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A numerical approach for fluid deformable surfaces

Published online by Cambridge University Press:  12 August 2020

S. Reuther
Affiliation:
Department of Mathematics, Technische Universität Dresden, 01062Dresden, Germany
I. Nitschke
Affiliation:
Department of Mathematics, Technische Universität Dresden, 01062Dresden, Germany
A. Voigt*
Affiliation:
Department of Mathematics, Technische Universität Dresden, 01062Dresden, Germany Center of Systems Biology Dresden (CSBD), Pfotenhauerstr. 108, 01307Dresden, Germany Cluster of Excellence Physics of Life (PoL), Tatzberg 47/49, 01307Dresden, Germany
*
Email address for correspondence: axel.voigt@tu-dresden.de

Abstract

Fluid deformable surfaces show a solid–fluid duality which establishes a tight interplay between tangential flow and surface deformation. We derive the governing equations as a thin film limit and provide a general numerical approach for their solution. The simulation results demonstrate the rich dynamics resulting from this interplay, where, in the presence of curvature, any shape change is accompanied by a tangential flow and, vice versa, the surface deforms due to tangential flow. However, they also show that the only possible stable stationary state in the considered setting is a sphere with zero velocity.

Information

Type
JFM Rapids
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2020. Published by Cambridge University Press
Figure 0

Figure 1. (a) Relaxation of a perturbed sphere for $t = 0$, $0.25$, $0.5$, $0.75$, $1$, $1.25$, $1.75$, $2$, $2.5$, $7.5$ (left to right, top to bottom); the tangential flow field is visualized by line integral convolution (LIC). Tangent, normal and overall kinetic energy $E_{{T}} := (\int _\mathcal {S}\langle \boldsymbol {v},\boldsymbol {v}\rangle \,\text {d}\mathcal {S})/{2}$, $E_{{N}} := (\int _\mathcal {S}\mathcal {V}^2\,\text {d}\mathcal {S})/{2}$ and $E_{{T}}+E_{{N}}$, respectively, against time $t$ (b) and tangent kinetic energy $E_{{T}}$ against normal kinetic energy $E_{{N}}$ (c).

Figure 1

Figure 2. Deviation from a sphere $\sigma _{{S}}$ against time $t$ for different Reynolds numbers ${Re}$ (a,b) and Bending capillary numbers ${Be}$ (c,d) for the perturbed sphere simulation (a,c) and power spectrum of the normalized deviation from a sphere $\sigma _{{S}} / \langle \sigma _{{S}}\rangle$ (b,d) with $\langle \sigma _{{S}}\rangle$ the time average of $\sigma _{{S}}$. Pure Helfrich flow is shown for comparison as a dashed line and is indicated as ‘no flow’.

Figure 2

Figure 3. (a) Relaxation of Killing vector field for $t = 0$, $1.5$, $3.5$, $15$, $20$ (left to right); the tangential flow field is visualized by LIC. (b,c) Contour plot of the sliced geometry in the time interval $[0,10]$ with ascending grey scale indicating increasing time (b) and plot of the $x$-/$y$-coordinate of the geometry against time $t$ (c). (d,e) Experimental order of convergence (EOC) for different mesh sizes $h$ and time step widths $\tau$ with a constant ratio $h^2/\tau$ and the measure of the error $e := \|\textrm{div}_{\!\mathcal {S}}\boldsymbol {v} - \mathcal {V}\mathcal {H}\|_2$ (d). Deviation from a sphere $\sigma _{{S}}$ against time $t$ with $\sigma _{{S}} := \int _{\mathcal {S}}(\mathcal {H} - \mathcal {H}_{{S}})^2\,\text {d}\mathcal {S}$ and $\mathcal {H}_{{S}}$ the mean curvature of a sphere with equal surface area for different mesh sizes $h$ (e).

Figure 3

Figure 4. Deviation from a sphere $\sigma _{{S}}$ against time $t$ for different Reynolds numbers ${Re}$ (a,b) and Bending capillary numbers ${Be}$ (c,d) for the Killing vector field relaxation (a,c) and power spectrum of the normalized deviation from a sphere $\sigma _{{S}} / \langle \sigma _{{S}}\rangle$ (b,d) with $\langle \sigma _{{S}}\rangle$ the time average of $\sigma _{{S}}$.