Superhydrophobic fiber films, as a typical superhydrophobic material, have advantages such as self-cleaning, non-wettability, and pollution resistance. They can be widely used in oil-water separation, antibacterial, anti-pollution, anti-icing, and self-cleaning fields. Traditional electrospun superhydrophobic fiber films face difficulties in fabricating fibers with large contact angles due to the non-Newtonian fluid flow and Taylor cone jet trajectory limitations. To address this challenge, this study develops a novel ultrasonic-magnetic field coupling electrospinning strategy for fabricating poly(methyl methacrylate)-polystyrene (PMMA-PS) fibrous films with enhanced superhydrophobicity. Physical, chemical, and contact angle measurements were used to analyze the morphology, composition, and hydrophobic properties of the fabricated films. The results showed that by controlling the blend ratio of PMMA and PS and optimizing the electrospinning process with ultrasonic vibration and magnetic field coupling, PMMA-PS fibers with better fiber refinement, closer spindle-shaped arrangements, and significantly increased roughness were successfully fabricated. When using 15% PMMA and 15% PS solutions, the static contact angle of the resulting fiber films reached 173.1°, demonstrating the best superhydrophobicity. The study suggests that optimizing the surface morphology of the nanofibers is an effective method to improve hydrophobicity and provides a new approach for fabricating superhydrophobic fiber films.

When predicting cavitation erosion risk in practical engineering bearings, traditional vapor cavitation models neglect the effect of dissolved air in the lubricant and fail to account for its precipitation and dynamic evolution in local low-pressure regions, leading to deviations in the prediction of cavitation extent, intensity, and distribution. Taking the main bearing of a certain type of diesel engine as the research object, a coupled cavitation model combining the Schnerr–Sauer vapor cavitation model and a Henry’s law-based gas dissolution model is established. Together with large eddy simulation (LES), the accuracy of the numerical model is verified by constructing a visualization experimental platform. Numerical analysis is then carried out to investigate the effect of dissolved air in the lubricant on the cavitating flow field of the bearing oil film under initial conditions ranging from undersaturated to saturated states (air mass concentration of 0–0.4 g/L). The results show that as the mass concentration increases, the amount of air precipitation in the near-wall region gradually increases and extends downstream. When the mass concentration reaches 0.1 g/L, the precipitated air mass reaches 50% of the vapor cavitation mass, significantly expanding the cavitation range. In the critical mass concentration range of 0.24–0.28 g/L, intense air precipitation occurs inside the oil hole and covers the entire region. Through the synergistic effects of inhibiting high-speed jets, altering the local pressure field, and competing for cavitation nuclei, the precipitated air significantly suppresses the development of near-wall vapor cavitation, and the vapor cavitation mass decreases by 83.1% at saturation. In summary, within the practical mass concentration range, the presence of dissolved air significantly enhances the gas phase intensity near the bearing bush surface and expands the cavitation range, thereby exacerbating the risk of cavitation erosion damage in this region, while having little effect on the oil supply performance of the oil hole.

Cavitation flow inside an injector control valve significantly affects the injection performance and operational reliability of diesel engines, and the selection of turbulence and cavitation models is crucial for accurately predicting cavitating flows. To evaluate the predictive performance of different model combinations, a numerical model was established based on the Winklhofer microchannel experiment. Three large eddy simulation (LES) subgrid-scale (SGS) models were coupled with three cavitation models, and their performance was assessed by comparing the predicted outlet mass flow rate, centerline pressure distribution, and cavitation distribution with the experimental results. The results show that the outlet mass flow rate increases with the inlet–outlet pressure difference. When the pressure difference reaches approximately 70 bar, the growth rate decreases significantly, indicating the onset of typical cavitation-induced flow choking. Under low pressure differences, the prediction results of different model combinations are generally similar, whereas significant discrepancies are observed under high-pressure-difference conditions with intense cavitation. In terms of mass flow rate prediction, the Dynamic Smagorinsky + FRP model combination shows the best agreement with the experimental results in the pressure difference range of 70–85 bar, with an error of 3.06%. For pressure distribution prediction, the Dynamic Smagorinsky + FRP and Smagorinsky + FRP model combinations exhibit relatively smaller errors than the other combinations. The cavitation distribution results indicate that, compared with the LES subgrid-scale model, the cavitation model has a more pronounced influence on the extent and evolution of the cavitation region. Overall, the Dynamic Smagorinsky + FRP model demonstrates the best comprehensive predictive performance. Furthermore, this model was applied to the simulation of cavitating flow in a two-dimensional injector control valve, and the predicted results agree well with the visualization experiments. The present study provides a useful reference for the numerical simulation and structural optimization of cavitating flows in injector control valves.