NEURAL NETWORK PROGNOSTIC MODEL FOR RC BEAMS STRENGTHENED WITH CFRP STRIPS - Lazarevska, Marijana; Gavrilovska, Ana-Trombeva; Knežević, Miloš; Samardžioska, Todorka; Cvetkovska, Meri (Journal of Applied Engineering Science, 2012)
Improper execution of bonding of FRP plates to the RC beam can result into appearance of zones where the bond is substantially weaker, and air pockets are present. This paper presents an attempt to model the weak bond zone and its influence on the global response of the externally CFRP strengthened RC beam. A numerical displacement-based fiber model was used for the prediction of the response of RC beams externally strengthened with CFRP. Also, using the concepts of artificial neural networks and the results of the performed numerical analyses, another prediction model has been made. Both models generated excellent results and some of them will be presented further below in this paper. Key words CFRP, neural network, RC beam, strengthening, discontinuous bond.
Keywords: prognostication; Models; discontinuous bond; strengthening; RC beam; neural network; CFRP