Title of article :
Compressive Strength Prediction Using the ANN Method for FRP Confined Rectangular Concrete Columns
Author/Authors :
Moghbeli, A Department of Civil Engineering - Vali-e-Asr University of Rafsanjan, Iran , Sharifi, Y Department of Civil Engineering - Vali-e-Asr University of Rafsanjan, Iran , Lotfi, F Faculty of Engineering - Institute of Higher Education Allameh Jafari Rafsanjan, Iran
Abstract :
Fiber Reinforced Polymer (FRP) was extensively employed as external confinement to strengthen the RC structures. Extensive studies were carried out to assess a more exact formula for measuring the strength enhancement of such strengthens concrete columns. A database from several experimental tests on was gathered. A comparison between the experimental values and existing formulae showed an urgent need for a more exact formula. This study investigated to develop an exact formula based artificial neural networks (ANNs), to present the strength enhancement. The ANN-based method was simulated based on the collected database and an exact formula generated. The proposed formula was compared to current formulae employing the gathered database. The results demonstrated 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 used variable.
Keywords :
Garson’s Algorithm , FRP Confined Rectangular Concrete Columns , Compressive Strength , ANN
Journal title :
Astroparticle Physics
