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Direct Numerical Simulation of Liquid Films with LargeInterfacial Deformation†

By J.-C. Nave, X. D. Liu, and S. Banerjee

Liquid films are important in many industrial applications, but also from afundamental point of view, they are important two-phase flow systems. In thispaper, we develop a sharp interface/level set method for the Direct NumericalSimulation (DNS) of liquid films with large interfacial deformations, and largedensity ratio between the liquid and the gas phase. We use the ghost fluidmethod to capture the interface motion without smoothing properties across it,and adopt a maximization scheme for the implicit treatment of the viscousterm in the Navier–Stokes equations. Because liquid films have very lowaverage depth compared to the distance between waves, several innovations arerequired to handle solving the equations on grid structures of high aspect ratio.Two-dimensional (2D) calculations for wavy films falling down a vertical wallare presented, and good agreement is found when numerical solutions aredirectly compared with the experiments of Nosoko et al. [1]. Some results arealso presented for falling liquid films transitioning naturally from 2D to 3Dsurface wave structures demonstrating the potential of the method for 3D fullycoupled two-phase liquid films simulations.

1. Introduction

The overall focus of the present work is to develop a method for directlysimulating two-phase flows, that is capable of handling large interfacial

Address for correspondence: J.-C. Nave, Department of Mathematics, Massachusetts Institute ofTechnology, 77 Massachusetts Avenue 2-363A, Cambridge, MA 02139, USA; e-mail: [email protected]†Dedicated to the memory of Xu Dong, our friend and colleague.

DOI: 10.1111/j.1467-9590.2009.00479.x 153STUDIES IN APPLIED MATHEMATICS 125:153–177C© 2010 by the Massachusetts Institute of Technology

154 J.-C. Nave et al.

Figure 1. Effect of smeared interface formulation for an elongated grid. This figure is colouronline.

deformations, and allows changes in interfacial topology, for example, wavebreaking and/or droplet detachment. Also, the approach must be able to treatlarge surface tensions and large density ratios while maintaining a “sharp”interface. Liquid films have in general a large aspect ratio, thus requiring longcomputational domains. Consequently, we investigate whether simulating asmall number of wave lengths (allowing for higher resolution) using periodicboundary conditions accurately predicts film statistics such as those presentedin [1]. To these ends, we chose to use the finite difference method on a MarkerAnd Cell (MAC) grid which allowed us to benefit substantially from the workof previous investigators [2–5].

Specifically, the simulation of falling liquid films is a particularly demandingproblem; typically, falling liquid films have large aspect ratio. The ratio ofthe wavelength to the average film thickness may be 100 or more. Asidefrom the resolution requirements associated with simulations on high aspectratio domains, the waves may present relatively steep fronts (see Figure 1).Consequently, any numerical method must be able to accurately capture theinterface in both the wall-normal direction as well as in the flow direction.These requirements imply that traditional simulation techniques must usesquare (or slightly elongated) meshes. This results in large problems that areoften too demanding for current computational capabilities. For a typical filmflow simulation with 100 grid points in the wall-normal direction, and a domainsize of four wave lengths, the simulation would require 100 × 20000 × 20000

Direct Numerical Simulation of Liquid Films with Large Interfacial Deformation 155

(roughly cubical) grid points, which is out of reach of common computersystems. As a result, most simulation must be conducted on grids withlarge aspect ratios, where �y ≈ �z ≈ 100�x for a 100:1 aspect ratiofilm.

With a finite-difference approach, several methods used for the simulationof two-phase flows assume a smeared interface representation. The smearedinterface approach [6], refers to approximating the discontinuous quantities(fluid densities, viscosities) with their smooth analogs typically over a distance�ε = 3 max(�x, �y, �z). While this approach is valid and accurate in mostphysical situations for which grids with aspect ratios near unity are adequate,using an elongated grid of aspect ratioγ = max(�x, �y, �z)/min(�x, �y, �z)would translate into smearing the interface over up to �ε · γ grid points in atleast one direction. The interface smearing leads to problems when the filmsurface is nearly vertical as is the case for the wave front in Figure 1; on thefront part of the wave, when the interface is nearly perpendicular to the wall,the smearing is performed over a distance larger by γ compared to the otherdirection. This effect introduces errors, and becomes problematic for the studyof processes where interface-local quantities are of interest such as heat transferand mass transfer.

Another approach [7] is to treat the interface as a contact surface,maintaining a “sharp” interface. This approach assumes piece-wise constantproperties (viscosity, density) on each domain and matches the two sides usingappropriate boundary conditions and locally 1D interpolation. This methodeliminates the issues associated with the smeared interface representation. Asa result, the need for resolution dictated by the interface region is reducedat the expense of a more complicated formulation. Additionally, solving forpressure through the variable coefficient Poisson equation, an elliptic problemwith jumps discontinuous interface conditions, becomes more involved assurface tension forces must be included as a pressure jumps rather than asmooth transition across the interface.

The problem associated with discretizing the equation for the pressure withinterfacial jump conditions was addressed in [8]. The approach for solvingthe Navier–Stokes equations in rectangular coordinates with two phases andincluding surface tension, was developed by Kang et al. [2] and was namedthe Ghost Fluid Method (GFM) in [7]. The method described in [2] is fullyexplicit, and did not consider accuracy for large aspect ratio grids, semi-implicittreatment of the viscous term, or turbulence. In the present work we addressthe first two issues, and motivate the appropriateness of the method for thefuture study of two-phase turbulence.

This paper is organized in the following way: in Section 2 we review thebackground on liquid films and previous numerical work, Section 3 presentsthe governing equations, and describes in detail the present scheme, inSection 4 we validate our approach by directly comparing our numerical results


with experiments, finally in Section 5 we summarize our main contribution,and provide an outlook toward possible future research.

2. Objectives and background

As mentioned earlier, the objective of this study is to develop a numericalmethod suitable for the study of a wide range of two-phase flows and validateit for liquid films that are either gravity, or gas driven. The numerical schemealso should be efficient, accurate, and able to handle arbitrarily large surfacetension forces, density ratios, and deformations of the interface. We will nowbriefly discuss previous work with somewhat similar goals that have been usedfor the simulation of free surface, or two-phase systems, in the context of theobjectives stated earlier.

The objectives outlined earlier are most closely met by [2]. Improvementsand validation to this approach are, however, necessary:

(1) Implicit treatment of the viscous term allowing us to remove the strongstability restriction on step size associated with the fully explicit schemespresented in [2]. This is especially important because wall-normalmesh spacing is typically one order of magnitude smaller than thestream-wise mesh spacing due to the nature of the problem.

(2) Validation of simulating liquid films systems using periodic boundaryconditions. The periodic treatment is necessary for the simulation ofturbulence, and to replace the spatially elongated systems that arerequired for inflow/outflow boundary conditions to obtain stationaryflow statistics.

One of the first numerical schemes developed for the simulation of freesurface flows is due to Harlow and Welch [9]. In their work, they used a MACgrid approach and a fractional step method later formalized by Chorin [10].With the increase in computational power, and the efficiency of the Fast FourierTransform (FFT), a number of schemes were developed to be able to simulatelarger problems, including turbulence. Many such schemes, referred to as“pseudo spectral methods” are referenced in [11]. For example, the problem offlat free surface turbulence has been extensively studied in [12], and [13].

For general two-phase flow computations, only a few methods can handlesurface tension forces and large density ratios. In the Volume of Fluid(VoF) method, Hirt and Nichols [14] use piecewise functions (often linear)to reconstruct the interface locally and determine the fraction of one phase,that is within a cell. This method has recently been applied to the simulationof 2D wavy falling liquid films with a free surface [15]. However, it onlycalculates the volume fraction occupied by each phase in an interfacial cell sothe shape of the interface has to be reconstructed. Another method uses a level


set function φ, to implicitly determine the position of the interface as its zerocontour. As a result, fluid properties such as viscosity and density are definedas a function of φ

μ(φ) =μ− + (μ+ − μ−)H (φ),

ρ(φ) = ρ− + (ρ+ − ρ−)H (φ), (1)

where H (φ) is a Heaviside function, and the “+” and “−” superscripts definethe two different phases, liquid and gas, respectively.

Surface tension forces are included using the Continuum Surface Force(CSF) model [16]. In this formulation, surface tension enters as a source termin the momentum equation and is located at the interface through the use of adelta function in φ,

δ(φ) ≡ d H

dφ. (2)

Because in the Eulerian framework, equations are discretized on a grid, thedelta function (2), and the Heaviside functions in (1) must be regularized toavoid O(0) discrete effects. Consequently, most studies suggest smearing (1),and (2) over a distance ε. As a result, and taking into account that the deltafunction should integrate to 1, we define

δε(φ) =

⎧⎪⎨⎪⎩

1

2ε

[1 + cos

(πφ

ε

)], |φ| ≤ ε,

0, |φ| > ε,

(3)

Hε(φ) =

⎧⎪⎪⎪⎪⎨⎪⎪⎪⎪⎩

0, φ < −ε,

1

2

[1 + φ

ε+ 1

πsin

(πφ

ε

)], |φ| ≤ ε,

1, φ > ε.

(4)

We can verify directly that,

∫ +∞

−∞δε(φ)dφ = 1. (5)

The method of using smeared quantities is appropriate in most situationswhere the aspect ratio of the physical problem is nearly one. However, asnoted earlier, this method is not adequate for the simulation of large aspectratio problems such as falling liquid films.


3. The level set/ghost fluid method approach

We now turn our attention to the sharp interface method for the simulation offalling liquid films, the Ghost Fluid Method (GFM) of Kang et al. [2] and Liuet al. [8].

Problems associated with the simulation of falling liquid films are demandingand constitute a good test of any proposed method. Specifically, the followingissues will be addressed in this section for the development of the numericalscheme.

First, falling liquid films have typically elongated aspect ratios; thewavelengths may be one hundred times the thickness of the film. This forces theuse of elongated meshes in the direction of the flow to make for a practicallytractable problem size. Typically, this translates into having an aspect ratio of10:1 for the mesh, which in turn gives roughly 10 times more grid points inthe streamwise direction compared to the wall normal direction. As an aside,such meshes elongated in the streamwise direction are also desirable for wallturbulence simulations as streamwise structures, such as quasi-streamwisevortices, are much longer than their extent in wall normal or spanwisedirections. Therefore, such elongated meshes are also necessary for the studyof turbulent liquid films—a subject of great practical interest. These twoadjustments can account for a wave length to film thickness ratio of ∼ 100 : 1which is observed in experimental studies [1]. Also, falling liquid films mayexhibit large curvatures and nearly vertical wave fronts we use the GFM for itscapacity to treat sharp interfaces, and to accurately model surface tension forcesat the sub-grid level. The GFM allows the interface to be defined to first-orderaccuracy independently of its local orientation with respect to the grid.

Second, for a film to reach statistically steady state conditions requires longsimulation domains if inflow/outflow boundary conditions are used [17]. As aresult, accurate simulations of large wavelength problems using inflow/outflowboundary condition are prohibitively expensive. To circumvent this problem wepropose to use periodic boundary conditions with an initial, spatial wavelengthdisturbance. In effect, the film develops as a transient problem in the periodicdomain, rather than over a long spatial domain with inflow/outflow boundaries.This is of course a very common procedure for turbulence simulations. Wewill verify the validity of this assumption in Section 4 in the context of fallingliquid films simulations.

Third, many problems of interest exhibit a wide range of scales in liquidfilms flows. For instance, the amplitude of capillary waves can be an order ofmagnitude smaller than that of a solitary wave. This observation requires usingsmall grid spacing to correctly capture the physics present at the capillarywave scale. As a result, the explicit treatment of viscosity in the GFM [2]imposes stability conditions on time step sizes that are too restrictive evenfor laminar problems of this nature. Note that this restriction occurs because


the scales present in the problem are small in the wall normal direction(capillary waves). In contrast to single phase homogeneous turbulence, forwhich in general an explicit treatment of the viscous term suffices, the need intwo-phase flows of resolving small interfacial features requires an implicitscheme for the viscous term. We propose an implicit treatment of viscositythrough a maximization approach similar to that of Badalassi et al. [18]. Thisapproach relaxes the restriction on the time step and allows us to performsimulations with higher spatial resolution at the same computational cost.

3.1. Problem setup and governing equations

The physical setup that must be addressed by the numerical scheme is shown inFigure 2. We use periodic boundary conditions in the y-direction, no slip walls inthe x-direction, and slip walls in the z-direction in all three-dimensional cases.The basic equations for an incompressible viscous fluid are the Navier–Stokesequations. In rectangular coordinates,

ρt + ∇ · (ρV ) = 0, (6)

ρ(Vt + (V · ∇)V ) = −∇ p + (∇ · τ )T + F, (7)

where “.T ” represents the transpose, F the body forces, τ = 12μ[∇V + (∇V )T ]

is the viscous stress tensor for incompressible viscous Newtonian fluid, andV = 〈u, v, w〉. The density ρ and the viscosity μ are both functions of φ, thesigned distance from the interface, and are defined in the following “sharp”manner,

ρ(φ) ={

ρliquid, φ > 0,

ρgas, φ ≤ 0,(8)

μ(φ) ={

μliquid, φ > 0,

μgas, φ ≤ 0.(9)

The level set function φ is obtained by solving the following equation

φt + V · ∇φ = 0. (10)

From φ, we can compute the normal and curvature

N = ∇φ

|∇φ| , (11)

κ = −∇ · N . (12)

Following the GFM formulation, we include surface tension forces as aninternal jump condition for the pressure.


Figure 2. Physical setup.

3.2. Numerical method

A staggered grid formulation is used to discretize the basic equations. Velocitycomponents are defined on cell faces, while the pressure, and level set functionare defined at the center of the control volume. The solver for the Navier–Stokesequation is an evolution of the scheme in [2]. We used a semi-implicittime marching method with a second-order Adams–Bashforth method for the


explicit terms and a maximization scheme for the implicit terms. A fractionalstep method, projection method [10] is used to solve the Navier–Stokesequation. The variable density and viscosity are treated “sharply” and jumpconditions are computed using sub-grid linear interpolation based on the levelset function φ. The discretized equations for conservation of momentum are

V n+1 − V n

�t=−∇ pn+1

ρ+ 3

2

[−(V · ∇)V + F

ρ− νmax

2M

]n

− 1

2

[−(V · ∇)V + F

ρ− νmax

2M

]n−1

+[

(∇ · τ )T

ρ

]n

+ νmax

2Mn+1, (13)

∇ · V n+1 = 0, (14)

where, M = �V and νmax = max(μgas

ρgas,

μliquid

ρliquid).

Using the projection method, we define the following fractional steps,

V � − V n

�t= 3

2

[−(V · ∇)V + F

ρ− νmax

2M

]n

− 1

2

[−(V · ∇)V + F

ρ− νmax

2M

]n−1

+[

(∇ · τ )T

ρ

]n

+ νmax

2M�, (15)

V n+1 − V �

�t+ ∇ pn+1

ρ= 0. (16)

Assuming that the velocity field at time level n + 1 is divergence-free (14),we derive the variable density pressure Poisson equation

∇ ·(∇ pn+1

ρ

)= ∇ · V �

�t. (17)

We assume no flow-through and no-slip conditions at solid wall boundaries,V · N = 0, and V × N = 0 respectively. The pressure boundary conditions atsolid wall boundaries are Neumann, ∇ p · N = 0.

In the GFM, the treatment of property discontinuities (density, viscosity) atthe interface requires jump conditions for the viscous term in the momentumequation (15), and in the Poisson equation (17). Following the notation in [2]


we denote the jump across the interface by [·], and we compute the matrix ofderivative jumps due to the discontinuity in viscosity,

⎛⎜⎝

[μux ] [μuy] [μuz]

[μvx ] [μvy] [μvz]

[μwx ] [μwy] [μwz]

⎞⎟⎠= [μ]

⎛⎜⎝

∇u

∇v

∇w

⎞⎟⎠

⎛⎜⎝

0

T1

T2

⎞⎟⎠

T ⎛⎜⎝

0

T1

T2

⎞⎟⎠

+ [μ]N T N

⎛⎜⎝

∇u

∇v

∇w

⎞⎟⎠ N T N

− [μ]

⎛⎜⎝

0

T1

T2

⎞⎟⎠

T ⎛⎜⎝

0

T1

T2

⎞⎟⎠

⎛⎜⎝

∇u

∇v

∇w

⎞⎟⎠

T

N T N , (18)

where T1 and T2 are the orthogonal and bi-orthogonal directions to the normalvector N . By knowing the values of the jumps across the interface, we canevaluate smoothly the individual derivatives on each side of the interface. Moredetails on the derivation and discretization of the explicit part of the viscousterm are available in [2].

The momentum equation can then be solved using an approximatefactorization technique. We use standard central differences for the Laplacianterms in (15), WENO fifth order for the convection term, and the techniquedeveloped in [2] and [19] for the discretization of the divergence of the rateof strain tensor, τ . For the solution of V �, we solve three tri-diagonal linearsystems, one per dimension. Additionally, the implicit treatment of the viscousterm by the maximization technique is intended to remove the O(�x2) stabilityrestriction on the time step �t .

Surface tension effects are incorporated into the equations as a jump inpressure across the interface. Thus, the jump condition for the pressure is

[p] − 2[μ](∇u · N , ∇v · N , ∇w · N ) · N = σκ, (19)

where σ is the surface tension, and is assumed to be constant in the present study.The interface is evolved using the level set equation (10) which is discretized

as

φn+1 − φn

�t+ V · ∇φn = 0, (20)

where WENO fifth order is used to approximate ∇φ.To preserve the level set function as a proper signed distance from the

interface (|∇φ| = 1), we use the reinitialization procedure with constraint from


Sussman and Fatermi [20]

φτ = sign(φ0)(1 − |∇φ|) + λ f (φ)

≡ L(φ0, φ) + λ f (φ), (21)

where φ0 is the level set function at pseudo-time τ = 0, and λ is given by

λ =

∫�

H ′(φ0)L(φ0, φ)∫�

H ′(φ0) f (φ0), (22)

and where, H (φ) is the Heaviside function, H ′(φ) = d H (φ)/dφ, andf (φ) = H ′(φ)|∇φ|.

Equation (21) with λ = 0 is the original reinitialization equation. We notethat the steady state of (21) with λ = 0 is |∇φ| = 1, the property we seek forthe level set function. However, numerical errors cause the zero-contour ofthe level set function to be displaced during this procedure, leading to theloss (gain) of mass. As a result, Sussman and Fatermi [20] introduced theintegrating factor λ, defined by (22) which represents a mass constraint forequation (21), thus guaranteeing that each cell domain � conserves the samemass throughout the procedure.

The integrations in (22) is performed using a second-order accurate Simpson’srule [21], over each individual grid cell � of the domain. Spatial derivatives in(21) are discretized using WENO fifth order, and the function is advanced intime using a third-order Runge–Kutta TVD scheme. Characteristics of (21) arenormal outward to the contour φ = 0, thus the integration is performed for afew steps in pseudo time, guaranteeing accuracy of the solution on a striparound the interface. Additional details about the solution of the level set andreinitialization equations are available in [20].

The variable coefficient Poisson equation (17) is solved with the interfacejump condition defined by (19). The discretization closely follows that describedin [8]. To compute curvature around the interface, we use sub-grid linearinterpolation

κI nt = θκRight + (1 − θ )κLeft, (23)

where θ is the cut cell defined by

θ = |φLeft||φLeft| + |φRight| . (24)

This discretization produces a linear system Ap = b to be solved. Becausethe matrix A is poorly conditioned, solving for pressure requires roughly 80%of the computational time. As a result, the solution method needs to be


Table 1Solution Scheme for 1 Time Step. (1 Euler Step, E(V ), is 1–4 Only)

1. Solve (15) for V �

2. Solve (17) for pn+1

3. Solve (16) for V n+1

4. Solve (20) for φn+1 (Advection)5. Solve (21) for φn+1 (Reinitialization)

complemented by a preconditioner in order to limit the number of iterationsrequired.

After investigating several iterative methods and preconditioners, we settledon the combination yielding the best robustness and efficiency for the simulationof liquid films. We use the BiCG-Stab iterative method from Van der Vorst[22] along with an Incomplete Upper-Lower (ILU) preconditioner. Note thatthe matrix A, produced from the discretization of the Poisson equation forthe pressure is symmetric; however, we chose BiCG-Stab, an iterative methodcapable of solving non-symmetric systems, foreseeing evolving the methodtoward the solution of problems with irregular wall boundaries possiblyresulting in nonsymmetric stencils.

Boundary conditions for most problems of interest in the present study havesolid walls in x and z directions and are periodic in the y direction. This resultsin a nonempty null space for A. We can therefore specify as an additionalconstraint that the sum of the residual be zero every time it is computed bysubtracting a constant cs

rnew = r − cs,

cs ≡ 1

n

n∑i=1

ri . (25)

This guarantees convergence of the iterative solution for the Poissonequation. The entire solution scheme (Table 1), corresponding to an Euler step,with the exception of the reinitialization is then embedded in the third-orderRunge–Kutta TVD scheme [23]

V n+1 = 1

3V n + 2

3E

{3

4V n + 1

4E[E(V n)]

}. (26)


3.3. Stability

The original Ghost Fluid Method used an explicit discretization for the viscousterm. We use a maximization scheme to relax the severe limitation imposed onthe time step �t when the mesh size is reduced. Kang et al. [2] showed thelimitation on the time step in the GFM to be

�t ≤(

Ccf l + Vcf l +√

(Ccf l + Vcf l)2 + 4G2c f l + 4S2

c f l

)−1

, (27)

with

Ccf l = max(|u|)�x

+ max(|v|)�y

+ max(|w|)�z

,

V Ecf l = max(v−, v+)

(2

�x2+ 2

�y2+ 2

�z2

),

Gcf l =√

|g|�y

,

Scf l =√

σ

min(ρ−, ρ+) min(�x, �y, �z)3. (28)

For the maximization scheme, Badalassi et al. [18] showed

V Mcf l =

[C

(max(μ−, μ+)

min(μ−, μ+)− 1

)−1

min(�x, �y, �z)

]−1

, (29)

where C is a constant.To demonstrate stability of the new scheme, we used a 2D laminar falling

liquid film problem at Re = 30 where surface tension has been chosen tobe low to remove the restriction imposed by Scf l in (28). We integrated theequations with different values of �x (mesh size), and chose for simplicity thesame grid spacing in the y-direction. The solution was computed until steadystate of the film or until numerical blowup due to violation of the stabilityconstraint was observed. For each �x , Figure 3 reports �tmax for both theexplicit scheme and the maximization scheme. The lines fitting the computedpoints are extrapolated to show the advantage of the maximization schemefor fine grid spacing. The extrapolation is based on the theoretical slopes forthe maximization and explicit schemes with the constant being determinedempirically from the data.

For the maximization approach used here, we observe proportionality to �xand not �x2, which is used for the explicit scheme data. We additionallychecked that the solution for critical time steps in both cases reach the samestatistically steady state wave profile and flow rates, that is, give essentially thesame results.


Figure 3. Critical stability comparison between the explicit GFM (black) and the maximizationscheme (blue). Note that a mesh size of 5e-6 corresponds to a 100 × 100 × 100 grid fortypical falling liquid film problems. This figure is colour online.

4. Validation

In this section, we focus on the simulation of vertically falling liquid films inthe wavy-laminar regime in two-dimensions. First, definitions and the casesstudied will be presented. Second, a quantitative study of the flow statisticswill be compared with experiments to serve as validation of our approach.

4.1. Numerical simulation and definitions

As stated earlier, the aspect ratio for these films is very large. As a result, weperformed our computation on a 2D grid of 50 × 250 mesh points for therange of Reynolds numbers from 30 to 100. The 50 × 250 grid was chosen toguarantee convergence of the results. Similar computations were performedusing inflow/outflow boundary conditions where inlet pressure is varied at agiven frequency [17]. In the present study, we use periodic boundary conditionswithout temporal forcing. To set the scale of the problem, we define λs as theinitial conditions for the wavelength of the solitary wave and Ns the number of


Table 2Computation Case Matrix

I II III IV V VI

Re 103 103 69 50 40 30N f · 10−12 0.41 0.052 0.2785 0.2018 0.1614 0.1614Nλ 994.9 994.9 826.8 742.6 689.4 689.4

Figure 4. Typical wave profile corresponding to statistically steady state for case II.

waves per computational domain of length L y . Here, λs is chosen so that itcorresponds to the steady-state solitary wave length observed in experiments.Also, the Reynolds number is defined based on the undisturbed film thicknessh0. We define the initial film thickness as

h(y) = h0 + ε sin

(2π Ns y

L y

), (30)


Figure 5. Typical wave profile corresponding to statistically steady state for case III.

where the initial disturbance ε � h0/100. The length of the periodic domain,Ly may have an influence on the accuracy of the solution if only one or twowaves were simulated in the domain, (Ns = 1, or Ns = 2) because the box sizeacts as a filter. As a result, choosing Ns = 4 for all of our two-dimensionalsimulations shows it eliminated this effect. The nondimensional groups for thisproblem are defined assuming the following scales for length 〈L〉 and velocity〈V 〉. The nomenclature is chosen here to allow for a direct comparison withthe results presented by Nosoko et al. [1]. Using their notation,

〈L〉 ≡(

v2

g

) 13

,

〈V 〉 ≡ (vg)13 ,

(31)

we define a fluid property nondimensional group as

N f = ρ3v4g

σ 3, (32)


Figure 6. Typical wave profile corresponding to statistically steady state for case V.

nondimensional peak height as

Nhp = h peak

(v2

g

)− 13

, (33)

nondimensional wavelength as

Nλ = λs

(v2

g

)− 13

, (34)

and, nondimensional wave velocity as

Nuw = uw(vg)−13 . (35)

We performed a set of six numerical experiments shown in Table 2, spanninga range of Re, N f , and Nλ similar to the experiments performed in [1].

In the regime under study in this section, the flow statistics become steady,and analysis is possible with good accuracy. For comparing with data, Nosokoet al. [1] have performed a comprehensive set of experiments in this regime,


Figure 7. Comparison between nondimensional peak height experimental scaling (dashedline) and numerical experimental cases I through VI. This figure is colour online.

and were able to extract many scaling characteristics of the flow. This sectionwill serve as a validation of our approach.

4.2. Results

In their work, Nosoko et al. [1] found from experiments the followingrelationships for wave peak height and wave velocity:

Nhp = 0.49N 0.044f N 0.39

λ Re0.46, (36)

Nuw = 1.13N 0.02f N 0.31

λ Re0.37, (37)

and

Nhp = 0.425N 0.019f N 1.25

uw . (38)

In Figures 4–6 we present wave shapes at statistically steady state forcases II, III, and V detailed in Table 2. Although the wave profiles may match


Figure 8. Comparison between nondimensional wave velocity experimental scaling (dashedline) and numerical experimental cases I through VI. This figure is colour online.

visually what is observed in experiments [8] and other numerical studies[17,15], we proceed to quantify our results by comparing with empiricalrelationships in Equations (36)–(38).

In Figure 7, we present the scaling corresponding to (36) versus ourcalculations. There is good agreement of values from the simulations withthe empirical relationship derived from experiment. Note at larger values ofthe abscissa, numerical results are more scattered. The larger scattering maybe explained by the fact that for larger values of the abscissa, the film isnot as statistically steady as for lower values, resulting in some difficulty incomputing statistically steady film heights.

The second empirical relationship described by (37) is tested against thesimulations in Figure 8. Good agreement between the relationship in [1] andthe numerical simulations is again evident.

Finally, Figure 9 shows the comparison between (38) and results ofthe simulations. It is again evident that there is good agreement betweenexperiments and the numerical solutions.


Figure 9. Comparison between nondimensional peak height experimental scaling (dashedline) and numerical experimental cases I through VI. This figure is colour online.

5. Conclusion and outlook

We have presented a numerical method for the Direct Numerical Simulation(DNS) of liquid films. Several issues needed to be addressed to solve theproblem of liquid films with large deformation:

• The need for an elongated grid aspect ratio arising from the geometricalconfiguration of liquid films has warranted development of a sharp interfacemethod based on the ghost fluid formulation [7].

• In contrast with homogeneous turbulence, liquid film turbulence is a highaspect ratio phenomenon, and again warrants using elongated grids. Toperform simulations, as required for example in the DNS of high Reynoldsnumber problems, we have developed an implicit treatment of the viscousterm present in the Navier–Stokes equations thus removing the stabilityrestriction imposed by the small grid spacing in the wall-normal direction.

• Because falling liquid films need a large domain to capture their growthto statistically steady state, we have developed a solution technique with


Figure 10. Transition from 2D to 3D on a vertically falling liquid film at RE = 400. (flow tothe right). This figure is colour online.


Figure 11. Structures in the liquid—No gravity/gas driven system. This figure is colour online.

periodic boundary conditions. This is also necessary for studying highReynolds and turbulence problems, as DNS is often performed for canonicalconditions using periodic boundary conditions. Figure 10 shows a sequencein time of interface profiles for a vertically falling liquid film in 3D. Theflow was initialized with a 2D disturbance and we observed the transitionto a fully 3D profile. Similar computations at much greater computationalcost (the results presented in Figure 10 required a few hours on a singleCPU machine) are performed in [17] using inflow/outflow conditions, thusrequiring unnecessarily long domains.

• We have validated our approach by comparing our numerical simulationswith the experiment of Nosoko et al. [1] for vertical falling liquid filmsat Reynolds number up to 100. The empirical relationships derived fromexperiment were compared with our numerical calculations with goodagreement. In conclusion, it is important to recognize that the numericalmethod developed here is very general.

As future work, we plan to study the effect of gravity on gas driven flows.As an example, Figures 11 and 12 show a case with no gravity. In Figure 11,we observe large deformation of the interface along with vortical structures in


Figure 12. Vortical structures in the gas—No gravity/gas driven system. This figure is colouronline.

the liquid. In Figure 12, we show vortical structures in the gas phase for thesame case, and here, streamwise streaky structures are present and “wave-shapeeffects” on these structures is observed.

Finally, we hope the method presented here will serve as a tool to studyliquid films systems whether they are gravity-driven such as falling liquidfilms, or gas-driven. In the latter case, a large area is now open for investigationthrough DNS including such systems as micro-breaking and breaking waves.

6. Acknowledgments

This work was partially supported by the National Aeronautics andSpace Administration, Microgravity Research Division under Contract No.NAG3-2414.


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MASSACHUSETTS INSTITUTE OF TECHNOLOGY

UNIVERSITY OF CALIFORNIA, SANTA BARBARA

CITY UNIVERSITY OF NEW YORK

(Received December 10, 2009)

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