Analysis of Bond Strength of FRP Rebar on Concrete
Versandkostenfrei!
Versandfertig in 6-10 Tagen
39,99 €
inkl. MwSt.
PAYBACK Punkte
20 °P sammeln!
In this book, a method to predict the bond strength of FRP rebar in concrete by using the Artificial Neural Network (ANN) was developed based on the inadequacy of appropriate methods dealing with bond strength. ANN was implemented to understand the complex nonlinear relationship between the inputs (bar diameter, embedment length, and strength of concrete) and the output (bond strength). The training and validation of the bond strength show the good linear relationship between ANN predicted and experimental values. It revealed the fact that surface geometry of FRP rebar highly affects the bond ...
In this book, a method to predict the bond strength of FRP rebar in concrete by using the Artificial Neural Network (ANN) was developed based on the inadequacy of appropriate methods dealing with bond strength. ANN was implemented to understand the complex nonlinear relationship between the inputs (bar diameter, embedment length, and strength of concrete) and the output (bond strength). The training and validation of the bond strength show the good linear relationship between ANN predicted and experimental values. It revealed the fact that surface geometry of FRP rebar highly affects the bond strength. Another important part of the project was the finite element analysis of the bond strength. A 3D finite element model was developed to simulate the bond behaviour that exists between concrete and FRP using Abaqus software. The friction was used to simulate the bond phenomenon between surface of rebar and surface of concrete in pull-out test specimen model.
Andere Kunden interessierten sich für
