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VOF-PLIC: sheared bubble

VOF-PLIC test case of sheared bubble (2D)

Description of the test case

This test case solves the advection of a disc of fluid in a sheared analytical velocity field. It is particularly adapted to measure mass-conservation. The objective is to compare two VOF-PLIC (Piecewise Linear Interface Construction) advection methods, the conservative method presented in [1] and the non conservative method presented in [2].

Configurations

Domain

The simulation takes place in a 2D box of coordinate \( (0,0) \) and \( (1,1) \). This domain is discretized uniformly with N cells in each directions. A bubble of fluid A is initialized in a domain full of fluid B. The coordinates of the center of the bubble at initial time is \( (0.5,0.75) \) with a \(0.15m\) radius. The simulation runs during \(T=1.5s\).

Velocity field and time step

Four velocity fields are proposed in this test case, from case A to case D. Velocity fields of cases C and D are respectively the symetric of cases A and B with respect to the line \( x=0.5 \).

CASE \(u(x,y)\) \(v(x,y)\)
A \( x \) \(-y \)
B \( x \) \(1-y \)
C \(-1+x \) \(-y \)
D \(-1+x \) \(1-y \)

![Figure 1: Velocity field for the CASE A] (velocity_field_bubble_distorsion.png)

To ensure that CFL of the method is always respected, we set a time step \( \Delta t \) such as

\begin{align} \Delta t = \frac{0.2}{N} \end{align}

Exact solution

We adopt the developpement of the exact solution proposed in [2] to our test case A.

\begin{align} u(x,y) = x \\ v(x,y) = -y \end{align}

We also know that :

\begin{align} u(x,y) = \frac{\partial x(t)}{\partial t} \Rightarrow u'-u=0 \qquad (1) \\ v(x,y) = \frac{\partial y(t)}{\partial t} \Rightarrow v'+v=0 \qquad (2) \end{align}

(1) and (2) are ordinary differencial equations with initial conditions defined such as :

\begin{align} x(t=0) = x_0 \\ y(t=0) = y_0\\ u(t=0) = x_0 \\ v(t=0) = -y_0 \end{align}

then solving (1) and (2) we obtain the following paraametric equation system :

\begin{align} x(t) = x_0e^{t} \\ y(t) = y_0e^{-t} \end{align}

which describes hyperbolic network curves. Let consider fluid particles which at initial time take part in the \( (x_{c0},y_{c0}) \) centered circle of radius \( R_0 \), we obtain :

\begin{align} (x_0-x_{c0})^2+(y_0-y_{c0})^2 = R_0^2 \end{align}

Let \( x_c(t) \), \( y_c(t) \) and \( x(t) \), \( y(t) \) the coordinate of the center and fluid particle of the bubble at the initial time. Then we get :

\begin{align} (x(t)-x_{c}(t))^2 = (x_0-x_{c0})^2e^{2t} \\ (y(t)-y_{c}(t))^2 = (y_0-y_{c0})^2e^{-2t} \end{align}

so that leads to the following ellipse cartesian equation of the form :

\begin{align} \left( \frac{x(t)-x_{c0}}{R_0e^t}\right)^2 + \left( \frac{y(t)-y_{c0}}{R_0e^{-t}}\right)^2 = 1 \end{align}

with for semi major axis \( a = R_0e^t \) and semi minor axis \( b = R_0e^{-t} \).

Finally, to initialize an ellipse in Notus we need to define a polygon with a given number of points \(n\). The coordinates of each point \(i\) are given by:

\begin{align} x(i) = acos(i) = R_0e^{0.8}cos(i\pi/n) \\ y(i) = bsin(i) = R_0e^{-0.8}sin(i\pi/n) \end{align}

Results

Isocontour visualisation for different cases

Next figures show isocontour of the volume fraction value 0.5 for cases A and B at initial time, intermediate and final time. Since isocontour for conservative and non conservative methods are surimposed, only one is shown.

![Figure 2: Isocontour of the volume fraction value 0.5 for the CASE A, from t=0s, t=0.4s to t=0.8s] (CASEB.png)

![Figure 3: Isocontour of the volume fraction value 0.5 for the CASE B, from t=0s, t=0.4s to t=0.8s] (CASEA.png)

Evaluation of mass loss

In order to evaluate mass loss \( \varepsilon \) during the simulation, we compute the difference between the volume fraction of fluid at initial time and at time T.

\begin{align} \varepsilon = \sum \limits^{N^2}_{i=1}f_i - \sum \limits^{N^2}_{i=1} f_i^0 \end{align}

Mesh convergence evaluation

To evaluate mesh convergence, we use the \( L_1 \) norm of the difference between the initial and the current volume fraction:

\begin{align} L_1 = \sum \limits^{N^3}_{i=1} |f_i - f^0_i| \\ \end{align}

We also compute local convergence order \( p \) of the method evaluating the evolution of the error with the mesh refinement:

\begin{align} p = \frac{ln\left( \frac{E_2}{E_1} \right)}{ln\left (\frac{N_1}{N_2} \right)} \end{align}

where \( E_1 \) and \(E_2 \) are error for mesh 1 and mesh 2, of size \( N_1\) and \(N_2\) respectively.

Results

The following tables show, for different spatial discretizations the material loss for the two diffents advection methods.

\begin{align} \textbf{Non-conservative method} \end{align}

Grid size N \( \Delta x \) \( \varepsilon_{air}\) (non conservative method) \( L_1 \) p
8 1/8 \( 3.75 \times 10^{-2} \) \( 3.75 \times 10^{-2}\)
16 1/16 \( 6.97 \times 10^{-4} \) \( 9.36 \times 10^{-3}\) \(2.00 \)
32 1/32 \( -3.53 \times 10^{-4} \) \( 2.39 \times 10^{-3}\) \(1.97 \)
64 1/64 \( 1.76 \times 10^{-4} \) \( 1.05 \times 10^{-3}\) \(1.18 \)
128 1/128 \( 8.82 \times 10^{-5} \) \( 4.69 \times 10^{-4}\) \(1.16 \)
256 1/256 \( 4.42 \times 10^{-5} \) \( 2.30 \times 10^{-4}\) \(1.02 \)
512 1/512 \( 2.21 \times 10^{-5} \) \( 1.08 \times 10^{-4}\) \(1.09 \)

\begin{align} \textbf{Conservative method} \end{align}

Grid size N \( \Delta x \) \( \varepsilon_{air}\) (conservative method) \( L_1 \) p
8 1/8 \( -1.11 \times 10^{-16} \) \( 3.76 \times 10^{-2}\)
16 1/16 \( 5.55 \times 10^{-16} \) \( 9.25 \times 10^{-3}\) \( 2.02 \)
32 1/32 \( -1.11 \times 10^{-16} \) \( 2.37 \times 10^{-3}\) \(1.96 \)
64 1/64 \( 0.0 \) \( 1.01 \times 10^{-3}\) \(1.23 \)
128 1/128 \( 1.11 \times 10^{-16} \) \( 4.75 \times 10^{-4}\) \(1.08 \)
256 1/256 \( 1.11 \times 10^{-16} \) \( 2.34 \times 10^{-4}\) \(1.02 \)
512 1/512 \( 1.11 \times 10^{-16} \) \( 1.10 \times 10^{-4}\) \(1.09 \)

Results confirm that even though the method presented in [2] shows pretty good results concerning mass conservation, the one presented in [1] is fully conservative (up to machine precision). Moreover, the convergence order is near to one for both methods and nearly same errors are noticed.

References

[1] G.D. Weymouth, Dick K.-P. Yue, Conservative Volume-of-Fluid method for free-surface simulations on Cartesian-grids, Journal of Computational Physics 229 (2010) 2853–2865

[2] Jérôme Breil. Modélisation du remplissage en propergol de moteur a propulsion solide. Mécanique des fluides [physics.class-ph]. Université de Bordeaux 1, 2001. Français. tel-0147869. https://tel.archives-ouvertes.fr/tel-01478691