Flow of bioartificial capsules in microchannels

Barthès-Biesel, Dominique; Leclerc, Éric; Lefebvre, Y.; Walter, J.

doi:10.1016/s0021-9290(06)84313-7

Cited by 1 publication

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“…The resulting model was employed to analyse the effects of cell distribution upon the overall effective viscosity in a circular tube. Further studies of two-phase flows in biomechanics have included the works of Eloot et al (2002) who examined dialysis systems, Luo et al (2007) who considered contaminant dispersion in respiratory flow, Barthès-Biesel et al (2006) who studied microchannel capsule transport and Hashmi (2008) who considered particle deformability in the circulatory system. Wu et al (2009) investigated bacterial separation from erythrocytes and Filletti and Seleghim (2010) developed a neural network model for acoustic wave transmission in dispersed fluid-particle suspension flows with applications in the human cochlear system.…”

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confidence: 99%

Differential transform semi-numerical analysis of biofluid-particle suspension flow and heat transfer in non-Darcian porous media

Bég¹,

Rashidi

Bég

et al. 2013

Computer Methods in Biomechanics and Biomedical Engineering

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The differential transform method (DTM) is semi-numerical method which is used to study the steady, laminar buoyancy-driven convection heat transfer of a particulate biofluid suspension in a channel containing a porous material. A two-phase continuum model is used. A set of variables is implemented to reduce the ordinary differential equations for momentum and energy conservation (for both phases) to a dimensionless system. DTM solutions are obtained for the dimensionless system under appropriate boundary conditions. We examine the influence of momentum inverse Stokes number (Skm), Darcy number (Da), Forchheimer number (Fs), particle loading parameter (pL), particle-phase wall slip parameter (Ω) and buoyancy parameter (B) on the fluid-phase velocity (U) and particle-phase velocity (Up). Padé approximants are also employed to achieve satisfaction of boundary conditions. Excellent correlation is obtained between the DTM and numerical quadrature solutions. The results indicate that there is a strong decrease in fluid-phase velocities with increasing Darcian (first-order) drag and the second-order Forchheimer drag, and a weaker reduction in particle-phase velocity field. Fluid and particle-phase velocities are also strongly affected with inverse momentum Stokes number. DTM is shown to be a powerful tool providing engineers with an alternative simulation approach to other traditional methods for multi-phase computational biofluid mechanics. The model finds applications in haemotological separation and biotechnological processing.

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