Cavitation typically occurs when the fluid pressure is lower than the vapor pressure in a local thermodynamic state,and the flow is frequently unsteady and turbulent.The Reynolds-Averaged Navier-Stokes(RANS)approach has been popular for turbulent flow computations.The most widely used ones,such as the standard k-εmodel,have well-recognized deficiencies when treating time dependent flow field.To identify ways to improve the predictive capability of the current RANS-based engineering turbulence closures,conditional averaging is adopted for the Navier-Stokes equation,and one more parameter,based on the filter size,is introduced into the k-εmodel.In the Partially Averaged Navier-Stokes(PANS)model,the filter width is mainly controlled by the ratio of unresolved-to-total kinetic energy1f.This model is assessed in unsteady cavitating flows over a Clark-Y hydrofoil.From the experimental validations regarding the forces,frequencies,cavity visualizations and velocity distributions,the PANS model is shown to improve the predictive capability considerably,in comparison to the standard k-ε model,and also,it is observed the value of1f in the PANS model has substantial influence on the predicting result.As the filter width1f is decreased,the PANS model can effectively reduce the eddy viscosity near the closure region which can significantly influence the capture of the detach cavity,and this model can reproduce the time-averaged velocity quantitatively around the hydrofoil.
In the present study, firstly, the unsteady cavitating flows around a hydrofoil are studied based on the flow visualization and detail velocity measurement, a high-speed video camera is used to visualize the flow structures, and a particle image velocimetry (PIV) technique is applied to the measurement of the time-averaged and instantaneous velocity and vorticity fields. The results show that the unsteadiness of mass transfer process between the vapor and the two-phase regions is substantial, a self-oscillatory behavior of the whole sheet cavitation is obtained, with large length fluctuations and vapor cloud shedding, and also the cavitation structure depends on the interaction of the water-vapor mixture and the periodic vortex shedding. The main purpose of this experimental study is to offer information for validating computational models, and shed light on the unsteady multiphase transport process of cavitating flows. Furthermore, with an emphasis on the dynamics of the attached turbulent cavitating flows, a filter-based model (FBM) is derived from the ktwo-equation model, a conditional averaging method aimed at improving unsteady simulation is applied to computation. In comparison to the standard kmodel, overall, the filter-based model is shown to improve the predictive capability considerably.
