construction material. Its properties depend on the bond between the reinforcing bar and concrete as much as the compressive strength or properties of the reinforcing bar because of component of construction expose to both flexural and bond together compressive loads. In this paper, the bond properties of concretes with different mix designs were investigated according to the results of compressive, flexural, bond, and flexural-bond tests. The data mining (DM) process was used to determine relationships among the test results and DM algorithms. Seventeen modeling techniques within WEKA were applied to the experimental data for the prediction of bond properties. The results show that the implemented models were good at predicting the bond properties. The best results were obtained from the RepTree algorithm for bond strength, the Multilayer Perceptron algorithm for flexural-bond strength, the MedSq algorithm for bond slippage, and the Pace Regression for flexural-bond deformation. Bond and flexural-bond can be easily predicted using the compressive strength, flexural strength and tensile stress of the rebar. Although a relationship is also existent between these and bond slippage and flexural-bond deformation, these relationships are weaker than the others. These results suggested that the DM algorithms can be used as an alternative approach to predict the bond strength using the results of compressive, flexural, bond, and flexural-bond tests as input parameters. The predictions of the bond slippage and flexural-bond deformation models poorly agreed with the experimental results. It can be obtained more successful results for these variables, when DM models with different inputs like the rebar-concrete interface stress together the measured parameters are used.