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Quantifying silo flow using MRI velocimetry for testing granular flow models

Abstract : In this work we present experimental results of the gravity-driven discharge of poppy seeds from 3D-printed silos. The velocity fields of the flowing poppy seeds are measured using Magnetic Resonance Imaging (MRI) velocimetry techniques. Crucially, this approach allows the velocity field to be determined throughout the flow domain, unlike visual techniques such as Particle Image Velocimetry (PIV) and related methods where only the flow at or near the wall is accessible. We perform the experiment three times; with 3D-printed silos of cone half angles 30∘ and 50∘ respectively, and then repeat the 30∘ silo experiment, but with a layer of poppy seeds glued to the silo wall to create a ``rough wall" condition. In our experiments, we observe and quantify velocity fields for three well known granular flow regimes; mass flow, funnel flow, and rat-holing. The results of the experiments are compared to equivalent output of numerical simulations. In this mathematical model, the well-known μ(I) friction law is used to define an effective granular viscosity, and the flow is solved using a standard Navier-Stokes type solver. While the results are generally encouraging, it is noted that some aspects of the model are lacking and should be improved; in particular, the rat-holing effect observed in one of the MRI experiments was not predicted by the model, nor was the exact volumetric flow rate from any of the silos. Suggestions for model improvement are discussed.
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Submitted on : Tuesday, June 25, 2019 - 9:36:50 AM
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  • HAL Id : hal-02164393, version 1

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Luke Fullard, Daniel Holland, Petrik Galvosas, Clive Davies, Pierre-Yves Lagrée, et al.. Quantifying silo flow using MRI velocimetry for testing granular flow models. Physical Review Fluids, American Physical Society, 2019. ⟨hal-02164393⟩

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