Abstract
The objective of the present investigation is the numerical prediction of the potential of a flow to inflict surface damage by cavitation. For this purpose, physical criteria are derived that detect and quantify relevant flow phenomena. In particular, we present a numerical approach for tracing isolated collapses of vapor clouds during the numerical simulation of the flow. The suggested “collapse detector” provides the frequency of collapses, their positions, and resulting maximum pressures, as well as the maximum condensation rate of each event. This data, together with the maximum wall pressure, allow for an automatic indication of erosion-sensitive areas.
The employed flow solver CATUM (CAvitation Technische Universität München) is a density-based 3-D finite volume method equipped with a Low-Mach-number consistent flux function. All fluid components (liquid, vapor, saturated mixture) are modeled by closed form equations of state.
To assess this novel approach we simulate an experimentally investigated nozzle-target flow. A comparison of numerically predicted collapse events with the experimentally observed areas of cavitation erosion substantiates the proposed methodology. The obtained data represents a time-history of collapse events together with their position and strength, and may be used to estimate erosion rates.
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Acknowledgements
We would like to thank Jean-Pierre Franc for providing detailed information on his experimental setup as well as for fruitful discussions and suggestions. All computational resources have been provided by the Leibniz Supercomputing Center.
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Mihatsch, M.S., Schmidt, S.J., Thalhamer, M., Adams, N.A. (2013). Numerical Prediction of Erosive Collapse Events in Unsteady Compressible Cavitating Flows. In: Eça, L., Oñate, E., García-Espinosa, J., Kvamsdal, T., Bergan, P. (eds) MARINE 2011, IV International Conference on Computational Methods in Marine Engineering. Computational Methods in Applied Sciences, vol 29. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6143-8_11
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DOI: https://doi.org/10.1007/978-94-007-6143-8_11
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