Compressive Strength Prediction Using the ANN Method for FRP Confined Rectangular Concrete Columns

Fiber Reinforced Polymer (FRP) was extensively employed as external confinement to strengthen the RC structures. Substantial studies were carried out in order to assess a more exact formula for measuring the strength enhancement of such strengthens concrete columns. A database from several experimental tests was gathered. A comparison between the experimental values and existing formulae called an urgent need for a more exact formula. Therefore, the aim of this paper is to develop an exact formula based artificial neural networks (ANNs), and to present the strength enhancement. The ANN-based method was simulated in consonance with the collected database and an exact formula generated. The proposed formula was compared to current formulae employing the gathered database. The results revealed that the new formula based ANN gives the best accuracy than others. A sensitivity analysis based on Garson’s algorithm was generated for indicating the value of each applied variable.

Keywords:

ANN , Compressive Strength , FRP confined rectangular concrete columns , Garson’s algorithm