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Appl. Sci. 2017, 7(8), 751; doi:10.3390/app7080751

Prediction of Ultimate Strain and Strength of FRP-Confined Concrete Cylinders Using Soft Computing Methods

1
Department of Civil Engineering, Birjand University of Technology, Birjand 97175-569, Iran
2
School of Natural Sciences and Engineering, Ilia State University, Tbilisi 0162, Georgia
3
Department of Civil and Resource Engineering, Dalhousie University, 1360 Barrington Street, Halifax, NS B3H 4R2, Canada
4
Research Institute of Structural Engineering & System, DongYang Structural Engineers Co., Ltd., Seoul 05836, Korea
5
Department of Civil and Environmental Engineering, Incheon National University, Incheon 22012, Korea
6
Incheon Disaster Prevention Research Center, Incheon National University, Incheon 22012, Korea
*
Author to whom correspondence should be addressed.
Received: 13 June 2017 / Revised: 14 July 2017 / Accepted: 18 July 2017 / Published: 25 July 2017
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Abstract

This paper investigates the effectiveness of four different soft computing methods, namely radial basis neural network (RBNN), adaptive neuro fuzzy inference system (ANFIS) with subtractive clustering (ANFIS-SC), ANFIS with fuzzy c-means clustering (ANFIS-FCM) and M5 model tree (M5Tree), for predicting the ultimate strength and strain of concrete cylinders confined with fiber-reinforced polymer (FRP) sheets. The models were compared according to the root mean square error (RMSE), mean absolute relative error (MARE) and determination coefficient (R2) criteria. Similar accuracy was obtained by RBNN and ANFIS-FCM, and they provided better estimates in modeling ultimate strength of confined concrete. The ANFIS-SC, however, performed slightly better than the RBNN and ANFIS-FCM in estimating ultimate strain of confined concrete, and M5Tree provided the worst strength and strain estimates. Finally, the effects of strain ratio and the confinement stiffness ratio on strength and strain were investigated, and the confinement stiffness ratio was shown to be more effective. View Full-Text
Keywords: fiber reinforced polymer; concrete; column; confinement; stress; strain; model fiber reinforced polymer; concrete; column; confinement; stress; strain; model
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Mansouri, I.; Kisi, O.; Sadeghian, P.; Lee, C.-H.; Hu, J.W. Prediction of Ultimate Strain and Strength of FRP-Confined Concrete Cylinders Using Soft Computing Methods. Appl. Sci. 2017, 7, 751.

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