Al2O3f/Al-4%Cu合金复合材料界面偏析研究

利用挤压铸造制备了Ａｌ２Ｏ３ｆ／Ａｌ－４％Ｃｕ合金复合材料,研究了复合材料的界面偏析。研究结果表明,在复合材料的凝固末期,由于选择结晶,剩余液相中的溶质变化导致基体合金类型的改变,最张立生界面偏析。偏析对材料的组织结构和性能的影响可能是双重的。     

A Two-dimensional Stress Analysis and Strength of Single-lap Adhesive Joints of Dissimilar Adherends Subjected to External Bending Moments

The stress distributions of single-lap adhesive joints of dissimilar adherends subjected to external bending moments are analyzed as a three-body contact problem by using a two-dimensional theory of elasticity (plane strain). In the analysis, dissimilar adherends and an adhesive are replaced by finite strips. In the numerical calculations, the effects of the ratio of Young's moduli of adherends, the adherend thickness ratio and the adherend length ratio between dissimilar adherends on the stress distributions at the interfaces are examined. The results show that the stress singularity occurs at the ends of the interfaces, and its intensity is greater at the interface of the adherend with smaller Young's modulus. It is also noted that the singular stress is greater at the interface of the thinner adherend. It is found that the effect of the adherend length ratio on the stress singularity at the interfaces is very small. Joint strength is predicted by using the interface stress and it was measured by experiments. From the analysis and the experiments, it is found that the joint strength increases as Young's modulus of adherends and the adherend thickness increase while the effect of the adherend lengths on the joint strength is small. For verification of the analysis, a finite element analysis (FEA) is carried out. A fairly good agreement of the interface stress distribution is seen between the analytical and the FEA results.     

Analytical and Numerical Calculation of the Energy Release Rate for the Microbond-Test

The energy release rate for interface crack propagation for the Microbond-Test specimen is calculated by using several stress analysis methods. For the corresponding finite element calculation an axisymmetrical model (elliptical droplet) and linear elastic material properties are used. The analytical approximations use several stress analysis methods to obtain the energy release rate.

The resulting energy release rate curves suggest that the debonding process can be described at least partially as a stable crack propagation along the interface. Some experiments confirm this prediction. The matrix droplet contribution to the energy release rate can be considerable. Because of the very complex stress fields in the droplet a simple analytical approximation cannot be given. The qualitative dependences on the material properties and on the geometry can be explained from the presented analysis. The remaining correction factor can be obtained from a numerical calculation.     

A Stress Singularity Approach for the Prediction of Fatigue Crack Initiation in Adhesive Bonds. Part 1: Theory

Since crack initiation in adhesive bonds tends to occur near the interface corners where the stress fields are singular, we define a fatigue initiation criterion using stress singularity parameter, Q (a generalized stress intensity factor) and the singular eigenvalue, λ.

Hattori et al., successfully used a generalized stress intensity factor to characterize the static strength of bimaterial interfaces. We show that this criterion is only appropriate for situations in which the adhesive contact angle is no larger than 90° and the modulus ratio (adhesive to adherend) is smaller than 0.1. Fortunately, these conditions are often met in real joints, permitting the use of a single eigenvalue approach. We then extend this criterion to the case of fatigue arising from mechanical, thermal, or hygroscopic cycling.

In preparation for Part 2 (experimental), the special case of an epoxy wedge on a flat aluminum substrate is considered. The singularity is analyzed both analytically and numerically. The scale of the region dominated by the singularity is found to be of the order of 100 μm. The size of the plastically yielded zone near the apex is found to decrease extremely rapidly as the stress intensity factor goes down, thereby increasing the applicability of the method at the low stress levels often encountered in fatigue.     

分散控制系统在钛白生产中的应用

介绍了分散控制系统在钛白生产中的应用,着重介绍该系统的硬件配置、控制系统组合、流程图绘制及控制程序编制等。阐述了分散控制系统在钛白生产中应用的优越性     

钛/钢爆炸复合板界面连接机理与力学行为

本文表征了钛/钢爆炸焊接复合板的界面组织和剪切性能,研究爆炸复合过程的界面结合机理。结果表明,在金属板之间形成了波状界面组织,剧烈塑性变形造成钢基体发生明显的塑性流动,并在界面形成连续的漩涡形貌。TEM和XRD检测证实界面存在纳米尺度的过渡层,并包含有固溶体组织和少量金属间化合物。波状界面组织改善了复合板沿爆炸方向的界面剪切强度,剪切断口显示漩涡组织发生韧性断裂形貌。     

多孔结构阻挡层对CuW/Al界面组织及性能的影响

将CuW假合金表面部分Cu腐蚀掉,预留100-200μm厚度的W骨架,随后通过化学镀在W骨架上形成多孔结构Ni扩散层,最后在700℃下用固-液连接的方法制备出CuW/Al整体材料。比较了不同保温时间下界面扩散区域微观组织结构,分析了界面扩散溶解层金属间化合物析出序列。结果表明,CuW/Al界面间多孔结构Ni中间层可有效抑制柱状Al2Cu相的生成和柯肯达儿孔洞裂纹的产生,界面处生成物主要以Al2Cu和 Al5W化合物为主。添加多孔结构Ni中间层可提高CuW/Al界面结合性能和电导率。     

Impacts of zinc layer and pouring method on interface performance for Al-22Si/ZL104 bi-metal

Bi-metal material consisting of spray-formed Al-22Si and ZL104 is a suitable candidate for applications in internal combustion engines. This research investigated the effects of surface treatment and appropriate gating system on the microstructures and mechanical properties in evaluating the optimal strategy for producing high quality bi-metal materials. The bi-metal materials were prepared using ZL104 gravity casting by different pouring types around the spray-formed Al-22Si with varied surface treatments. The wettability between Al-22Si and ZL104 was significantly improved when Zn coating was used to remove the natural oxide layer. This research also obtained the improved interfacial microstructures and interfacial bonding strength for materials when applying the appropriate pouring method. The hardness profiles of Al-22Si/ZL104 bi-metal were consistent with the observed microstructures. The average tensile strength of the bi-metal material with zinc coating is ~42.3 MPa, which is much higher than that with oxide film at ~10 MPa. The process presented is a promising and effective approach for developing materials in the automotive industry.     

Effects of glass bead content and surface treatment on viscoelasticity of filled polypropylene/elastomer hybrid composites

The dynamic mechanical properties of A‐glass bead filled polypropylene (PP)/ethylene–propylene–diene monomers polymer (EPDM) ternary composites have been measured over a temperature range from −80 °C to 100 °C and at a fixed frequency of 1 Hz, using a dynamic mechanical analyser (DMA), to identify the effects of the filler content and its surface treatment with a silane coupling agent on the dynamic viscoelastic behaviour. The results show that the storage modulus (E′_c) and loss modulus (E ″_c) of these composites with 10% volume fraction of EPDM at 25 °C increase non‐linearly with increasing volume fraction of glass beads (ϕ_g). At the same test conditions, the E′_c value of the PP/EPDM filled with pretreated glass beads is higher than that of the uncoated glass bead filled PP/EPDM system, especially at higher ϕ_g, while the difference in E ″_c between both systems is very small. The mechanical damping for the former decreases with increasing ϕ_g, but the opposite is true for the latter. The glass transition temperature of these composites varies irregularly with ϕ_g. The dynamic complex viscosity increases nonlinearly with an increase of ϕ_g. In addition, the interfacial structure between the matrix and inclusions has been observed by means of a scanning electron microscope. © 1999 Society of Chemical Industry     

Detection of motor imagery EEG signals employing Naïve Bayes based learning process

The objective of this study is to develop a reliable and robust analysis system that can automatically detect motor imagery (MI) based electroencephalogram (EEG) signals for the development of brain–computer interface (BCI) systems. The detection of MI tasks provides an important basis for designing a communication way between brain and computer in creating devices for people with motor disabilities. This paper presents a synthesis approach based on optimum allocation system and Naive Bayes (NB) algorithm for detecting mental states based on EEG signals. In this study, an optimal allocation (OA) is introduced to discover the most effective representatives with minimal variability from a large number of MI based EEG data and the NB classifier is employed on the extracted features for discriminating the MI signals. The feasibility and effectiveness of the proposed method is demonstrated by analyzing the results and its success on two public benchmark datasets. The results indicate that the proposed approach outperforms the most recently reported five methods and achieves 0.64–20.90% improvement on average accuracy. The performances of this proposed approach implies that it can be reliably used to detect EEG based MI activity and can be a promising avenue for EEG based BCI applications.