Water cavitation from ambient to high temperatures

Francesco Magaletti, Mirko Gallo, Carlo Massimo Casciola

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Predicting cavitation has proved a formidable task, particularly for water. Despite the experimental difficulty of controlling the sample purity, there is nowadays substantial consensus on the remarkable tensile strength of water, on the order of −120 MPa at ambient conditions. Recent progress significantly advanced our predictive capability which, however, still considerably depends on elaborate fitting procedures based on the input of external data. Here a self-contained model is discussed which is shown able to accurately reproduce cavitation data for water over the most extended range of temperatures for which accurate experiments are available. The computations are based on a diffuse interface model which, as only inputs, requires a reliable equation of state for the bulk free energy and the interfacial tension. A rare event technique, namely the string method, is used to evaluate the free-energy barrier as the base for determining the nucleation rate and the cavitation pressure. The data allow discussing the role of the Tolman length in determining the nucleation barrier, confirming that, when the size of the cavitation nuclei exceed the thickness of the interfacial layer, the Tolman correction effectively improves the predictions of the plain Classical Nucleation Theory.

Original languageEnglish
Article number20801
Pages (from-to)20801
JournalScientific Reports
Issue number1
Publication statusPublished - 21 Oct 2021

Bibliographical note

Funding Information:
F. M. wants to acknowledge the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. [836693] for fundings. He also acknowledges that the results of this research have been achieved using the DECI resource EAGLE hosted by PSNC (Poland) with support from the PRACE aisbl. Generous computer resources on Marconi 100 CINECA obtained in the context of the PRACE call 20 project BIMI are kindly acknowledged. The work of M.G. was partially supported by Sapienza through the project ASSEMBLE.

Publisher Copyright:
© 2021, The Author(s).


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