The distributions of plastic strain near grain boundaries induced by fatigue loading were investigatedby the fiducial grid method in pure aluminum specimens, and the resulted grain boundary sliding(GBS) was systematically analysed. The results show that the strain field near a grain boundary isnonuniform. GBS is restricted by the junction of grain boundaries and causes discontinuities of bothdisplacement and strain. A peak value of shear strain was created in short-range area across the grainboundary. GBS plays an important role in cyclic softening and secondary hardening. The control fac-tor of GBS is the relative orientation between two grains and the macro orientation of the grainboundary rather than the ∑ value of the boundary. 相似文献
In-phase(IP) and out-of-phase(OP)thermal-mechanical fatigue(TMF) behavior of cast Ni-base superalloy K417 was studied.All experiments were carried out under total strain control with temperature cycling between 400-850℃.Both in-phase and out-of-phase TMF specimens exhibited cyclic hardening followed by cyclic softening at the minimum temperature.Besides,they cyclically hardened in the early stage of life followed by cyclic softening at the minimum temperature.Besides,they cyclically hardened in the early stage of life followed by cyclic softening at the maximum temperature.OP TMF life was longer than of IP TMF.Various damage mechanisms operating in different controlled strain ranges and phasing were discussed.A few life prediction methods for isothermal fatigue were used to handle TMF fatigue and their applicability to superalloy K417 was evaluated.The SEM analysis of the fracture surface showed that transgranular fracture was the principal cracking mode for both IP and OP TMF.Oxidation was the main damage mechanism in causing shorter fatigue life for IP TMF compared with OP TMF. 相似文献
With the rapid development of information technology, social media has been widely used, and Internet information has been exploded, and consumers may experience information overload. Recommender systems using the social recommendation method that integrates social relationship information can provide users with target information that meets their needs. However, most of the existing methods only rely on the user’s ordinary friends to make recommendations, neglecting another influential group, the opinion leaders. In this study, we propose a new social recommendation method based on opinion leaders. The proposed method assumes that the influence of the opinion leader on the user is much greater than that of the user’s ordinary friends. The experimental results on two real datasets show that the proposed method not only has a better recommendation effect than the state-of-the-art recommendation algorithms, but also has a good performance in the cases of cold-start users.