In this paper, a theoretical scheme is proposed for shape-programming of thin hyperelastic plates through differential growth. First, starting from the 3D governing system of a hyperelastic (neo-Hookean) plate, a consistent finite-strain plate equation system is formulated through a series expansion and truncation approach. Based on the plate equation system, the problem of shape-programming is studied under the stress-free assumption. By equating the stress components in the plate equations to be zero, the explicit relations between the growth functions and the geometrical quantities of target shape of the plate are derived. Then, a theoretical scheme of shape-programming is proposed, which can be used to identify the growth fields corresponding to arbitrary 3D shapes of the plate. To demonstrate the efficiency of the scheme, some typical examples are studied. The predicted growth functions in these examples are adopted in the numerical simulations, from which the target shapes of the plate can be recovered completely. The scheme of shape-programming proposed in the current work is applicable for manufacturing intelligent soft devices.
3(a), in addition, a low internal dislocation density was revealed, which resulted from the great reduction of single rolling pass during continuous rolling, these internal dislocation and deformation band provide nucleation site, and result in the high nucleation rate of ferrite crystal. Moreover, the dislocation/precipitation interaction in ferrite matrix would be one of the dominant reasons of strengthening.8) It was observed that the precipitates are mostly spherical in appearance, and the TEM microstructure of extraction replica also reveal the existence of precipitates clearly in Fig. 3(b). Large precipitates have been identified as carbide particles through electron dispersive analysis as shown in Fig. 3(c), but the size distribution of other shapes could not be estimated because the number was so small, which indicates that they are present in the austenite prior to precipitate from the austenite during cooling.Selective area electron diffraction study was carried out with TEM to clarify the orientation relationship between the tiny precipitates and the a-Fe matrix. beam parallel to [100] direction. A lot of diffraction spots are seen in addition to the matrix spots. It is difficult to determine the relationship between the particles and the matrix from this pattern. If we assume that the particles have a cube relationship with the matrix, the spots that do not belong to the matrix correspond very well to those of ferrite phase with the zone axis being parallel to [001]. Thus, the assumption that the tiny have cube-cube relationship with the matrix is reasonable. The dark field image in Fig. 3(e) is taken using the super lattice spots shown in the inset diffraction pattern of Fig. 3(d) and reveals that the precipitates (bright) are very small and coherent with the matrix; it would show a very effective pinning in ferrite matrix.9) The coherent orientation relationship between the tiny precipitates and the a-Fe suggests that these tiny particles may precipitate from the a-Fe instead of the g-Fe. Furthermore, the coherent orientation relationship may influence the interfacial energy between the particle and the matrix as well as the nucleation process of the particles. 10)As shown in Fig. 4(a), a small cluster of particles were observed at junctions of a curved grain boundary. The recrystallization nuclei in these alloys would form primarily adjacent to nanometer-sized particles that are produced during casting and the movement of the boundary need overcoming the pinning force of particle, which will result in a local increase in the driving force due to changes in boundary curvature and thermal activation.11) In conclusion, small particles can restrict subsequent grain boundary movement and promote a fine-grained microstructure through Zener drag. Smith 12) attributes to Zener the analysis of the pinning force exerted by particles on grain boundary, and Azmir Har et al. had also simulated particle pinning force acting on the grain boundary.13) The geometry of such an interaction is shown in Fig. 4(b).C...
In the grinding process, the workpiece would not only be cut by abrasive grains, but also have adhesive wear caused by high temperature and heavy load, which makes the surface quality of the workpiece worse. In this paper, a wear test method considering speed, force, wear coefficient, temperature and hardness was proposed. A new wear Research highlights: 1. Proposed a wear prediction physical model considering speed, contact force, temperature, wear coefficient and material hardness for grinding process, which can predict surface morphology. 2. A method for measuring and calculating surface wear in grinding process was proposed.3. The grinding temperature field, wear volume, surface morphology and wear mechanism are analyzed, which provides technical support for improving grinding surface quality from the perspective of grinding burn and grinding.
Wear debris generated in a pitting process of planetary gearboxes carries valuable information about health status. However, RGB images of online wear debris are often affected by image blur caused by Gaussian noise, high-frequency noise, and other random noises besides Gaussian noise, including bubbles in lubricating oil, dark oil caused by contamination, and the temperature rise of electronic components. To address these issues, in this work, an image denoising model WVBOD was proposed based on the fusion of wavelet, variational mode decomposition and non-local mean filtering, which makes full use of the advantages of above three denoising methods, removes the noise in the image and preserves the details of the image information. Comparing the peak signal-to-noise ratio and structural similarity of the denoised image using different models, the WVBOD objectively acquired better denoising result than other advanced denoising methods. In addition, the previous online wear debris features mainly focus on using changes in particle concentration to reveal the deterioration of the wear state. Based on the fact that the quantity of large wear debris increases with the evolution of gear pitting, a novel wear index Z(i), representing the size gradient of large wear debris and sensitive to an increase in large wear debris, is proposed for the denoising image. Then early fault warning can be realized for the planetary gearbox. Finally, it is verified by the size and quantity features extracted by using offline oil analysis techniques.INDEX TERMS Planetary gears, Online monitoring, Wear debris image analysis, Pitting.
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