Reza Mikaeil; Mostafa Piri; Sina Shaffiee Haghshenas; Nicola Careddu; Hamid Hashemolhosseini
Abstract
The noise of drilling in the dimension stone business is unbearable for both the workplace and the people who work there. In order to reduce the negative effects drilling has on the health of the environment, the drilling noise has to be measured, assessed, and controlled. The main purpose of this work ...
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The noise of drilling in the dimension stone business is unbearable for both the workplace and the people who work there. In order to reduce the negative effects drilling has on the health of the environment, the drilling noise has to be measured, assessed, and controlled. The main purpose of this work is to investigate an experimental-intelligent method to predict the noise value of drilling in the dimension stone industry. For this purpose,135 laboratory tests are designed on five types of rocks (four types of hard rock and one type of soft rock), and their results are measured in the first step. In the second step, due to the unpredicted and uncertain issues in this case, artificial intelligence (AI) approaches are applied, and the modeling is conducted using three intelligent systems (IS), namely an adaptive neuro-fuzzy inference system-SCM (ANFIS-SCM), an adaptive neuro-fuzzy inference system-FCM (ANFIS-FCM), and the radial basis function network (RBF) neural network. 75% of the samples are considered for training, and the rest for testing. Several models are constructed, and the results indicate that although there is no significant difference between the models according to the performance indices, the proposed construction of ANFIS-SCM can be considered as an efficient tool in the evaluation of drilling noise. Finally, several scenarios are designed with different input modes, and the results obtained prove that the types of rock and the drill bits are more important than the operational characteristics of the machine.
M. Eftekhari; A. Baghbanan; H. Hashemolhosseini
Abstract
The cracked Brazilian disc (CBD) specimen is widely used in order to determine mode-I/II and mixed-mode fracture toughness of a rock medium. In this study, the stress intensity factor (SIF) on the crack-tip in this specimen is calculated for various geometrical crack conditions using the extended-finite ...
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The cracked Brazilian disc (CBD) specimen is widely used in order to determine mode-I/II and mixed-mode fracture toughness of a rock medium. In this study, the stress intensity factor (SIF) on the crack-tip in this specimen is calculated for various geometrical crack conditions using the extended-finite element method (X-FEM). This method is based upon the finite element method (FEM). In this method, the crack is modeled independently from the mesh. The results obtained show that the dimensionless SIFs for the pure modes I and II increase with increase in the crack length but the angle in which pure mode-II occurs decreases. For the mixed-mode loading, with increase in the crack angle, NI value decreases, while NII value increases to a maximum value and then decreases. The results obtained from the crack propagation examinations show that the crack angle has an important effect on the crack initiation angle. The crack initiation angle increases with increase in the crack angle. When the crack angle is zero, then the crack is propagated along its initial direction, whereas in the mixed-mode cases, the crack deviates from the initial direction, and propagates in a direction (approximately) parallel to the direction of maximum compressive load.