A study on the numerical prediction of cavitation erosion for propellers

Usta, Onur and Aktas, Batuhan and Maasch, Matthias and Turan, Osman and Atlar, Mehmet and Korkut, Emin; Sánchez-Caja, Antonio, ed. (2017) A study on the numerical prediction of cavitation erosion for propellers. In: Proceedings of the Fifth International Symposium on Marine Propulsors - SMP'17 12 - 15 June 2017, Espoo, Finland. VTT Technical Research Center of Finland Ltd, FIN. ISBN 978-951-38-8606-6

[thumbnail of Usta-etal-SMP-2017-A-study-on-the-numerical-prediction-of-cavitation-erosion]
Preview
Text. Filename: Usta_etal_SMP_2017_A_study_on_the_numerical_prediction_of_cavitation_erosion.pdf
Accepted Author Manuscript

Download (1MB)| Preview

Abstract

This paper presents a numerical study on the prediction of performance, cavitation and erosion characteristics of King's College-D (KCD)-193 model propeller in different flow conditions. The present work is achieved by using unsteady Detached Eddy Simulation (DES) turbulence model in a Computational Fluid Dynamics (CFD) software STAR-CCM+. Cavitation is modelled by Schnerr-Sauer cavitation model with Reboud correction. Flow velocity and flow turbulent intensity, derived from Laser Doppler Anemometry (LDA) measurements conducted at the Emerson Cavitation Tunnel for the KCD-193 propeller, are applied as numerical boundary fields for the inlet of the cavitation tunnel domain to reflect the experimental flow conditions. Cavitation erosion is modelled by three different approaches using pressure, saturation pressure, volume fraction of vapour, time derivative of the pressure and time derivative of the volume fraction of vapour on the propeller blades obtained from simulations. A new approach to predict cavitation erosion intensity on the propeller blade is proposed. The preliminary results of the study are compared with the experimental results carried out at Emerson Cavitation Tunnel of Newcastle University. Qualitative cavitation extent and erosion comparisons are made for different conditions. Computation results are in good agreement with those of experiments.