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contributor authorThong M. Pham
contributor authorMuhammad N. S. Hadi
date accessioned2017-05-08T22:08:46Z
date available2017-05-08T22:08:46Z
date copyrightDecember 2014
date issued2014
identifier other33423449.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/72276
description abstractThis study proposes the use of artificial neural networks (ANNs) to calculate the compressive strength and strain of fiber reinforced polymer (FRP)–confined square/rectangular columns. Modeling results have shown that the two proposed ANN models fit the testing data very well. Specifically, the average absolute errors of the two proposed models are less than 5%. The ANNs were trained, validated, and tested on two databases. The first database contains the experimental compressive strength results of 104 FRP confined rectangular concrete columns. The second database consists of the experimental compressive strain of 69 FRP confined square concrete columns. Furthermore, this study proposes a new potential approach to generate a user-friendly equation from a trained ANN model. The proposed equations estimate the compressive strength/strain with small error. As such, the equations could be easily used in engineering design instead of the
publisherAmerican Society of Civil Engineers
titlePredicting Stress and Strain of FRP-Confined Square/Rectangular Columns Using Artificial Neural Networks
typeJournal Paper
journal volume18
journal issue6
journal titleJournal of Composites for Construction
identifier doi10.1061/(ASCE)CC.1943-5614.0000477
treeJournal of Composites for Construction:;2014:;Volume ( 018 ):;issue: 006
contenttypeFulltext


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