- All Journals
- Al-Qadisiyah University
- Basrah University
- Kirkuk University
- Mosul University
- The Iraqi Borad for Medical Specialization
- University of Anbar
- University of Technology
- Al Mustafa University
- Al-Zahraa University for Women
- Alnoor University
- Kunooz University
- Misan University
- Ninevah University
- Tikrit University
- University of Al-Hamdaniya
- University of Kerbala
Modeling of ultimate load for R.C. beams strengthened with Carbon FRP using artificial neural networks | ||
| Al-Rafidain Engineering Journal (AREJ) | ||
| Article 6, Volume 18, Issue 6, 2010, Pages 28-41 PDF (0 K) | ||
| DOI: 10.33899/rengj.2010.34813 | ||
| Authors | ||
| Dr. Salim T.Yousif; Majid A. AL- Jurmaa; Majid A. AL- Jurmaa | ||
| Abstract | ||
| Abstract The use of carbon fiber reinforced composite materials is an accepted technology that is being used in practice to strengthen existing reinforced concrete (R/C) elements. An artificial neural network (ANN) model was developed using past experimental data on flexural failure of R/C beams strengthened by carbon FRP. The input parameters cover the carbon sheet properties, beam geometrical properties and reinforcement properties; the corresponding output is the ultimate load capacity. The ANN prediction and the measured experimental values are compared with load prediction of ACI440.2R-02 formulas. A sensitivity study of parameters that affect ultimate load of R/C beams strengthened by carbon FRP is carried out. It is concluded that ANN can predict, to a good degree of accuracy, the ultimate load capacity of R/C beams strengthened by carbon FRP and it is a viable tool to carry out parametric study of flexural behavior of R/C beams strengthened by carbon FRP. Keywords: carbon FRP, Reinforced Concrete Beam, Ultimate Load, and Neural Network | ||
| Keywords | ||
| KEYWORDS; Reinforced Concrete Beam; Ultimate Load; and Neural Network | ||
|
Statistics Article View: 492 PDF Download: 478 |
||