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Updated: Jun 4, 2026

Quantifying Mixing using Magnetic Resonance Imaging
Published on: January 25, 2012
A Bayesian approach to characterising multi-phase flows using magnetic resonance: application to bubble flows
D J Holland1, A Blake, A B Tayler
1Department of Chemical Engineering and Biotechnology, University of Cambridge, Pembroke Street, Cambridge CB2 3RA, United Kingdom. djh79@cam.ac.uk
Abstract:
Magnetic Resonance (MR) imaging is difficult to apply to multi-phase flows due to both the inherently short T₂* characterising such systems and the relatively long time taken to acquire the data. We develop a Bayesian MR approach for analysing data in k-space that eliminates the need for image acquisition, thereby significantly extending the range of systems that can be studied. We demonstrate the technique by measuring bubble size distributions in gas-liquid flows. The MR approach is compared with an optical technique at a low gas fraction (∼2%), before being applied to a system where the gas fraction is too high for optical measurements (∼15%).
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