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Deformation of drops by outer eddies in turbulence

Published online by Cambridge University Press:  28 October 2021

Alberto Vela-Martín*
Affiliation:
Centre of Applied Space Technology and Microgravity (ZARM), University of Bremen, Bremen, 28359 GermanySchool of Aeronautics, Universidad Politécnica de Madrid, Madrid, 28040 Spain
Marc Avila
Affiliation:
Centre of Applied Space Technology and Microgravity (ZARM), University of Bremen, Bremen, 28359 Germany
*
†Email address for correspondence: albertovelam@gmail.com

Abstract

Drop deformation in fluid flows is investigated as an exchange between the kinetic energy of the fluid and the surface energy of the drop. We show analytically that this energetic exchange is controlled only by the stretching (or compression) of the drop surface by the rate-of-strain tensor. This mechanism is analogous to the stretching of the vorticity field in turbulence. By leveraging the non-local nature of turbulence dynamics, we introduce a new decomposition that isolates the energetic exchange arising from local drop-induced surface effects from the non-local action of turbulent fluctuations. We perform direct numerical simulations of single inertial drops in isotropic turbulence and show that an important contribution to the increments of the surface energy arises from the non-local stretching of the fluid–fluid interface by eddies far from the drop surface (outer eddies). We report that this mechanism is dominant and independent of surface dynamics in a range of Weber numbers in which drop breakup occurs. These findings shed new light on drop deformation and breakup in turbulent flows, and opens the possibility for the improvement and simplification of breakup models.

Information

Type
JFM Papers
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 (https://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), 2021. Published by Cambridge University Press
Figure 0

Figure 1.(a,b) Schematic representation of the mechanism that generates positive (a) and negative (b) increments of the surface energy owing to the compression or stretching of the interface between two immiscible liquids, where $\boldsymbol n$ is the orthogonal vector normal to the interface, $\boldsymbol t^1$ and $\boldsymbol t^2$ are vectors parallel to the surface, and $\vartheta =-\sigma n_i S_{ij} n_j$. Blue and green arrows indicate the compressive and stretching directions of the rate-of-strain tensor at the surface, and dotted lines are the streamlines of the velocity field with respect to the surface.

Figure 1

Figure 2.Temporal evolution of a drop at ${We}=1.8$. The frame is fixed at the centre of the drop and the time of the snapshots corresponds, from left to right, to $t/t_d=2.0$, $2.9$, $4.8$ and $5.1$. Blue isosurfaces denote vorticity with magnitude $|\boldsymbol \omega |=2.6\langle |\boldsymbol \omega |\rangle$, where the brackets denote the ensemble average. The size of the computational box is marked in Kolmogorov units.

Figure 2

Figure 3.(a) Median time to breakup as a function of the $We$. The upper and lower bars mark plus-minus the standard deviation. The style of the markers is only used for ease of reference for the data shown in the following panels. (b) Average kinetic energy spectra at $Re_\lambda =58$ for turbulent flow without droplet (dashed line); ${We}=1.8$ (magenta circles); ${We}=5.4$ (blue squares). Vertical dotted lines mark the scale (wavenumber) of the drop, $k_d=2{\rm \pi} /d$, the scale where the spectral density of the kinetic energy dissipation is the highest, $k_\varepsilon$, and the scale of the interface, $k_\delta =2{\rm \pi} /\delta$. The spectra are averaged across the flow fields in the database. (c) Pre-multiplied production spectra, $k\eta \varPhi (k)$. Lines as in panel (b). The total contribution of each wavenumber to the variation of the surface free energy is represented as the area below the curve. Here, $\varPhi$ is normalised with its average in each case.

Figure 3

Figure 4.(a) Decomposition of the rate-of-strain tensor in contributions arising from eddies a distance $\varDelta$ from the drop surface, denoted as $S^O_{ij}$, and a distance $\varDelta$ close to the surface (including the inside of the drop), denoted as $S^I_{ij}$. Here $\boldsymbol x_s$ marks the drop surface. Magnitude of the outer (b) and inner (c) rate-of-strain tensor, $2S^O_{ij}S^O_{ij}$ and $2S^I_{ij}S^I_{ij}$, in a direct numerical simulation for $\varDelta =0.19d$ and $We=5.4$. The solid red line marks the drop surface and the dashed magenta line a distance $\varDelta =0.19d$ from the surface. In panel (b), the outer rate-of-strain tensor at a distance smaller than $\varDelta =0.19d$ from the drop surface has been multiplied by $10$ to ease visualisation. Axes in Kolmogorov units.

Figure 4

Figure 5.(a,b) Correlation coefficient, $\mathcal {C}$, between the stretching by inner eddies, $\vartheta ^I$, and outer eddies, $\vartheta ^O$, as a function of $\varDelta$ (a) and $We$ (b).

Figure 5

Figure 6.Probability density function of the local surface stretching arising from the full flow, $\vartheta$, (a), the inner eddies, $\vartheta ^I$, (b) and the outer eddies, $\vartheta ^O$, (c) for $\varDelta =0.12d$ and at $We=$: solid magenta line, 1.8; dashed blue line, 5.4. Quantities are plotted without the mean and divided by their standard deviation.

Figure 6

Figure 7.(a) Mean, (b) standard deviation, (c) skewness and (d) excess flatness of $\vartheta$ as a function of $We$. Mean and standard deviation are normalised by $\rho u_d^3$, where $u_d=d/t_d$. Solid symbols correspond to the statistics of $\vartheta ^O$ and empty symbols to $\vartheta ^I$. Colour lines correspond to $\varDelta =$: solid, $0.12d$; dashed, $0.19d$; and solid black line to the full rate-of-strain tensor. In panel (b), the dotted line is proportional to $We^{-1}$.

Figure 7

Figure 8.(a–c) Probability density function of $\cos \theta _i=\boldsymbol n \boldsymbol {\cdot }\boldsymbol v_i$, where $\boldsymbol v_i$ are the principal directions of the rate of strain tensor and $\lambda _1\le \lambda _2\le \lambda _3$ are their eigenvalues. Solid markers correspond to angles calculated with $S^{O}_{ij}$ and empty markers to $S^{I}_{ij}$, for $\varDelta =0.19d$. (d) Similar but for the vorticity vector, $\cos \theta _\omega =\boldsymbol n \boldsymbol {\cdot }\boldsymbol \omega /|\boldsymbol \omega |$. Lines correspond to ${We}=$: solid, $1.8$; dashed, $3.6$; dash–dotted, $5.4$. The vertical dotted line in panels (a,c) marks $\cos {\rm \pi}/4$.

Figure 8

Figure 9.(a,b) Average surface stretching owing to each eigenvalue of the rate-of-strain tensor, $p_i=\sigma \lambda _i\sin ^2\theta _i$, as a function of the Weber number for the inner (a) and the outer (b) contributions, for $\varDelta =0.19d$. The surface stretching is normalised by $\rho u_d^3$. (c) Surface average of the square of the inner rate-of-strain tensor, $2S^I_{ij}S^I_{ij}$, for $\varDelta =0.19d\eta$, and the vorticity vector $\omega _i\omega _i$ for different Weber numbers, normalised with Kolmogorov units. (d) Probability distribution function of $\varLambda =\log _2 |\lambda _1|/\lambda _3$ for different Weber numbers.

Figure 9

Figure 10.Comparison of the analytical solution of $\Delta r/\epsilon$ for a drop with ${Oh}=0.013$ with a numerical simulation with a Cahn–Hilliard–Navier–Stokes (CHNS) code.