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Earthquakes and Structures
  Volume 8, Number 5, May 2015, pages 1171-1190

Compressive strength prediction by ANN formulation approach for CFRP confined concrete cylinders
Mojtaba Fathi, Mostafa Jalal and Soghra Rostami

    Enhancement of strength and ductility is the main reason for the extensive use of FRP jackets to provide external confinement to reinforced concrete columns especially in seismic areas. Therefore, numerous researches have been carried out in order to provide a better description of the behavior of FRP-confined concrete for practical design purposes. This study presents a new approach to obtain strength enhancement of CFRP (carbon fiber reinforced polymer) confined concrete cylinders by applying artificial neural networks (ANNs). The proposed ANN model is based on experimental results collected from literature. It represents the ultimate strength of concrete cylinders after CFRP confinement which is also given in explicit form in terms of geometrical and mechanical parameters. The accuracy of the proposed ANN model is quite satisfactory when compared to experimental results. Moreover, the results of the proposed ANN model are compared with five important theoretical models proposed by researchers so far and considered to be in good agreement.
Key Words
    ANN formulation; CFRP confinement; concrete cylinder; strength prediction
Mojtaba Fathi and Soghra Rostami: Department of Civil Engineering, Razi University, Kermanshah, Iran

Mostafa Jalal: Zachry Department of Civil Engineering, Texas A&M University, College Station, TX 77843–3136, USA

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