The three-dimensional dynamic behaviour of a tip vortex generated by a NACA $66_2$ -415 hydrofoil is investigated under wetted flow and cavitating conditions using time-resolved tomographic particle image velocimetry. Two main cavitation modes are studied, namely the breathing and double-helical modes. The time-averaged flow field consists of a system of two streamwise vortices for all three conditions. The shape of the tip vortex resembles that of the cavitation mode, instead of a circular cylinder. Multi-scale vortical structures are captured in the instantaneous flow field. The surface oscillation of the cavity contributes to the growth of Kelvin–Helmholtz instability over the tip vortex, leading to the onset of hairpin vortices. Stronger spanwise interaction between the tip vortex and flow separation of the hydrofoil is produced by cavitation, further intensifying the perturbation growth. The proper orthogonal decomposition analysis gives insight into the relationship between cavity oscillation and vortex instability. Two major types of unstable modes of the tip vortex are obtained, leading to serpentine centreline displacement and elliptical deformation motion. The selection of the dominant unstable mode is associated with cavity surface oscillation. For the wetted flow condition, the displacement mode dominates the growth of vortex perturbation, while for breathing mode cavitation, the most energetic unstable mode changes into an elliptical deformation pattern, the disturbance energy of which is negligible in the wetted flow condition. Consistency is found between the peak frequency of the deformation mode and the cavity resonance frequency, indicating the contribution of cavity oscillation to the disturbance growth and breakdown of the tip vortex.

The interactions between finite-size spheroidal particles and upward turbulent flows in a vertical channel are numerically simulated with a direct-forcing fictitious domain method at two particle settling coefficients . The settling particles tend to migrate towards the channel centre due to the Saffman effect, and the migration is strongest for the spherical particles. The non-spherical particles tend to align their long axes with the streamwise direction in the near-wall region, and perpendicular to the streamwise direction in the bulk region due to the significant settling effect.

A parallel direct-forcing (DF) fictitious domain (FD) method for the simulation of particulate flows is reported in this paper. The parallel computing strategies for the solution of flow fields and particularly the distributed Lagrange multiplier are presented, and the high efficiency of the parallel code is demonstrated. The new code is then applied to study the effects of particle density (or particle inertia) on the turbulent channel flow. The results show that the large-scale vortices are weakened more severely, and the flow friction drag increases first and then reduces, as particle inertia is increased.

As a conventional and persistent topic, a single bubble freely ascending in Newtonian liquids is investigated based on its shape and motion predictions using the strategy of machine learning. The dataset for training, validating, and testing neural networks is composed of the current experimental results and the extensively collected data from previous research works, which covers a broad range of dimensionless parameters that are ${10}^{-3}\le Re\le {10}^5,\hspace{0.17em}{10}^{-2}\le Eo\le {10}^3,\hspace{0.17em}{10}^{-5}\le We\le {10}^2$ , and ${10}^{-14}\le Mo\le {10}^7$ . The novel models of the aspect ratio E and drag coefficient $C_D$ are proposed based on a backpropagation neural network. The comparisons of the conventional correlations indicate that the new E model presents a significant superiority. This E model also has a good capability to predict the minimum E as about 0.26 that is consistent with the theoretical value $E_{We\to \infty }\approx 0.25$ . Moreover, the $C_D$ models are divided into E-independent and E-dependent types. The performances of these two type models are quite similar and both agree well with the experimental results. The errors of the $C_D$ predictions for Re > 1 are mostly in the range of $\pm 20\%$ .

Tip clearance cavitation (TCC) is a type of vortex cavitation. It widely exists in axial flow hydraulic machinery and has significant negative influence on the mechanical service life and the operating stability. It is necessary to suppress the tip clearance vortices (TCV) to control the TCC in engineering applications. Based on the analysis of the advantages and disadvantages of the present various suppression strategies, a new coupling method is proposed in this study by combining the damping approach and the diversion approach. Porous medium material is used to realize the coupling effect. A 2 mm span length porous tip is installed on the solid tip surface of a hydrofoil under two gap sizes conditions (representing two types of gap flow pattern), and excellent suppression results of the TCV and TCC are obtained. The characteristics and mechanism of the clearance flow are analyzed by numerical simulation. The numerical accuracy is verified by experimental qualitative observations. The simulation results show that the temporal and spatial stability of the clearance flow field is enhanced, and the leakage velocity and the TCV strength are weakened via the combined action of damping and diversion effects. There is a difference in the damping mechanism between the two gap flow patterns. It is a comprehensive result of viscous dissipation and momentum loss in the jet pattern represented by the small gap size, and primarily, the result of momentum loss in the rolling pattern represented by the large gap size.