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In this article, the fatigue crack closure in a new titanium alloy is carried out under constant amplitude cyclic loading with the combination of the simulation method and experiments. A numerical simulation of the crack closure effect on a new titanium alloy under different load ratios was carried out to analyze the effect of grid size on the crack closure level and to obtain the fatigue crack opening load level under different load ratios. The experimental study of the fatigue crack growth rate of the new titanium alloy under different load ratios has demonstrated that the fatigue crack growth rate is affected by the stress ratio. With the increase in load ratio, the crack expansion rate of new titanium also increases. Combined with the simulation, the experiments show that the crack closure effect induced by the plastic region at the crack tip is the main reason for the load ratio effect on the fatigue crack expansion rate of the new titanium alloy.

At present, the existing influence evaluation algorithms often ignore network structure attributes, user interests and the time-varying propagation characteristics of influence. To address these issues, this work comprehensively discusses users’ own influence, weighted indicators, users’ interaction influence and the similarity between user interests and topics, thus proposing a dynamic user influence ranking algorithm called UWUSRank. First, we determine the user’s own basic influence based on their activity, authentication information and blog response. This improves the problem of poor objectivity of initial value on user influence evaluation when using PageRank to calculate user influence. Next, this paper mines users’ interaction influence by introducing the propagation network properties of Weibo (a Twitter-like service in China) information and scientifically quantifies the contribution value of followers’ influence to the users they follow according to different interaction influences, thereby solving the drawback of equal value transfer of followers’ influence. Additionally, we analyze the relevance of users’ personalized interest preferences and topic content and realize real-time monitoring of users’ influence at various time periods during the process of public opinion dissemination. Finally, we conduct experiments by extracting real Weibo topic data to verify the effectiveness of introducing each attribute of users’ own influence, interaction timeliness and interest similarity. Compared to TwitterRank, PageRank and FansRank, the results show that the UWUSRank algorithm improves the rationality of user ranking by 9.3%, 14.2%, and 16.7%, respectively, which proves the practicality of the UWUSRank algorithm. This approach can serve as a guide for research on user mining, information transmission methods, and public opinion tracking in social network-related areas.

Electromechanical actuators (EMAs) have shown a high efficiency in flight surface control with the development of more electric aircraft. In order to identify the abnormalities and potential failures of EMA, a methodology for fault diagnosis is developed. A simulating model of EMA is first built to perform different working states. Based on the modeling of EMA, the corresponding faults are then simulated to re-generate the fault data. Afterwards, a gated recurrent unit (GRU) and co-attention-based fault diagnosis approach is proposed to classify the working states of EMA. Experiments are conducted and a satisfying classification accuracy on simulated data is obtained. Furthermore, fault diagnosis on an actual working system is performed. The experimental results demonstrate that the proposed method has a high efficiency.