The Cahn-Hilliard-Navier-Stokes Framework for Multiphase Fluid Flows: Laminar, Turbulent, and Active

Abstract

The Cahn-Hilliard-Navier-Stokes (CHNS) framework has found extensive applications, across diverse length and time scales, for multi-phase flows. In this thesis, we demonstrate that this framework offers a robust theoretical foundation for probing diverse aspects of fluid dynamics in binary- and ternary-fluid mixtures and active fluids. A summary of the main results of our studies is given below, along with the Chapters in which we present these.

In Chapter 1, we lay the foundation for our exploration of complex multiphase flows by providing essential background information related to the problems discussed in this thesis. This includes: (a) a brief historical perspective on mult-iphase interfaces; (b) an exploration of the statistical mechanics of interfaces; (c) a comprehensive overview of various models, such as binary CHNS, ternary CHNS, active CHNS, and volume-penalized CHNS models; (d) a detailed explanation of the numerical techniques that we use to solve the coupled CHNS equations; and (e) analysis and validation of numerical studies of CHNS models.

In Chapter 2, we demonstrate the existence of an emergent nonequilibrium statistically steady state (NESS) with spatiotemporal chaos, which is induced by interfacial fluctuations in low-Reynolds-number binary-fluid mixtures, where we start with a cellular flow. We uncover the properties of this NESS via direct numerical simulations (DNSs) of the coupled Cahn-Hilliard-Navier-Stokes (CHNS) equations for binary fluids. We show that, in this NESS, the shell-averaged energy spectrum $E(k)$ is spread over several decades in the wavenumber $k$ and it exhibits a power-law region, indicative of turbulence \textit{but without a conventional inertial cascade}. To characterize the statistical properties of this turbulence, we compute, in addition to $E(k)$, the time series $e(t)$ of the kinetic energy and its power spectrum, scale-by-scale energy transfer as a function of $k$, and the energy dissipation resulting from interfacial stresses. Furthermore, we analyze the mixing properties of this low-Reynolds-number turbulence by using Lagrangian statistics, such as the mean-square displacement (MSD) of tracer particles. Our results demonstrate diffusive behaviour at long times, a hallmark of strong mixing that is similar to its inertial-turbulence counterpart.

In Chapter 3, we investigate the role of interfaces as transport barriers in CHNS turbulence by employing Lagrangian tracer particles in such turbulence. The Cahn-Hilliard-Navier-Stokes (CHNS) system of partial differential equations provides a natural theoretical framework for our investigations. For specificity, we utilize the two-dimensional (2D) CHNS system. We capture efficiently interface and their fluctuations in 2D binary-fluid turbulence by using extensive pseudospectral direct numerical simulations (DNSs) of the 2D CHNS equations. We begin with $n$ tracers within a droplet of one phase and examine their dispersal into the second phase. The tracers remain within the droplet for a long time before emerging from it, so interfaces act as transport barriers in binary-fluid turbulence. We show that the fraction of the number of particles inside the droplet decays exponentially and is characterized by a decay time $\tau_{\xi}\sim R_0^{3/2}$ that increases with $R_0$, the radius of the initially circular droplet. Furthermore, we demonstrate that the average first-passage time $\langle \tau \rangle$ for tracers inside a droplet is orders of magnitude larger than it is for transport out of a hypothetical circle with the same radius as the initially circular droplet. We examine the roles of the Okubo-Weiss parameter $\Lambda$, the fluctuations of the droplet perimeter, and the probability distribution function of $\cos(\theta)$, with $\theta$ the angle between the fluid velocity and the normal to droplet interface, in trapping tracers inside droplets. We mention possible generalisations of our study.

In Chapter 4, we demonstrate that the three-phase Cahn-Hilliard-Navier-Stokes (CHNS3) system provides a natural theoretical framework for studying liquid-lens coalescence, which has been investigated in recent experiments. Our extensive direct numerical simulations (DNSs) of lens coalescence, in the two and three dimensional (2D and 3D) CHNS3, uncover the rich spatiotemporal evolution of the fluid velocity $\bm u$ and vorticity $\bm \omega$, the concentration fields $c_1, \, c_2,$ and $c_3$ of the three liquids, and a generalized Laplace pressure $P^G_\mathcal{L}$, which we define in terms of these concentrations via a Poisson equation. We find, in agreement with experiments, that as the lenses coalesce, their neck height $h(t) \sim t^{\alpha_v}$, with $\alpha_v \simeq 1$ in the viscous regime, and $h(t) \sim t^{\alpha_i}$, with $\alpha_i \simeq 2/3$ in the inertial regime. We obtain the crossover from the viscous to the inertial regimes as a function of the Ohnesorge number $Oh$, a dimensionless combination of viscous stresses and inertial and surface tension forces. We show that a vortex quadrupole, which straddles the neck of the merging lenses, and $P^G_\mathcal{L}$ play crucial roles in distinguishing between the viscous- and inertial-regime growths of the merging lenses. In the inertial regime we find signatures of turbulence, which we quantify via kinetic-energy and concentration spectra. Finally, we examine the merger of asymmetric lenses, in which the initial stages of coalescence occur along the circular parts of the lens interfaces; in this case, we obtain power-law forms for the $h(t)$ with inertial-regime exponents that lie between their droplet-coalescence and lens-merger counterparts.

In Chapter 5, we elucidate the statistical properties of activity-induced homogeneous and isotropic turbulence in a model that has been employed to investigate motility-induced phase separation (MIPS) in a system of microswimmers. The active Cahn-Hilliard-Navier-Stokes equations (CHNS), or the active model H, provides a natural theoretical framework for our study. In this CHNS model, a single scalar order parameter $\phi$, positive (negative) in regions of high (low) microswimmer density, is coupled with the velocity field $\bm u$. The activity of the microswimmers is governed by an activity parameter $\zeta$ that is positive for \textit{extensile} swimmers and negative for \textit{contractile} swimmers. With extensile swimmers, this system undergoes complete phase separation, which is similar to that in binary-fluid mixtures. By carrying out pseudospectral direct numerical simulations (DNSs), we show that this model (a) develops an emergent nonequilibrium, but statistically steady, state (NESS) of active turbulence, for the case of contractile swimmers, if $\zeta$ is sufficiently large and negative and (b) this turbulence arrests the phase separation. We quantify this suppression by showing how the coarsening-arrest length scale does not grow indefinitely, with time $t$, but saturates at a finite value at large times. We characterise the statistical properties of this active-scalar turbulence by employing energy spectra and fluxes and the spectrum of $\phi$. For sufficiently high Reynolds number, the energy spectrum $\mathcal E(k)$ displays an inertial range, with a power-law dependence on the wavenumber $k$. We demonstrate that, in this range, the flux $\Pi(k)$ assumes an approximately constant, negative value, which indicates that the system shows an inverse cascade of energy, even though energy injection occurs over a wide range of wavenumbers in our active-CHNS model.

In Chapter 6, we elucidate the crucial role that confinement plays in collective and emergent behaviors in active- or living-matter systems by developing a minimal hydrodynamic model, without an orientational order parameter, for assemblies of contractile swimmers encapsulated in a droplet of a binary-fluid emulsion. Our model uses two coupled scalar order parameters, $\phi$ and $\psi$, which capture, respectively, the droplet interface and the activity of the contractile swimmers inside this droplet. These order parameters are also coupled to the velocity field $\bm u$. At low activity, our model yields a self-propelling droplet whose center of mass $(CM)$ displays rectilinear motion, powered by the spatiotemporal evolution of the field $\psi$, which leads to a time-dependent vortex dipole at one end of the droplet. As we increase the activity, this $CM$ shows chaotic super-diffusive motion, which we characterize by its mean-square displacement; and the droplet interface exhibits multifractal fluctuations, whose spectrum of exponents we calculate. We explore the implications of our results for experiments on active droplets of contractile swimmers.