Resolving parameter uncertainties in non-spherical bubble dynamics: a measurement simulation comparison study

A widely cited experimental dataset (Cleve et al. , J. Fluid Mech. , 2019, vol. 875, pp. 597–621) on non-spherical acoustic cavitation dynamics provides a valuable benchmark for model validation, yet its use is hindered by large uncertainties in the two key parameters: the equilibrium bubble radius and the acoustic pressure amplitude. This study introduces a robust parameter-identification framework to resolve these discrepancies and enable meaningful comparison with models. Using an in-house graphics processing unit-accelerated solver for solving the second-order perturbation model developed by Shaw ( Phys. Fluids , 2006, vol. 18, issue 7, p. 072104), the dataset is systematically re-examined. A Fourier coefficient-based error metric is developed to quantify the pronounced mismatch between simulations and measurements. The proposed method reliably corrects the vast majority of the experimental parameters, yielding excellent agreement between numerical predictions and observations. The outcome is a validated dataset with accurately identified parameters that can serve as a reliable benchmark for validating advanced computational fluid dynamics simulations and theoretical models. In addition, the approach offers a general tool for future experiments where direct measurements of local acoustic pressure remain difficult.

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Publication Details

Journal
Journal of Fluid Mechanics
Published
2026-09-08
DOI
https://doi.org/10.1017/jfm.2026.12003
Primary Topic
Ultrasound and Cavitation Phenomena
Type
article
Field-Weighted Citation Impact
0.00

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article

Resolving parameter uncertainties in non-spherical bubble dynamics: a measurement simulation comparison study

Cyril Mauger, Benjámin Csippa, Kálmán Klapcsik, Robert Mettin et al.
Journal of Fluid Mechanics
Ultrasound and Cavitation Phenomena
article

Resolving parameter uncertainties in non-spherical bubble dynamics: a measurement simulation comparison study

Cyril Mauger, Benjámin Csippa, Kálmán Klapcsik, Robert Mettin, Claude Inserra, Christiane Lechner, Stephen Shaw, Péter Kalmár, Ferenc Kubicsek, Péter Tamás Nagy, Matti Tervo, Max Koch, Ferenc Hegedus, Dániel Nagy
article en

Abstract

A widely cited experimental dataset (Cleve et al. , J. Fluid Mech. , 2019, vol. 875, pp. 597–621) on non-spherical acoustic cavitation dynamics provides a valuable benchmark for model validation, yet its use is hindered by large uncertainties in the two key parameters: the equilibrium bubble radius and the acoustic pressure amplitude. This study introduces a robust parameter-identification framework to resolve these discrepancies and enable meaningful comparison with models. Using an in-house graphics processing unit-accelerated solver for solving the second-order perturbation model developed by Shaw ( Phys. Fluids , 2006, vol. 18, issue 7, p. 072104), the dataset is systematically re-examined. A Fourier coefficient-based error metric is developed to quantify the pronounced mismatch between simulations and measurements. The proposed method reliably corrects the vast majority of the experimental parameters, yielding excellent agreement between numerical predictions and observations. The outcome is a validated dataset with accurately identified parameters that can serve as a reliable benchmark for validating advanced computational fluid dynamics simulations and theoretical models. In addition, the approach offers a general tool for future experiments where direct measurements of local acoustic pressure remain difficult.

Journal of Fluid MechanicsVol. 1042
Université Claude Bernard Lyon 1 (FR), Centre National de la Recherche Scientifique (FR), TU Wien (AT), Inserm (FR), Lyon College (US), Budapest University of Technology and Economics (HU), Centre Léon Bérard (FR), Laboratoire de Mécanique des Fluides et d'Acoustique (FR), Institut National des Sciences Appliquées de Lyon (FR), Xi’an Jiaotong-Liverpool University (CN), University of Göttingen (DE)
Austrian Science Fund
Openalex Percentile: Top 24%
Ultrasound and Cavitation Phenomena
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