Drops In Turbulent Flow Research Articles

Interface topology and evolution of particle patterns on deformable drops in turbulence

The capture of neutrally buoyant, sub-Kolmogorov particles at the interface of deformable drops in turbulent flow and the subsequent evolution of particle surface distribution are investigated. Direct numerical simulation of turbulence, phase-field modelling of the drop interface dynamics and Lagrangian particle tracking are used. Particle distribution is obtained considering excluded-volume interactions, i.e. by enforcing particle collisions. Particles are initially dispersed in the carrier flow and are driven in time towards the surface of the drops by jet-like turbulent fluid motions. Once captured by the interfacial forces, particles disperse on the surface. Excluded-volume interactions bring particles into long-term trapping regions where the average surface velocity divergence sampled by the particles is zero. These regions correlate well with portions of the interface characterized by higher-than-mean curvature, indicating that modifications of the surface tension induced by the presence of very small particles will be stronger in the highly convex regions of the interface.

Particle capture by drops in turbulent flow

Three-phase turbulent flows are crucial in a number of practical problems involving particulate abatement, from scavenging of air pollutants by precipitation to scrubbing processes. These flows are extremely rich in physics and challenging to simulate. Through direct numerical simulations of turbulence, coupled with a phase field interface description and Lagrangian particle tracking, the capture dynamics of small solid particles by large deformable drops is examined in detail. The role of the topologically changing drop interface in connection with the local turbulence structure is highlighted, and a simple transport model for predicting capture efficiency is derived.

Direct Numerical Simulations of Flows with Phase Change

Direct Numerical Simulations (DNS) of multiphase flows, where every continuum length and time scale are fully resolved, currently allow us to simulate flows of considerable complexity, such as the motion of several hundred bubbles or drops in turbulent flows, for sufficiently long time so that meaningful statistical quantities can be obtained. Additional physical processes such as heat transfer and phase change have also been included, although only for relatively small systems so far. After reviewing briefly recent studies of bubbles in turbulent channel flows, we discuss simulations of flows with phase change, focusing on bubble generation by boiling. The addition of new physics often results in new length and time scales that are shorter and faster than the dominant flow scales. Similarly, very small features such as thin films, filaments, and drops can also arise during coalescence and breakup of fluid blobs. The geometry of these features is usually simple, since surface tension effects are strong and inertia effects are relatively small and in isolation these features are often well described by analytical or semi-analytical models. Recent efforts to embed analytical and semi-analytical models to capture such features, in combination with direct numerical simulations of the rest of the flow, are discussed. We conclude by a short discussion of the use of DNS data for closure laws for model equations for the large scale flow.

Estimation of the maximum stable drop sizes, coalescence frequencies and the size distributions in isotropic turbulent dispersions

The process of coalescence or breakup of drops in turbulent flow is of importance in many technical applications. A new size distribution takes place due to the coalescence or the breakup of the drops during the motion of a dispersed system. Based on the experimental data given in the literature, some new empirical relationships are developed in this paper to evaluate the maximum stable drop sizes, the coalescence frequencies and the drop size distribution in an isotropic turbulent flow. The relationships are developed essentially in terms of the particle Reynolds number or of the physical properties of the system. The Focker–Planck equation is used to estimate the particle size distribution. The model predictions are compared with the experimental data given in the literature. The results indicated that the predicted values and the experimental data are in a good agreement.

A numerical technique for the solution of integrodifferential equations arising from balances over populations of drops in turbulent flows

This paper describes a numerical technique designed to solve certain forms of partial differential equations. The method is applied to the partial integrodifferential population balance equations presented by Jairazbhoy [Jairazbhoy, V., Tavlarides, L. L., & Lewalle, J., (1995) A cascade model for neutrally buoyant two-phase homogeneous turbulence – part I. Model formulation. International Journal of Multiphase Flow, 21(3), 467] that describe the behavior of dense liquid dispersions of interacting drops in isotropic turbulence. In the successively contained semi-discretization scheme developed, the drop number density functions are discretized into non-uniform intervals corresponding to Gaussian quadrature points. The governing equations are assumed to hold identically at all the discretization points, generating a set of ordinary integrodifferential equations that are solved by an integrator package. The integrals in each function evaluation are calculated by Gaussian quadrature. The results show that, in some cases, as many as fifteen quadrature points are required to achieve grid independence. Each additional discretization point results in an additional ordinary integrodifferential equation. To achieve comparable accuracy with a uniform discretization scheme, many more discretization points would be required, resulting in an inordinately large number of ordinary integrodifferential equations. The computations also show that, in every run, there appears to be an optimum number of discretization intervals around which incremental increases in the resolution do not increase the CPU time or perceivable accuracy of the solution.

Breakage of a drop of inviscid fluid due to a pressure fluctuation at its surface

In this work, an attempt is made to gain a better understanding of the breakage of low-viscosity drops in turbulent flows by determining the dynamics of deformation of an inviscid drop in response to a pressure variation acting on the drop surface. Known scaling relationships between wavenumbers and frequencies, and between pressure fluctuations and velocity fluctuations in the inertial subrange are used in characterizing the pressure fluctuation. The existence of a maximum stable drop diameterdmaxfollows once scaling laws of turbulent flow are used to correlate the magnitude of the disruptive forces with the duration for which they act.Two undetermined dimensionless quantities, both of order unity, appear in the equations of continuity, motion, and the boundary conditions in terms of pressure fluctuations applied on the surface. One is a constant of proportionality relating root-mean-square values of pressure and velocity differences between two points separated by a distancel. The other is a Weber number based on turbulent stresses acting on the drop and the resisting stresses in the drop due to interfacial tension. The former is set equal to 1, and the latter is determined by studying the interaction of a drop of diameter equal todmaxwith a pressure fluctuation of length scale equal to the drop diameter. The model is then used to study the breakage of drops of diameter greater thandmaxand those with densities different from that of the suspending fluid.It is found that, at least during breakage of a drop of diameter greater thandmaxby interaction with a fluctuation of equal length scale, a satellite drop is always formed between two larger drops. When very large drops are broken by smaller-length-scale fluctuations, highly deformed shapes are produced suggesting the possibility of further fragmentation due to instabilities. The model predicts that as the dispersed-phase density increases,dmaxdecreases.