A Computational Approach to Predict the Bond Strength of Thin Steel Rebars in Concrete by Means of Support Vector Machine

Resumo

The bond strength between steel bars and concrete is one of the essential aspects of reinforced concrete
structures and is generally affected by several factors. As a phenomenon influenced by many variables, it is
challenging to establish how the steel-concrete adhesion can be described in the standards used for reinforced
concrete design. This study used an experimental data set of 89 pull-out specimens to develop a support vector
machine (SVM). The data used in the modeling was arranged as four input parameters: bar surface, bar diameter
(φ), concrete compressive strength (fc) and the anchorage length (Ld). Several scientific studies on this property
have been performed since the 1940s, among many other investigations in this field. Generally, these studies refer
to bars with diameters greater than 12.0 mm. However, few studies have evaluated the performance of reinforcing
bars with diameters smaller than 10.0 mm, which includes 5.0-, 6.3-, 8.0- and 9.5-mm diameters, usually used in
reinforced concrete elements. This work uses SVM to analyze and build a prediction model for the steel-concrete
bond and its potential to deal with experimental data. The root mean squared error (RMSE) found for the maximum
applied load in the pull-out test was 1.305 kN and the R-squared was 0.95. Therefore, this study can conclude that
the current model can satisfactorily predict the bond strength of thin bars.