Construction of reliable dynamic models of nanostructures is an important task for design procedures of different nanoresonator devices. Such theoretical models allow as to perform different numerical experiments, which is the key point in the development of advanced nanodevices. This paper presents a new nanoresonator model based on the axial vibration of the elastic multi-nanorod system. It is assumed that the system of multiple nanorods is embedded in an elastic medium. The governing equations of motion of a coupled multi-nanorod system are derived using the Hamilton’s principle, the nonlocal elastic constitutive relation, and Bishop’s rod theory, where effects of inertia of the lateral motion and the shear stiffness are considered. Exact closed form solutions for natural frequencies are obtained for one and multiple nanorod systems with different boundary conditions. Then, results for natural frequencies obtained by the finite difference method are compared with the results obtained analytically. Effects of nonlocal parameter, different rod theories, number of nanorods and stiffness coefficient of an elastic medium on natural frequencies are examined through several numerical examples.
The early studying of natural frequencies and associated mode shapes for different geometric parameters and different boundary conditions is considered an integral approach that has received great attention in industrial applications to prevent catastrophic failure in machines. The effect of different diameters (Solid and Hollow) on the transverse bending and torsional natural frequencies on a uniform steel beam with a circular cross-section is studied. The effect of different materials and different beam lengths on the fundamental transverse bending and torsional natural frequencies are introduced for Fixed-Free supported beam. Theoretical analysis calculation and the Finite Element Methods using ANSYS Workbench 17 software results are introduced. Theoretical and numerical methods give approximately the same results. Figures of effects of the beam length, material types, and different inner diameters on the transverse bending, and torsional natural frequencies of the uniform beam are performed.
This study was devoted in investigating the optimum geometric parameters for underactuated linkage three phalanges robotic finger. New kinematic and kinetic equations of grasping were derived in this research taking into account the angle for the ternary solid links of the four-bar linkages. To obtain the target of optimization, a gradient descent method was used which consists of three stages to find the optimal geometric parameters with high accuracy. Five criteria were selected to find the optimal solution by using multi objectives function algorithm, these are percentage of the grasping stability, the grasp forces, squeezing force, Mimic function for grasping task, and transmission angle for grasping operation. Gradient descent method starts by detecting the optimal geometric parameters for each criterion and choosing the best geometric parameters from the five criteria functions. At the optimum solution, the underactuated robotic finger prototype was built from hard Polylactic acid (PLA) plastic using rapid prototyping and was tested performance by grasping objects. Finally, the results have been shown that the robotic finger adapts to the wanted configurations.
The early detection of faults in rotating systems considers an integral approach that has received considerable attention from the industrial sector, as it contributes to preventing catastrophic failures in machines. In this research, the natural frequencies of a shaft, when it is healthy and when cracks with different depths are introduced, have been calculated. The deviation of the computed natural frequencies from the healthy ones is counted as a sign of the presence of an abnormality in the system. For this intention, the finite element analysis (FEA) method based on ANSYS software has been utilized to obtain the first five natural frequencies of the shaft when there is a crack of different severity at different positions. The results of the FEA are used for designing an artificial neural network (ANN) model that can be easily used to predict the first five natural frequencies of the shaft based on just the crack's position and depth. Finally, the predicted natural frequencies by the deigned ANN have been compared to their peers that were computed using the FEA method. The absolute error percentage has then been calculated and used to get an indication of how close the result of both techniques is. The recorded highest error percentage was 0.67%, which is quite small and referring to that the designed ANN can accurately predict the natural frequencies of rotating systems.
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