2022
DOI: 10.1063/5.0120801
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Inertial migration of soft particles initially evenly spaced along the flow direction in a channel

Abstract: The inertial migration of two-dimensional soft particles initially distributed uniformly in channel flow is numerically studied by employing an immersed-boundary lattice Boltzmann method coupled with a finite element method. To model a soft particle, a capsule with an elastic membrane separating the liquid inside from the outside is used. Validation tests show excellent agreement with previous numerical results of other researchers. Then the effects of the number of capsules $N_p$, the bending stiffness $E_b$,… Show more

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Cited by 12 publications
(2 citation statements)
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“…Feng et al [164] showed that the formation of trains in dilute suspensions depends on particle concentration, Reynolds number, and particle softness. Huang et al [170] further demonstrated that, once the line fraction was too large for more particles to enter the train, additional particles were likely to locate close to the channel centre, moving at a larger axial velocity than particles in the train.…”
Section: Particle Suspensionsmentioning
confidence: 99%
“…Feng et al [164] showed that the formation of trains in dilute suspensions depends on particle concentration, Reynolds number, and particle softness. Huang et al [170] further demonstrated that, once the line fraction was too large for more particles to enter the train, additional particles were likely to locate close to the channel centre, moving at a larger axial velocity than particles in the train.…”
Section: Particle Suspensionsmentioning
confidence: 99%
“…The behavior of solid particles in fluids is complex and diverse, which makes their simulation challenging. Numerous numerical simulation methods have been developed to simulate particle two-phase flows, including finite element method (FEM) (Kees et al 2022), finite difference method (Antonopoulou et al 2018), finite volume method (FVM) (Zhang 2020), lattice Boltzmann method (LBM) (Nie and Lin 2020, Huang et al 2022, Afra et al 2022a, 2022b, as well as their combinations (Huang et al 2019). Additionally, particle-based methods (Luo et al 2021, Zhang et al 2021b have been proposed as mesh-free alternatives.…”
Section: Introductionmentioning
confidence: 99%