Finite element modeling of shear deficient RC beams strengthened with NSM CFRP rods under cyclic loading


Hawileh R., Abdalla J., Naser M., Tanarslan M.

Modeling of FRP Strengthening Techniques in Concrete Infrastructure at the ACI Fall 2011 Convention, Toronto, Kanada, 21 - 25 Ekim 2011, ss.69-85 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Basıldığı Şehir: Toronto
  • Basıldığı Ülke: Kanada
  • Sayfa Sayıları: ss.69-85
  • Anahtar Kelimeler: Computational modeling, Cyclic loading, Fiber-reinforced polymers (FRP), Near-Surface Mounted (NSM), Reinforced concrete beams, Shear failure, Strengthening
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

This paper presents Finite Element (FE) model to predict and analyze the cyclic loading response of reinforced concrete (RC) beams strengthened in shear with Carbon Fiber Reinforced-Polymer (CFRP) and Near-Surface Mounted (NSM) reinforcement. Four FE models were developed based on experimental tests conducted in a previous study. The first specimen was unstrengthened to serve as a control beam while the other two beams were strengthened with NSM CFRP bars with different spacing arrangements. The last beam specimen was strengthened with larger diameter CFRP bars. The developed FE models employed different nonlinear constitutive material modeling laws and techniques such as concrete cracking, steel yielding, bondslip between CFRP bars and epoxy resin, and debonding between the epoxy resin and concrete surfaces. The predicted and measured load-deflection response envelop curves along with the associated hysteresis loops for each specimen were used as platforms to validate the accuracy of the developed models. The results indicate that there is a good match between the predicted results and measured data. It is concluded that the developed FE model is a suitable tool to predict the behavior of such strengthening systems when subjected to cyclic loading and could be used in lieu of expensive experimental testing especially in design-oriented parametric studies.