Modelling of Laminar-to-Turbulent Flow Transition on a Marine Propeller Using a RANS Solver

Traditionally, predicting propeller performance is based on model-scale experiments carried out in towing tanks or cavitation tunnels. These results are then extrapolated to full-scale using methods, such as the 1978 ITTC (International Towing Tank Conference) performance prediction method. However, this approach might not accurately account for new propeller configurations and Reynolds number effects.
While the flow around marine propellers at full-scale is presumed to be fully turbulent, at modelscale a combination of laminar, transitional, and turbulent flow patterns may occur simultaneously. These different flow regimes can be inferred from propeller paint-tests. In addition, the ITTC have encouraged exploring Computational Fluid Dynamics to address scaling problems. Therefore, paint-tests are used alongside Reynolds-averaged Navier-Stokes (RANS) solvers for performance prediction and scale-effect quantification.
The goal of the present study is to improve the accuracy of the propeller performance prediction at model-scale using a RANS solver. The analysis is carried out for propeller S6368, for which blade surface flow visualisation from paint-test photos are available at model-scale, Boorsma (2000). Recently, new paint-tests were conducted at MARIN and are included in the present study, Kerkvliet et al. (2022). Two RANS-based turbulence models are selected: the k −ω SST turbulence model, Menter et al. (2003), where flow transition is taken care implicitly by the model, and the ɣ-Re_θ turbulent-transition model, Langtry and Menter (2009), which solves additional transport equations.
Several numerical studies are presented in this paper, which includes an estimation of the numerical errors in the simulations, an evaluation of the influence of inlet turbulence quantities on the transition location, identification of the flow regime, and an analysis of the predicted propeller blade boundary-layer flow. Finally, a comparison between the RANS simulations and experimental data is made, which will help to improve the propeller flow modelling at model-scale. This comparison will help in the definition of more realistic inlet turbulence quantities that may be used for numerical predictions at model-scale without the need of any type of calibration based on experimental information.