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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/3716
Title: Concrete compressive strength prediction using ultrasonic pulse velocity through artificial neural networks
Authors: Gupta, Rajiv
Keywords: Civil Engineering
Concrete
Compressive strength
Artificial neural network
Issue Date: May-2006
Publisher: Elsiever
Abstract: Numerous attempts to use ultrasonic pulse velocity (UPV) as a measure of compressive strength of concrete has been made due to obvious advantages of non-destructive testing methods. The present study is conducted for prediction of compressive strength of concrete based on weight and UPV for two different concrete mixtures (namely M20 and M30) involving specimens of two different sizes and shapes as a result of need for rapid test method for predicting long-term compressive strength of concrete. The prediction is done using multiple regression analysis and artificial neural networks. A comparison between two methods depicts that artificial neural networks can be used to predict the compressive strength of concrete effectively. The results are plotted as experimentally evaluated compressive strength versus predicted strength through both methods of analysis.
URI: https://www.sciencedirect.com/science/article/pii/S0926580505000968?via%3Dihub
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/3716
Appears in Collections:Department of Civil Engineering

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