油门踏板预变形注射模设计

介绍了汽车油门踏板的结构特点,通过模流分析计算出变形量,将3D数据按变形量进行反变形设计,达到注射成型后塑件的设计尺寸。     

Strain-rate dependence of surface/subsurface deformation mechanisms during nanoscratching tests of GGG single crystal

Constant- and varied-depth nanoscratching tests of GGG single crystal were carried out at different scratching velocities. The morphologies of the scratched grooves and chips were analysed using scanning electron microscope. The experimental results indicated that higher scratching velocity led to shallower penetration depth, shallower residual depth, and larger continuous chips. Increasing the scratching velocity could effectively improve the plasticity and reduce the brittle-to-ductile transition depth of GGG single crystal. Based on the contact stress and contact area between the analysed sample and Berkovich indenter, a model for predicting the penetration depth was developed, which took into account the strain rate effect and elastic recovery of materials. The model was verified using constant- and varied-depth nanoscratching tests, and the predicted and experimental results were in good agreement. Subsurface damage underneath the ductile surface was characterised using transmission electron microscope. The TEM results demonstrated that higher scratching velocity led to the slipping planes appearing in more directions, which prevented the generation of long slipping plane and reduced the depth of the damage layers. The plastic deformation of GGG at the scratching velocity of 100 μm/s was dominated by poly-crystalline nanocrystallites and amorphous phases, and was similar to that at the low scratching velocity. This study provided a fundamental understanding of the strain-rate dependence of surface/subsurface deformation mechanisms of GGG during ultra-precision machining.     

Finite element analysis on shape deformation of the macro-structure region during hot-rolling process for gear steel FAS3420H and its modification

The rectangular macro-segregation region in the core of hot-rolled steel bar has a great influence on the heat treatment distortion of an automotive gear steel FAS3420H. In order to understand the distortion process of the segregation region during hot-rolling process, a finite element (FE) analysis of the whole hot-rolling process was carried out by software DEFORM-3D, and a constructed constitutive model was embedded into DEFORM-3D to describe the deformation process. The results show there is an inhomogeneous strain distribution at the cross-section of hot-rolled round bar, which results in uneven distortion of the segregation region in different directions. A square segregation region, which can reduce inhomogeneous distortion of gear in the subsequent heat treatment, is obtained after being rolled by simulation calculation verified through experiment.     

Revealing the relationships between alloy structure,composition and plastic deformation in a ternary alloy system by a combinatorial approach

A high-throughput approach based on magnetron co-sputtering of alloy libraries is employed to inves-tigate mechanical properties of crystalline and amorphous alloys in a ternary palladium(Pd)-tungsten(W)-silicon(Si)system with the aim to reveal the difference in plastic deformation response and extract the relevant structure-property relationships of the alloys in the system.It was found that in contrast to crystalline alloys,the amorphous ones,i.e.,metallic glasses,exhibited a much smaller fluctuation range in the plasticity parameters(Er2/H and Wp/Wt),indicating a significant difference in the plastic deformation mechanism controlling the mechanical properties for the respective alloys.We propose that the inho-mogeneous deformation of amorphous alloys localized in thin shear bands is responsible for the weaker compositional dependence of both plasticity parameters,while dislocation gliding in crystalline materials is significantly more dependent on the exact structure,thus resulting in a larger scattering range.Based on the representative efficient cluster packing model,a set of composition-dependent atomic structural models is proposed to figure out the structure-property relationships of amorphous alloys in Pd-W-Si alloy system.     

Grain refinement in low SFE and particle-containing nickel aluminium bronze during severe plastic deformation at elevated temperatures

The influence of particle size and morphology on grain refinement in low stacking fault energy(SFE)alloys was studied by comparing the grain structures in single-and multi-phase Al-bronze(AB)alloys following equal channel angular pressing(ECAP)between 350 and 500℃.In particular,nickel aluminium bronze(NAB)was chosen as it contained both coarse and fine rounded particles,as well as a lamellar phase which evolved during ECAP.Grain refinement in the single-phase alloy was achieved through dynamic recrystallisation initiated at deformed twin boundaries.By contrast,different mechanisms were observed in the particle-containing NAB.Recrystallisation around the coarse κⅡ particles(～5 μm)was promoted through particle stimulated nucleation(PSN),whereas recrystallisation in the region of the fine κⅣ(～0.4μm)was delayed due to the activation of secondary slip.Grain refinement in areas of the lamellar κⅢ showed significant variation,depending on the lamellar orientation relative to the shear plane of ECAP.As the lamellae deformed,numerous high angle grain boundaries were generated between fragments and served as nucleation sites for recrystallisation,while PSN occurred around spheroidised lamellae.The spreading of the κⅢ particles by ECAP then enhanced the total area of recrystallised grains.     

Combined effect of channel to rib width ratio and gas diffusion layer deformation on high temperature – Polymer electrolyte membrane fuel cell performance

The present study investigates the combined influence of Channel to Rib Width (CRW) ratio and clamping pressure on the structure and performance of High Temperature-Polymer Electrolyte Membrane Fuel Cell (HT-PEMFC) using a three-dimensional numerical model developed previously. It also considers the impact of interfacial contact resistance between the Gas Diffusion Layer (GDL) and Bipolar Plate (BPP). The structural analysis of the single straight channel HT-PEMFC geometry shows that the von-Mises stress greatly increases in the GDL under the ribs as the CRW ratio increases resulting in considerably high deformation. The cell performance analysis depicts the significance of ohmic resistance and concentration polarization for different CRW ratios, particularly at higher operating current densities. However, in low to medium current density regions, the CRW ratio has little influence on cell performance. A substantial impact on the species, overpotential, and current distributions is observed. The findings also reveal that the CRW ratio significantly affects the temperature distribution in the cell.     

Design of data feature-driven 1D/2D convolutional neural networks classifier for recycling black plastic wastes through laser spectroscopy

In this study, two types of convolutional neural network (CNN) classifiers are designed to handle the problem of classifying black plastic wastes. In particular, the black plastic wastes have the property of absorbing laser light coming from spectrometer. Therefore, the classification of black plastic wastes remains still a challenging problem compared to classifying other colored plastic wastes using existing spectroscopy (i.e., NIR). When it comes the classification problem of black plastic wastes, effective classification techniques by the laser spectroscopy of Fourier Transform-Infrared Radiation (FT-IR) with Attenuated Total Reflectance (ATR) and Raman to analyze the classification problem of black plastic wastes are introduced. Due to the strong ability of extracting spatial features and remarkable performance in image classification, 1D and 2D CNN through data features are designed as classifiers. The technique of chemical peak points selection is considered to reduce data redundancy. Furthermore, through the selection of data features based on the extracted 1D data with peak points is introduced. Experimental results demonstrate that 2DCNN classifier designed with the help of 2D data feature selection as well as 1DCNN classifier shows the best performance compared with other reported methods for classifying black plastic wastes.