Owing to the strong three-dimensionality and transient evolution, the flow dynamics of a cavitating jet inside a water poppet valve is poorly understood, leading to insufficient basis for exploring the governing mechanism of cavitation effects. In this paper, a three-dimensional simulation considering the compressibility of each constituent phase is performed, to clarify the governing mechanisms under the cavitating flow inside two water poppet valves. The cavitation structures inside the poppet valves are primarily located at three regions and triggered by different mechanisms. The vortex cavitation, mainly confined within the free shearing layer, is due to vortex dynamics, while the attached cavitation at the poppet trailing edge and within the chamfered groove arises from flow separation. The fast laminar–turbulent transition process contributes to the three-dimensionality within the free shearing layer and the rear part of the chamfered groove. The flow separation due to the chamfered groove leads to increased velocity of the central potential core, contributing to a different flow discharge performance from that of the poppet valves with a sharp seat. In addition, the periodic variation in cavitation reveals the significant interaction between the shed cavitating vortex and attached cavitation at the poppet trailing edge. In conclusion, the change in velocity distribution due to different poppet valve seat structures leads to variation in flow discharge performance, and the vortex dynamics makes sense for all three kinds of cavitation occurring inside poppet valves.

To study dynamic evolution law of mechanical reliability caused by wear, gear transmission system is taken as a research object. Considering the effect of clearance caused by wear on gear teeth load in double meshing area, the formula of dynamic distribution load which is undertaken by two adjacent teeth is deduced. And the distributed pressure and meshing speed, which should be taken into account while calculating gear wear, are obtained based on the Winkler surface model and principle of tooth mesh. Based on the Archard’s wear model, numerical simulation model for wear in spur gear is deduced, and the wear depth of each meshing points on teeth outline with different wear cycles are obtained. The calculation wear model is replaced with a surrogate model with Neural Network and Kriging method to overcome time-consuming defect. Random process model is integrated with the surrogate model, and dynamic reliability for nonlinear stochastic structure with unknown distribution characteristic is obtained with Neural Network-based Edgeworth series technique and four moment methods, which is compared with Kriging-based Monte Carlo simulation method. The computational efficiency and accuracy are also demonstrated.

The stiffness degradation of the servo turret will inevitably lead to accuracy reduction of the cutter head and the tool change. Considering the degradation process of servo turret with stiffness, by introducing the stiffness cumulative damage theory into the vibration differential equation, combined with stochastic finite element method and reliability theory, the mathematical model of the reliability and reliability sensitivity for vibration transmission path system with random parameters was established. Taking a typical power servo turret for example, the reliability and the reliability sensitivity to each random parameter at the mean value with the excitation frequency and time were obtained. The results showed that the shift of the reliability and reliability sensitivity to random parameters with time was caused by the stiffness degradation, the peak value of reliability sensitivity fluctuated with time, and the peak value in the frequency domain at the initial time was not necessarily the maximum value in the time domain. The accuracy of the proposed method was further proved by the Monte Carlo method. Optimizing sensitive parameters could enhance the system stability and effectively prevent the resonance failure caused by the change of the resonance region.