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Numerical experiments

In this chapter we present numerical experiments results for the diffuse interface model for both single and multiple components gas-liquid systems. For single-component system with M = 1 in the first part, we consider a pure substance fluid of isobutane (C4H10). For multi-component system in the second part, a mixture of isobutane

(C4H10) and decane (C10H22) is used for the case M = 2. The critical properties

used to calculate parameters in the models are listed in Table 5.1. All experiments are carried in the domain Ω = (0, L)d _{with L = 2.0E-08 meters and d= 2,3 denotes}

the space dimension. The first order and second order invariant energy quadratization methods are denoted by IEQ-1 and IEQ-BDF2, respectively.

Table 5.1 Critical properties and parameters.

Symbol Tc(K) Pc ω m C4H10 425.2 3.80 MPa 0.199 0.6708

C10H22 617.7 2.10 MPa 0.484 1.0578

5.1 Single-component system

5.1.1 Temporal accuracy test for single-component system

We first present numerical experiments in two dimensions to demonstrate the tempo- ral accuracy of the two numerical schemes for the single-component system. For the initial configuration, we use the case of single droplet – the liquid density of isobu- tane under a saturated pressure condition at the temperature 350K is imposed in the

square subregion of 3L

8 , 3L

4 2

, and the rest of the domain is filled with a saturated gas of isobutane under the same temperature. In other words, about 14% of the total volume is saturated liquid, while the rest 86% is saturated gas.

We perform the refinement test of the time step size (∆t = 2.0E-2, 1.0E-2, · · ·, 1.5625E-4) for both the IEQ-1 and IEQ-BDF2 schemes, and choose the approximate solution obtained by applying the schemes with the small time step size ∆t = 1.0E-6 as the benchmark solution for computing errors. The penalty parameter is set to beP

= 1.0E+20. The spatial discretization is carried out using the central finite difference on the uniform 1024×1024 mesh of the domain Ω to remove the effect caused by the errors of spatial discretization. Define the L2 relative error of the approximate

solution for the molar density n by

L2 =

||n∗−nh||

||n∗||

,

where n∗ denotes the benchmark solution and nh the numerical solution. Table 5.2

lists theL2 relative errors and convergence rates of the numerical solutions at t= 0.5

with different time step sizes. It is easy to see that both the IEQ-1 and IEQ-BDF2 schemes work very stably for all time step sizes and show almost perfect first and second order accuracies. In addition, IEQ-BDF2 gives much better accuracy than IEQ-1 along the time step size refinement.

There is a large gradient contribution to the total Helmholtz free energy due to the jump in molar density between the gas and liquid regions. We will numerically simulate the time evolution of the molar density distribution and track the gas-liquid interface under the gradient flow in two and three dimensional spaces.

5.1.2 2D simulation

We perform experiments in 2D with different initial configurations. We use the IEQ- BDF2 scheme with ∆t = 5.0E-3 and a uniform mesh of 512×512 and set the penalty parameter P = 1.0E+20.

Table 5.2 Convergence tests for single component system.

Time Step Size IEQ-1 IEQ-BDF2 ∆t Error Conv. Rate Error Conv. Rate 2.0E-2 9.4836E-3 - 5.2778E-3 - 1.0E-2 4.6670E-3 1.023 1.8632E-3 1.503 5.0E-3 2.2616E-3 1.045 5.8986E-4 1.659 2.5E-3 1.1027E-3 1.036 1.6892E-4 1.804 1.25E-3 5.4286E-4 1.022 4.4680E-5 1.919 6.25E-4 2.6915E-4 1.012 1.1272E-5 1.987 3.125E-4 1.3401E-5 1.006 2.7880E-6 2.015 1.5625E-4 6.6855E-5 1.003 7.0398E-7 1.986

one droplet

Figure 5.1 presents the simulated molar density distribution for the one droplet case at different times (t = 0,1,3,5,10,20, respectively) during the evolution. The initial configuration is the same as we used in the accuracy test. We can see that the shape of the droplet for the liquid is initially square, but its four corners are slowly rounded as the time increases, and finally appears to be a perfect circle. At the time

t= 20 the steady state seems to be reached. As suggested in [40], the surface tension contribution of Helmholtz free energy density, fST, is defined by

fST = 2f∇(n) =c∇n· ∇n, (5.1)

which can be used to better characterize the gas-liquid interface. The plots of the simulated surface tension contribution of Helmholtz free energy density at the same times are shown in Figure 5.2, and we can clearly see the movement of the interface along with the time. The corresponding plots of evolution of the total energy (3.4) and the mass are given in Figure 5.3. We observe that the energy decreases monotonically and the mass is accurately maintained with respect to the time. The energy decay is very fast initially then slows down as the solution approaches its steady state.

Figure 5.1 Dynamical evolution of one droplet in 2D: molar density distribution of

C4H10.

Figure 5.2 Dynamical evolution of one droplet in 2D: surface tension contribution of Helmholtz free energy density of C4H10.

Figure 5.3 Energy and mass evolutions of one droplet in 2D. Top: energy; Bottom: mass.

four droplets

Next, we simulate the dynamical evolution of the molar density distribution for the case of having four droplets in the initial configuration – the liquid density of isobutane under a saturated pressure condition at the temperature 350K is imposed in the subregion of four squares nL

4,

L

2

,5₈L,7₈Lo2, and the rest of the domain is filled with a saturated gas of isobutane under the same temperature. Figure 5.4 presents the simulated molar density distribution of Helmholtz free energy density for the case of four droplets at different times (t = 0, 5,10, 20, 40, 50, respectively) during the evolution, and Figure 5.5 the surface tension contribution of Helmholtz free energy density at the same times. The steady state seems reached at the timet= 50, which is longer than that needed for the single droplet case. We observe that the shapes of the four droplets are square initially, then four corners of all droplets are slowly rounded to become four circles as the time increases, and next the four circular droplets start to merge together and finally form one bigger circle. Figure 5.6 plots the evolution of the total energy and the mass, and again it is observed that the energy decreases monotonically and the mass is accurately maintained along the time. We also observe that there is a quite large energy decay at the very early time and small energy decay thereafter before steady state is reached.

We remark that extra experiments with a smaller time step size ∆t= 0.001 and a larger penalty parameterP = 1.0E+21 for the above examples are also carried out to make sure the convergences of the numerical solutions, and very similar simulation results are obtained for both one and four droplets cases.

5.1.3 3D simulation

Now we carry out some experiments to simulate the dynamics of the molar density distribution in 3D. We use the IEQ-BDF2 scheme with ∆t = 5.0E-3 and a uniform mesh of 128×128×128 and set the penalty parameter P = 1.0E+30.

Figure 5.4 Dynamical evolution of four droplets in 2D: molar density distribution of C4H10.

Figure 5.5 Dynamical evolution of four droplets in 2D: surface tension contribution of Helmholtz free energy density of C4H10.

Figure 5.6 Energy and mass evolutions of four droplets in 2D. Top: energy; Bottom: mass.

one droplet

We first test using a single droplet as the initial condition – the liquid density of isobutane under a saturated pressure condition at the temperature 350K is imposed in the cube subregion of (3₈L,3₄L)3, and the rest of the cube is filled with a saturated gas of isobutane under the same temperature. Figure 5.7 presents the simulated molar density distribution for one droplet in 3D at different times (t = 0, 1, 3, 5, 10, 20, respectively) during the evolution. In each time panel, the top one represents the isosurface and the bottom one represents the approximated solution across the three central planes of the 3D cubic domain. We observe that the 3D dynamical behaviors are very consistent with 2D cases, and the droplet finally forms a perfect sphere around the timet = 20, which is almost the steady state. Figure 5.8 plots the evolution of total energy and the mass along the time, and we again observe that the energy monotonically decays and the mass are well preserved with respect to time.

eight droplets

For the next example in 3D, the initial configuration is taken to be eight droplets – the liquid density of isobutane is imposed in the subregion of eight cubesnL

4, L 2 ,5L 8 , 7L 8 o3

at 350K, and the rest of the domain is filled with a saturated gas of isobutane under a saturated pressure condition at the same temperature. Figure 5.9 presents the sim- ulated molar density distribution for the eight droplet case in 3D at different times (t = 0,5,10,20,40,50, respectively) during the evolution. The eight cubic droplets first evolve into eight separate spheres, then start to merge and finally form one big- ger sphere around the time t = 50. This dynamic process is very similar to that for the four droplets case in 2D. In Figure 5.10, we present the evolution of the total energy and the mass with respect to the time, and observe again that the energy monotonically decays and the mass always keeps constant.

Figure 5.7 Dynamical evolution of one droplet in 3D: molar density distribution of

C4H10.

5.1.4 Comparisons with laboratory data

We now compare the numerical predictions from our simulations with laboratory data to valid the reliability of our schemes. As the quantity of interest in many applications, the surface tension σ is defined as the work for creating a unit area of interface with a unit ofJ/m2 _{or the net contractive force per unit length of interface}

Figure 5.8 Energy and mass evolutions of one droplet in 3D. Top: energy; Bottom: mass.

Figure 5.9 Dynamical evolution of eight droplets in 3D: molar density distribution of C4H10.

with a unit of N/mfrom the thermodynamical or mechanical point of view. In this model, the surface/interface tension σ is defined by

σ= ∂F ∂A = F(n)−F0(ninitial) A ∼ = R ΩfSTdx A ,

where A is the area of the interface.

Let us assume that the mass of the liquid droplet does not change along with time and the steady state droplet has a perfect circular/spherical shape. For the single

Figure 5.10 Energy and mass evolutions of eight droplets in 3D. Top: energy; Bottom: mass.

droplet case in 2D, the radius of the circular droplet is r = 4.231 ×10−9 _meters.

The surface tension of isobutane in the equilibrium state at the temperature ranging from 250K to 333.82K are calculated by using the IEQ-BDF2 scheme with ∆t = 5.0E-3 on the uniform mesh of 512×512 and the penalty parameter P = 1.0E+20. For example, F(n)−F0(ninitial)= 2∼ .229×10−10J at the temperature T = 333.82K,

and the corresponding interface tension isσ = 8.384×10−3J/m2 by our simulation. The complete results are presented in left panel of Figure 5.11 together with the laboratory measured values provided in [32]. It is clear that the differences between the numerical results and the experimental data is small from the engineering point of view.

Based on the values of the surface tension, we can test another physically con- cerned quality, the capillary pressure Pc, which defined by the well-known Young-

Laplace equation

Pc=Pliquid−Pgas≈ σ

r, (5.2)

where the thermodynamic pressure for the liquid Pliquid or the gasPgas is defined by

P = nRT

1−bn−

n2_a(T)

1 + 2bn−b2_n2. (5.3)

According to the equation (5.2), there are two different ways to numerically calculate the capillary pressure, one is to use the difference between the liquid drop pressure and the pressure of the gas phase and the other is to use the numerical results obtained for the interface tension σ. For example, at the temperature 333.28K, Pliquid =

2.634×106Pa and Pgas = 0.701×106Pa, thus the difference isPc = 1.933×106Pa.

On the other hand, the capillary pressure obtained from the approximated interface tension isPc= σ_r = 1.981×106Pa. It is clear that the Young-Laplace prediction is well

matched with the capillary pressure obtained by our numerical schemes with about an error of 2%. The right panel of Figure 5.11 plots the capillary pressure from 250K to 333.82K, which are calculated by above two ways. The matching errors are all

about or smaller than 2% at tested temperatures. In this case, the diffuse interface model with Peng-Robinson equation of state and the proposed numerical schemes are physically reliable to be used to simulate the two-phase fluid of the substance isobutane.

We next use the results from the single droplet case in 3D to compare with the laboratory data. The IEQ-BDF2 scheme with ∆t = 5.0E-3 on the uniform mesh of 128×128×128 and the penalty parameterP = 1.0E+30 is used for all simulations, and the results are given in Figure 5.12. The simulated interface tensions at all tested temperatures still match the laboratory data from the engineering point of view. For the capillary pressure, the results calculated from the Young-Laplace equation are close to those obtained from the approximate interface tensions when the temperature is in the high end of the [250,333.28], but the difference becomes larger and larger along with the decreasing of the temperature. This issue on the capillary pressure may be worthy of further investigation from the modeling side on the causes.

5.2 Multi-component system

5.2.1 Temporal accuracy test

In order to test the convergence order, we first use the case of one single droplet, that is, the liquid density of the mixture consisting of isobutane (C4H10) and decane

(C10H22) under a saturated pressure condition at the temperature 450K is imposed

in a square subregion (3₈L,5₈L)2_{, and the rest of domain is filled with a saturated}

gas of the mixture under same temperature. We perform our simulations on the time intervalt0.6 with refinement time step size ∆t= 2.0E−2,1.0E−2,· · · ,3.125E−4 for both the first order (IEQ-1) and the second order (IEQ-BDF2) schemes. We choose the stabilizer coefficients κi = 180, together with a lower bound 1E+12 and use a

256×256 mesh grid in 2D. We compare each simulated solution with the benchmark obtained by each scheme with ∆t = 1.0E-5. The L2 _{relative errors and convergence}

Figure 5.11 Comparison between the numerical predictions and the laboratory data in 2D. Top: interface tension; Bottom: capillary pressure.

Figure 5.12 Comparison between the numerical predictions and the laboratory data in 3D. Top: interface tension; Bottom: capillary pressure.

rates are listed in Table 5.3.

Table 5.3 Convergence tests for multi-component system.

Time Step Size IEQ-1 IEQ-BDF2 ∆t Error Conv. Rate Error Conv. Rate 2.0E-2 2.1943E-2 - 1.5156E-2 - 1.0E-2 1.8201E-2 0.27 5.9916E-3 1.34 5.0E-3 1.3570E-2 0.42 1.6472E-3 1.86 2.5E-3 8.9856E-3 0.59 4.4788E-4 1.88 1.25E-3 5.3502E-3 0.75 1.2479E-4 1.84 6.25E-4 2.9414E-3 0.86 3.4321E-5 1.86 3.125E-4 1.5298E-3 0.94 9.1366E-6 1.91

From Table 5.3, it is easy to observe that both the IEQ-1 and IEQ-BDF2 schemes are very stable for all time step sizes, and have almost first and second order accuracy, respectively.

5.2.2 2D simulation

In this section, we investigate the time evolution of the molar density distribution and the gas-liquid interface in 2D with one droplet and four droplets, respectively. The IEQ-BDF2 scheme with ∆t=5.0E-3 is adopted to perform the simulations. The stabilizer coefficients, the lower bound and the mesh grid are chosen as κi = 180,

1.0E+12 and 256×256, respectively.

one droplet

The liquid density of the mixture is filled in the square subdomain of (3₈L,5₈L)2, and a saturate gas of both components is full of the rest of the domain under the tem- perature 450K. The simulations of evolution process are shown in Figure 5.13 and Figure 5.14 at different times (t = 0,0.5,1,2,5,10) for both components, isobutane and decane, respectively. We can observe that the shape of the droplet for the liquid phase is initially square, then corners are rounded and turning to a circle as system

approaching to steady state, and finally the droplet becomes a perfect circle. This coincides with Figure 5.15 where the energy decreasing is significant at the beginning and slows down as density of each substance is distributed uniformly in all directions and a circular interface is formed, and the mass conservation is well preserved.

Figure 5.13 Dynamical evolution of one droplet in 2D: molar density distribution of C4H10.

four droplets

Next, we simulate the dynamical evolution of molar density distribution for the case of having four droplets as initial configuration, that is, the liquid density of the mixture under a saturated pressure condition at the temperature 450K is imposed in the square subregion of {(3L

16, 7L 16),( 9L 16, 13L 16 )}

2_{, and the rest of domain is filled with a}

saturated gas of the mixture under same temperature. The simulation of evolution process are shown in Figure 5.16 and Figure 5.17. We observe that the shapes of four droplets are initially square, then four corners are slowly rounded to become circular. Next when the interfaces of droplets start to touch each other, these four droplets start to merge to form one circle-like droplet. In Figure 5.18 we plot the evolutions

Figure 5.14 Dynamical evolution of one droplet in 2D: molar density distribution of C10H22.

of total energy and mass, and again observe that the energy decreases monotonically and the mass of each species is accurately maintained along the time.

5.2.3 3D simulation

Experiments are presented to simulate the dynamics of the molar density distribution of both components in 3D. We adopt the IEQ-BDF2 scheme with ∆t=5.0E-3 and a uniform mesh of 128×128×128 grid together with a lower bound 1.0E+12 and the stabilizer coefficients κi = 180.

one droplet

The first simulation has a single droplet as the initial condition. The liquid density of the mixture under a saturated pressure condition at the temperature 450K is imposed in the cube subregion of (3L

8 , 5L

8 )

3_{, and the rest of the cube is filled with a saturated}

gas of both components under the same temperature .

Figure 5.15 Energy and mass evolutions of one droplet in 3D. Top: energy; Bottom: mass.

Figure 5.16 Dynamical evolution of four droplets in 2D: molar density distribution of C4H10.

Figure 5.17 Dynamical evolution of four droplets in 2D: molar density distribution of C10H22.

both components in 3D at different times (t= 0,0.5,1,2,5,10) during the evolution, respectively. Similar to the dynamical behaviors of a single droplet in 2D, we can observe that the droplet finally forms a sphere and the steady state is reached. The

Figure 5.18 Energy and mass evolutions of four droplets in 2D. Top: energy; Bottom: mass.