Cavitation Noise Spectra Prediction with Hybrid Models

  • Francesca CipolliniEmail author
  • Fabiana MigliantiEmail author
  • Luca OnetoEmail author
  • Giorgio TaniEmail author
  • Michele VivianiEmail author
  • Davide AnguitaEmail author
Conference paper
Part of the Proceedings of the International Neural Networks Society book series (INNS, volume 1)


In many real world applications the physical knowledge of a phenomenon and data science can be combined together in order to get mutual benefits. As a result, it is possible to formulate a so-called hybrid model from the combination of the two approaches. In this work, we propose an hybrid approach for the prediction of the ship propeller cavitating vortex noise, adopting real data collected during extensive model scale tests in a cavitation tunnel. Results will show the effectiveness of the proposal.


Cavitation noise prediction Physical models Data-Driven Models Hybrid Models 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.DIBRIS - University of GenoaGenovaItaly
  2. 2.DITEN - University of GenoaGenovaItaly

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