Steady cavitating propeller performance by using OpenFOAM, StarCCM plus and a boundary element method

Accurate and reliable numerical predictions of propeller performance are a fundamental aspect for any analysis and design of a modern propeller. Prediction of cavitation and of cavity extension is another important task, since cavitation is one of the crucial aspects that influences efficiency in addition to propagated noise and blade vibration and erosion. The validation of the numerical tools that support the design process, including open-source codes, is, consequently, essential. The public availability of measurements and observations which cover not only usual thrust and torque in open water conditions (including cavitation) but also unsteady functioning with pressure pulse measurements in the case of the Potsdam Propeller Test Case certainly represents an extremely useful source of information and an excellent chance for verification and validation purposes. In the present work, the prediction of the Potsdam Propeller Test Case propeller performance using the OpenFOAM computational fluid dynamics package is proposed. After a preliminary validation and calibration of the OpenFOAM native Schnerr-Sauer interphase mass transfer model for cavitating flow, based on the experimental results on a 2D NACA66Mod hydrofoil, open water propeller performance and cavitation predictions are carried out. The OpenFOAM results are finally compared both with the available experimental measurements and with calculations carried out with StarCCM+ and with a proprietary boundary element method code, in order to assess the accuracy and the overall capabilities of the open-source tools (from meshing to post-processing) available in the OpenFOAM package. The comparison, in addition to assessing the accuracy of the open-source approach, is aimed to verify its advantages and drawbacks with respect to widely used solvers and to further verify the reliability of traditional boundary element method approaches that are still widely adopted for design and optimization (thanks to their extremely higher computational efficiency) in a very demanding test case.