Estimation of Shear Strength of RC Beams FRP-Strengthened by Using Soft Computing Method and Codes

GUNNURYAVUZ, GUNNURYAVUZ and MUSA HAKAN, ARSLAN (2014) Estimation of Shear Strength of RC Beams FRP-Strengthened by Using Soft Computing Method and Codes. In: International Conference on Advances in Civil, Structural and Construction Engineering - CSCE 2014, 07- 08 June,2014, International Conference on Advances in Civil, Structural and Construction Engineering - CSCE 2014.

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Abstract

In this study, the efficiency of artificial neural networks (ANN) in predicting the shear strength of reinforced concrete (RC) beams strengthened by means of externally bonded fiber reinforced polymer FRP is explored. Experimental data of rectangular RC beams from an existing database in the literature were used to develop ANN model. Different eight input parameters affecting the shear strength were selected for creating three layered back-propagation method of ANN structure. The initial performance evaluation back propagation was evaluated and discussed. In addition to these, the paper presents a short review of the well-known building codes provisions for the design of RC beams strengthened by means of externally bonded FRP under shear effect. The accuracy of the codes in predicting the shear strength of RC beams FRP strengthened was also examined with comparable way by using same test data. The study concludes that ANN model predicts the shear strength of RC beams FRP strengthened better than existing building code approaches on shear strength.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: beam, strengthening, FRP, shear strength, artificial neural network
Depositing User: Mr. John Steve
Date Deposited: 21 May 2019 09:07
Last Modified: 21 May 2019 09:07
URI: http://publications.theired.org/id/eprint/2545

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