Identification of the precessing vortex core in a hydro turbine model using local stability analysis and stochastic modeling

Abstract Stochastic modeling and local linear stability analysis (LSA) is employed to predict the onset of precessing vortex core (PVC) in hydro turbine model. The method stochastic based on pressure fluctuation signals correctly predicts instability azimuthal mode m = 1 at flow rates below 0 . 7 Q c This line with LSA that shows modes 2 are absolutely unstable rate absolute a new observation part load regimes turbines plays significant role dynamics PVC. As demonstrated this paper, modelling both methods uncover driver PVC using sparse experimental data stemming from either spatially resolved but non-timeresolved PIV snapshots or single-point time-resolved wall recordings, respectively. makes these suitable be applied configurations industrial relevance.