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Geomechanics and Engineering Volume 15, Number 1, May20 2018 , pages 631-643 DOI: https://doi.org/10.12989/gae.2018.15.1.631 |
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Prediction of the mechanical properties of granites under tension using DM techniques |
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Francisco F. Martins, Graça Vasconcelos and Tiago Miranda
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| Abstract | ||
| The estimation of the strength and other mechanical parameters characterizing the tensile behavior of granites can play an important role in civil engineering tasks such as design, construction, rehabilitation and repair of existing structures. The purpose of this paper is to apply data mining techniques, such as multiple regression (MR), artificial neural networks (ANN) and support vector machines (SVM) to estimate the mechanical properties of granites. In a first phase, the mechanical parameters defining the complete tensile behavior are estimated based on the tensile strength. In a second phase, the estimation of the mechanical properties is carried out from different combination of the physical properties (ultrasonic pulse velocity, porosity and density). It was observed that the estimation of the mechanical properties can be optimized by combining different physical properties. Besides, it was seen that artificial neural networks and support vector machines performed better than multiple regression model. | ||
| Key Words | ||
| granite; tensile behavior; mechanical properties; physical properties; data mining techniques | ||
| Address | ||
| Francisco F. Martins, Graça Vasconcelos and Tiago Miranda: ISISE, Department of Civil Engineering, University of Minho, Guimarães, Portugal | ||