Journal
CONSTRUCTION AND BUILDING MATERIALS
Volume 20, Issue 9, Pages 801-811Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.conbuildmat.2005.01.047
Keywords
fiber reinforced concrete beams; neural networks; SFRC beam; shear strength
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This paper presents the development of artificial neural network models for predicting the ultimate shear strength of steel fiber reinforced concrete (SFRC) beams. Two models are constructed using the experimental data from the literature and the results are compared with each other and with the formula proposed by Swamy et al. and Khuntia et al. It is found that the neural network model, with five input parameters, predicts the shear strength of beams more closely than the network with four input parameters. Moreover, the neural network models predict the shear strength of SFRC beams more accurately than the above-mentioned formulas. Further, the accuracy of predicted results is found not biased with concrete strength, shear span to depth ratio and the beam depth. Limited parametric studies show that the network model captures the RC beam's underlying shear behavior very well. (c) 2005 Elsevier Ltd. All rights reserved.
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