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Soft streaming – flow rectification via elastic boundaries

Published online by Cambridge University Press:  14 July 2022

Yashraj Bhosale
Affiliation:
Mechanical Sciences and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
Tejaswin Parthasarathy
Affiliation:
Mechanical Sciences and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
Mattia Gazzola*
Affiliation:
Mechanical Sciences and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA Center for Artificial Intelligence Innovation, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
*
†Email address for correspondence: mgazzola@illinois.edu

Abstract

Viscous streaming is an efficient mechanism to exploit inertia at the microscale for flow control. While streaming from rigid features has been thoroughly investigated, when body compliance is involved, as in biological settings, little is known. Here, we investigate body elasticity effects on streaming in the minimal case of an immersed soft cylinder. Our study reveals an additional streaming process, available even in Stokes flows. Paving the way for advanced forms of flow manipulation, we illustrate how gained insights may translate to complex geometries beyond circular cylinders.

Information

Type
JFM Rapids
Copyright
© The Author(s), 2022. Published by Cambridge University Press
Figure 0

Figure 1. Problem set-up. Elastic solid cylinder $\varOmega _e$ of radius $a$ with a rigid inclusion (pinned zone $\varGamma$ of radius $b$), immersed in the viscous fluid $\varOmega _f$. The cylinder is exposed to an oscillatory flow with far-field velocity $V(t) = \epsilon a \omega \cos (\omega t)$.

Figure 1

Figure 2. Effect of elasticity on streaming flow. (a–c) Time-averaged Lagrangian (i.e. Stokes-drift corrected – see supplementary material, § 3 for details) streamline patterns (blue/orange represent clockwise/anticlockwise rotating regions) depicting streaming response at $M \approx 8$ with increasing softness $\mathrm {Cau}$: (a) rigid limit ($\mathrm {Cau} = 0$), (b) $\mathrm {Cau} = 0.025$ and (c) $\mathrm {Cau} = 0.05$. Non-dimensional radius of the pinned zone (green cylinder) is set at $\zeta = 0.2$ throughout the study. For effects of $\zeta$ variation on streaming, refer to supplementary material, § 5. (d) Normalized DC layer thickness $\delta _{DC} / a$ vs inverse of Womersley number ($1 / M$) from theory and simulations, for varying body elasticity $\mathrm {Cau}$. The DC layer is the innermost recirculation zone (a–c). Its extent (finite or infinite thickness) and flow velocities characterize streaming. Its robust nature and high flow gradients and curvatures render the DC layer useful for trapping, filtration or chemical mixing. (e–g) Radial decay of velocity magnitude along $\theta = 0^{\circ }$ from theory and simulations, with increasing softness $\mathrm {Cau}$. Experimental parameter values equivalent to the range of $M$ and $\mathrm {Cau}$ considered here can be found in supplementary material, § 6, revealing practical viability in association with soft tissue or common polymeric materials. Simulations are performed using a remeshed vortex methodology (Gazzola et al.2011; Bhosale, Parthasarathy & Gazzola 2021a) that accurately solves the vorticity–velocity formulation of the Navier–Stokes equations. The flow domain is discretized as particles for vorticity advection. The vorticity carried by particles is then interpolated on a regular mesh for the evaluation of all other terms. Within this framework, the rigid cylinder is modelled as a density matched ($\rho _f = \rho _e = 1$) Brinkmann solid, while the elastic cylinder is modelled as a density matched viscoelastic Kelvin–Voigt solid with shear modulus $G$. Deformations are tracked using an inverse-map technique (Kamrin & Nave 2009; Kamrin, Rycroft & Nave 2012). The pinned zone is modelled as a Brinkmann solid. The parametric values for the far-field motion $V(t) = V_0 \cos \omega t$ with characteristic velocity $V_0 = \epsilon a \omega$, are $\epsilon = 0.1$ and $\omega = 32 {\rm \pi}$. Parametric values of fluid dynamic viscosity $\mu _f$, oscillation frequency $\omega$ and shear modulus $G$ are determined based on the Womersley number $M = a \sqrt {\rho _f \omega / \mu _f}$, and Cauchy number $\mathrm {Cau} = \epsilon \rho _f a^{2} \omega ^{2} / G$. Additional simulation details: domain $[0, 1]^{2}$, uniform grid spacing $h=1 / 1024$, penalization factor $\lambda = 1\times 10^{4}$, mollification length $\epsilon _{moll} = 2 \sqrt {2} h$, Lagrangian Courant–Friedrichs–Lewy number LCFL = $0.1$. These values are used throughout the text, unless stated otherwise. Refer to Gazzola et al. (2011) and Bhosale et al. (2021a) for details on these parameters.

Figure 2

Figure 3. Extension of compliance-induced streaming to generalised, multiple curvature bodies. Time-averaged Eulerian flow topologies obtained from simulations for a bullet – formed by hybridizing a circle of radius $a$ with a square of side length $2a$ – at $M \approx 8$, with varying body elasticity $\mathrm {Cau}$: (a) rigid limit $\mathrm {Cau} = 0$, (b) $\mathrm {Cau} = 0.05$ and (c) $\mathrm {Cau} = 0.1$. Increasing body softness results in contraction and strengthening of the rear DC vortex on the square side, consistent with our theoretical insights.

Supplementary material: PDF

Bhosale et al. supplementary material

Supplementary data

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