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Markus Hundshagen, Michael Mansour, Dominique Thévenin, Romuald Skoda

• An assessment of a two-fluid model assuming a continuous liquid and a dispersed gas phase for 3D computational fluid dynamics (CFD) simulations of gas/liquid flow in a centrifugal research pump is performed. A monodisperse two-fluid model, in conjunction with a statistical eddy-viscosity turbulence model, is utilized. By a comprehensive measurement database, a thorough assessment of model inaccuracies is enabled. The results on a horizontal diffuser flow reveal that the turbulence model is one main limitation of simulation accuracy for gas/liquid flows. Regarding pump flows, distinctions of single-phase and two-phase flow in a closed and semi-open impeller are figured out. Even single-phase flow simulations reveal challenging requirements on a high spatial resolution, e.g., of the rounded blade trailing edge and the tip clearance gap flow. In two-phase pump operation, gas accumulations lead to coherent gas pockets that are predicted partly at wrong locations within the blade channel. At best, a qualitative prediction of gas accumulations and the head drop towards increasing inlet gas volume fractions (\(\it IGVF\)) can be obtained. One main limitation of two-fluid methods for pump flow is figured out in terms of the violation of the dilute, disperse phase assumption due to locally high disperse phase loading within coherent gas accumulations. In these circumstances, bubble population models do not appear beneficial compared to a monodisperse bubble distribution. Volume-of-Fluid (VOF) methods may be utilized to capture the phase interface at large accumulated gas cavities, requiring a high spatial resolution. Thus, a hybrid model, i.e., a dispersed phase two-fluid model including polydispersity for flow regions with a dilute gas phase, should be combined with an interphase capturing model, e.g., in terms of VOF. This hybrid model, together with scale-resolving turbulence models, seems to be indispensable for a quantitative two-phase pump performance prediction.