کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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5406437 | 1393174 | 2011 | 5 صفحه PDF | دانلود رایگان |

Magnetic Resonance (MR) imaging is difficult to apply to multi-phase flows due to both the inherently short T2â 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 (â¼2%), before being applied to a system where the gas fraction is too high for optical measurements (â¼15%).
Photograph of a bubble swarm and comparison of the corresponding magnetic resonance and optical measurements of the bubble size distribution.147Research highlights⺠Bayesian approach developed to characterise image features directly in k-Space. ⺠Enables measurements of transient systems that could not be studied conventionally. ⺠Approach validated by numerical simulations. ⺠Demonstrated experimentally on bubble sizing in a gas-liquid flow. ⺠Applicable to low magnetic field and poor signal-to-noise ratio systems.
Journal: Journal of Magnetic Resonance - Volume 209, Issue 1, March 2011, Pages 83-87