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Pro103

Development of ANN model for Bearing Strength of Concrete



Author(s): U. Raghu Babu and N.Venkata Ramana
Paper category: Proceeding
Book title: International Conference on Advances in Civil Engineering and Sustainable Construction
Editor(s): T.Ch. Madhavi, G. Prabhakar, Santhosh Ram, and P.M. Rameshwaran
Print-ISBN: None
e-ISBN: 978-2-35158-161-2
Publisher: RILEM Publications SARL
Publication year: 2016
Pages: 58-62
Total Pages : 5
Language : English


Abstract: This paper presents the study on workability, compressive strength and bearing strength of waste stone aggregate concrete reinforced with industrial wastes of metal scrap. An Artificial Neural Network (ANN) approach was used to model the bearing strength of waste stone aggregate concrete for bearing ratio of five. The target strength, bearing ratio,% of waste stone, and % of metal scrap were used as input terminals in the input layer and the output was bearing strength of the concrete. Data on the bearing strength of waste stone aggregate concrete with different replacement levels of natural coarse aggregate (25, 50, 75 and 100%) with and without industrial wastes was obtained from experimental study. The predicted values of the ANN were in accordance with the experimental data. The results indicate that the model can predict the bearing strength with adequate accuracy.


Online publication: 2017
Publication type: full_text
Public price (Euros): 0.00