A data assimilation method for analysis of cavitation bubble dynamics

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Here, we present a novel state-observer data-assimilation technique designed to fuse time-resolved cavitation bubble diameter measurements with a governing model to yield enhanced Spatio-temporal prediction of the cavitation bubble dynamics.

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Version 1.0 - published on 13 Apr 2021 doi:10.4231/0YAM-9T87 - cite this Archived on 14 May 2021

Licensed under CC0 1.0 Universal

Cavitation Bubble Timeseries.png GA.png

Description

The data provided in this publication was used to introduce a novel data assimilation-based technique to model the cavitation bubble dynamics (See https://rdcu.be/cip12).

The original or modified Rayleigh Plesset equation (RPE) is often used to analyze cavitation bubble dynamics. The prediction accuracy of these equations is governed by the initial values of the physical parameters. However, even for higher fidelity models, deviations from experimental measurements are observed due to the models' underlying assumptions. Here, we present a novel state-observer data-assimilation technique designed to fuse time-resolved cavitation bubble diameter measurements with a governing model to yield enhanced Spatio-temporal prediction of the cavitation bubble dynamics. This technique places an observer variable in the original or modified RPE and uses a proportional-integral-derivative (PID) control law on the difference between the predicted and measured cavitation bubble diameter. The data-assimilated modeling most accurately estimates the bubble diameter and far-field pressure as the deviation of bubble diameter and far-field pressure predictions from measurements decrease by up to 90% and 60%, respectively. Although the assimilated model is not a substitute for high fidelity models, this technique overcomes the inherent model assumptions and makes the model’s outputs more robust with respect to the physical parameters' initial values.  

 

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