Volume 9, Issue 3 (12-2015)
2015, 9(3): 2983-3002 |
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Sharifi J, Nikodel M R. Prediction of Concrete Strength Containing Different Aggregates through Artificial Neural Networks. Journal of Engineering Geology 2015; 9 (3) :2983-3002
URL: http://jeg.khu.ac.ir/article-1-1819-en.html
URL: http://jeg.khu.ac.ir/article-1-1819-en.html
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Abstract: (6423 Views)
In this research, prediction of concrete strength containing different aggregates using Non-destructive (Ultrasonic) testing through Artificial Neural Networks was carried out. For this purpose, aggregates with different properties were selected from the quarries, and then their destructive and nondestructive properties were obtained in laboratory. The significance of this research, using different aggregates with physical, mechanical and chemical properties also used two different test methods, such as Non-destructive static and dynamic testing, which are respectively uniaxial compressive strength and compressive wave velocity. Thus, this model includes various types of samples and the prediction model includes static and dynamic tests. The results showed that the use of artificial neural networks not only increases the accuracy, but also it reduces costs and time.
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