Istrazivanja i projektovanja za privreduJournal of Applied Engineering Science

NEURAL NETWORK PROGNOSTIC MODEL FOR RC BEAMS STRENGTHENED WITH CFRP STRIPS


DOI: 10.5937/jaes10-1661
This is an open access article distributed under the CC BY-NC-ND 4.0 terms and conditions. 
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Volume 10 article 217 pages: 27 - 30

Marijana Lazarevska 
University of Skopje, Faculty of Civil Engineering, Skopje, Macedonia

Ana Trombeva-Gavriloska 
University of Skopje, Faculty of Architecture, Skopje Macedonia

Milos Knezevic 
University of Podgorica, Faculty of Civil Engineering, Podgorica, Montenegro

Todorka Samardzioska 
University of Skopje, Faculty of Civil Engineering, Skopje, Macedonia

Meri Cvetkovska 
University of Skopje, Faculty of Civil Engineering, Skopje, Macedonia

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 fibber 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.

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