Freschi, RosaBakogianni, AgapiRajendran, David JohnAnselmi Palma, EduardoTalluri, LorenzoRoumeliotis, Ioannis2023-02-082023-02-082023-02-03Freschi R, Bakogianni A, Rajendran DJ, et al., (2023) Flow field explorations in a boundary layer pump rotor for improving 1D design codes, Designs, Volume 7, Issue 1, February 2023, Article number 292411-9660https://doi.org/10.3390/designs7010029https://dspace.lib.cranfield.ac.uk/handle/1826/19147Boundary layer pumps, although attractive due to their compactness, robustness and multi-fluid and phase-handling capability, have been reported to have low experimental efficiencies despite optimistic predictions from analytical models. A lower-order flow-physics-based analytical model that can be used as a 1D design code for sizing and predicting pump performance is described. The rotor component is modelled by means of the Navier–Stokes equations as simplified using velocity profiles in the inter-disk gap, while the volute is modelled using kinetic-energy-based coefficients inspired by centrifugal pumps. The code can predict the rotor outlet and overall pump pressure ratio with an around 3% and 10% average error, respectively, compared to the reference experimental data for a water pump. Moreover, 3D RANS flow-field explorations of the rotor are carried out for different inter-disk gaps to provide insights concerning the improvement of the 1D design code for the better prediction of the overall pump performance. Improvements in volute loss modelling through the inclusion of realistic flow properties at the rotor outlet rather than the detailed resolution of the velocity profiles within the rotor are suggested as guidelines for improved predictions. Such improved design codes could close the gap between predictions and experimental values, thereby paving the way for the appropriate sizing of boundary layer pumps for several applications, including aircraft thermal management.enAttribution 4.0 Internationalboundary layer pumpsdesign codeNavier–Stokesvelocity profilesvolute loss modelling3D RANSinflectionArticle