An improved calibration methodology and uncertainty assessment in measurements of microbubble size and concentration

R. Stigter; D. Fiscaletti; G. E. Elsinga; T. van Terwisga; J. Westerweel

doi:10.1007/s00348-024-03929-3

An improved calibration methodology and uncertainty assessment in measurements of microbubble size and concentration

R. Stigter^*, D. Fiscaletti, G. E. Elsinga, T. van Terwisga, J. Westerweel

^*Corresponding author for this work

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Abstract

Interferometric particle imaging (IPI) is used to measure both the size distribution and concentration of microbubbles (with a diameter less than 100 micron) in water. Using a new method for calibration makes it possible to obtain quantitative results for the concentration of microbubbles. The results are validated using imaging with a long-range microscope shadowgraph (LMS). Estimates of the size distribution and concentration from both IPI and LMS agree within uncertainty limits. The relative uncertainty in the IPI concentration estimation is about 10% and is mostly due to the finite number of detected bubbles. It is shown that the performance of the bubble-image detection algorithm needs to be quantified to obtain a reliable estimate of the concentration obtained with IPI.

Original language	English
Article number	14
Number of pages	17
Journal	Experiments in Fluids
Volume	66
Issue number	1
DOIs	https://doi.org/10.1007/s00348-024-03929-3
Publication status	Published - 2025

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10.1007/s00348-024-03929-3

s00348-024-03929-3Final published version, 33.5 MBLicence: CC BY

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AU - Westerweel, J.

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AB - Interferometric particle imaging (IPI) is used to measure both the size distribution and concentration of microbubbles (with a diameter less than 100 micron) in water. Using a new method for calibration makes it possible to obtain quantitative results for the concentration of microbubbles. The results are validated using imaging with a long-range microscope shadowgraph (LMS). Estimates of the size distribution and concentration from both IPI and LMS agree within uncertainty limits. The relative uncertainty in the IPI concentration estimation is about 10% and is mostly due to the finite number of detected bubbles. It is shown that the performance of the bubble-image detection algorithm needs to be quantified to obtain a reliable estimate of the concentration obtained with IPI.

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An improved calibration methodology and uncertainty assessment in measurements of microbubble size and concentration

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