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Issue 48, 2017
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Viscoelastic flow past mono- and bidisperse random arrays of cylinders: flow resistance, topology and normal stress distribution

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Abstract

We investigate creeping viscoelastic fluid flow through two-dimensional porous media consisting of random arrangements of monodisperse and bidisperse cylinders, using our finite volume-immersed boundary method introduced in S. De, et al., J. Non-Newtonian Fluid Mech., 2016, 232, 67–76. The viscoelastic fluid is modeled with a FENE-P model. The simulations show an increased flow resistance with increase in flow rate, even though the bulk response of the fluid to shear flow is shear thinning. We show that if the square root of the permeability is chosen as the characteristic length scale in the determination of the dimensionless Deborah number (De), then all flow resistance curves collapse to a single master curve, irrespective of the pore geometry. Our study reveals how viscoelastic stresses and flow topologies (rotation, shear and extension) are distributed through the porous media, and how they evolve with increasing De. We correlate the local viscoelastic first normal stress differences with the local flow topology and show that the largest normal stress differences are located in shear flow dominated regions and not in extensional flow dominated regions at higher viscoelasticity. The study shows that normal stress differences in shear flow regions may play a crucial role in the increase of flow resistance for viscoelastic flow through such porous media.

Graphical abstract: Viscoelastic flow past mono- and bidisperse random arrays of cylinders: flow resistance, topology and normal stress distribution

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Publication details

The article was received on 08 Sep 2017, accepted on 24 Nov 2017 and first published on 27 Nov 2017


Article type: Paper
DOI: 10.1039/C7SM01818E
Citation: Soft Matter, 2017,13, 9138-9146
  • Open access: Creative Commons BY license
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    Viscoelastic flow past mono- and bidisperse random arrays of cylinders: flow resistance, topology and normal stress distribution

    S. De, J. A. M. Kuipers, E. A. J. F. Peters and J. T. Padding, Soft Matter, 2017, 13, 9138
    DOI: 10.1039/C7SM01818E

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