On the influence of rotational motion on MRI velocimetry of granular flows – Theoretical predictions and comparison to experimental data

Clarke, Daniel; Fabich, Hilary T.; Brox, Timothy I.; Galvosas, Petrik; Holland, Daniel J.

doi:10.1016/j.jmr.2019.106569

Cited by 5 publications

(1 citation statement)

References 46 publications

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“…This approach has the potential to increase the accuracy of k-space simulation and therefore improve the accuracy of the MRI simulations. Additionally, a recent work by Clarke et al 50 has shown that rotation motion of particles can lead to substantial signal attenuation and, hence, to an amplified velocity variance. In the present work, we did not take into account the effect of rotational motion on the MRI measurements.…”

Section: Discussionmentioning

confidence: 99%

Computer Simulation of Magnetic Resonance Imaging of the Flow of Fluidized Particles

Bordbar

Benders

Zia

et al. 2023

Ind. Eng. Chem. Res.

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Rapid magnetic resonance imaging (MRI) and velocimetry (MRV) are non-invasive measurement techniques in 3D opaque systems with ∼10 ms temporal resolution, enabling new opportunities to challenge the accuracy of computational models of flow. Comparisons between rapid MRI/MRV and computer simulations are limited by (i) artifacts in rapid MRI techniques and (ii) non-trivial aspects of post-processing of computer simulation data to best match the measurement techniques. Here, we address these issues by starting with data from computer flow simulations of fluidized particles and feeding the data to a physics-based simulation of MRV measurements, which captures potential artifacts introduced by the measurement techniques. Flow simulation data is then post-processed in various ways, demonstrating that (1) velocity and particle position data must be taken from flow simulations at different points in time to match MRV measurements and (2) imaging must be faster than flow fluctuation for MRV to produce effectively instantaneous velocity fields.

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Section: Discussionmentioning

confidence: 99%