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15  \section{Rayleigh-Taylor Instability}  \section{Rayleigh-Taylor Instability}
16  \label{LEVELSET CHAP}  \label{LEVELSET CHAP}
17    
18  In this chapter we will implement the Level Set Method in Escript for tracking the interface between two fluids for Computational Fluid Dynamics (CFD).  In this chapter we will implement the Level Set Method in Escript for tracking the interface between two fluids for Computational Fluid Dynamics (CFD). The method is tested with a Rayleigh-Taylor Instability problem, which is an instability of the interface between two fluids with differing densities. \\
19  Normally in Earth science problems two or more fluids in a system with different properties are of interest. For example, lava dome growth in volcanology, with the contrast of the two mediums as being lava and air. The interface between the two mediums is often referred to as a free surface (free boundary value problem); the problem arises due to the large differences in densities between the lava and air, with their ratio being around 2000, and so the interface between the two fluids move with respect to each other.    Normally in Earth science problems two or more fluids in a system with different properties are of interest. For example, lava dome growth in volcanology, with the contrast of the two mediums as being lava and air. The interface between the two mediums is often referred to as a free surface (free boundary value problem); the problem arises due to the large differences in densities between the lava and air, with their ratio being around 2000, and so the interface between the two fluids move with respect to each other.  
20  %and so the lava with the much higher density is able to move independently with respect to the air, and the interface between the two fluids is not constrained.  %and so the lava with the much higher density is able to move independently with respect to the air, and the interface between the two fluids is not constrained.
21  There are a number of numerical techniques to define and track the free surfaces. One of these methods, which is conceptually the simplest, is to construct a Lagrangian grid which moves with the fluid, and so it tracks the free surface. The limitation of this method is that it cannot track surfaces that break apart or intersect. Another limitation is that the elements in the grid can become severely distorted, resulting in numerical instability. The Arbitrary Lagrangian-Eulerian (ALE) method for CFD in moving domains is used to overcome this problem by remeshing, but there is an overhead in computational time, and it results in a loss of accuracy due to the process of mapping the state variables every remesh by interpolation.  There are a number of numerical techniques to define and track the free surfaces. One of these methods, which is conceptually the simplest, is to construct a Lagrangian grid which moves with the fluid, and so it tracks the free surface. The limitation of this method is that it cannot track surfaces that break apart or intersect. Another limitation is that the elements in the grid can become severely distorted, resulting in numerical instability. The Arbitrary Lagrangian-Eulerian (ALE) method for CFD in moving domains is used to overcome this problem by remeshing, but there is an overhead in computational time, and it results in a loss of accuracy due to the process of mapping the state variables every remesh by interpolation.
22    
23  There is a technique to overcome these limitations called the Level Set Method, for tracking interfaces between two fluids. The advantages of the method is that CFD can be performed on a fixed Cartesian mesh, and therefore problems with remeshing can be avoided. The field equations for calculating variables such as velocity and pressure are solved on the the same mesh. The Level Set Method is based upon the implicit representation of the interface by a continuous function. The function takes the form as a signed distance function, $\phi(x)$, of the interface in a Eulerian coordinate system. For example, the zero isocontour of the unit circle $\phi(x)=x^2 + y^2 -1$ is the set of all points where $\phi(x)=0$.  There is a technique to overcome these limitations called the Level Set Method, for tracking interfaces between two fluids. The advantages of the method is that CFD can be performed on a fixed Cartesian mesh, and therefore problems with remeshing can be avoided. The field equations for calculating variables such as velocity and pressure are solved on the the same mesh. The Level Set Method is based upon the implicit representation of the interface by a continuous function. The function takes the form as a signed distance function, $\phi(x)$, of the interface in a Eulerian coordinate system. For example, the zero isocontour of the unit circle $\phi(x)=x^2 + y^2 -1$ is the set of all points where $\phi(x)=0$. Refer to Figure \ref{UNITCIRCLE}.
24  %  %
25  \begin{figure}  \begin{figure}
26  \center  \center
27  \scalebox{0.5}{\includegraphics{figures/unitcircle.eps}}  \scalebox{0.7}{\includegraphics{figures/unitcircle.eps}}
28  \caption{Implicit representation of the curve $x^2 + y^2 = 1$.}  \caption{Implicit representation of the curve $x^2 + y^2 = 1$.}
29  \label{UNITCIRCLE}  \label{UNITCIRCLE}
30  \end{figure}  \end{figure}
31  %  %
32  The implicit representation can be used to define the interior and exterior of a fluid region. Since the isocontour at $\phi(x)=0$ has been defined as the interface, a point in the domain can be determined if its inside or outside of the interface, by looking at the local sign of $\phi(x)$. A point is inside the interface when $\phi(x)<0$, and outside the interface when $\phi(x)>0$. Parameters values such as density and viscosity can then be defined for two different mediums, depending on which side of the interface they are located. The displacement of the interface at the zero isocontour of $\phi(x)$ is calculated each time step by using the velocity field. This is achieved my solving the advection equation:  The implicit representation can be used to define the interior and exterior of a fluid region. Since the isocontour at $\phi(x)=0$ has been defined as the interface, a point in the domain can be determined if its inside or outside of the interface, by looking at the local sign of $\phi(x)$. For example, a point is inside the interface when $\phi(x)<0$, and outside the interface when $\phi(x)>0$. Parameters values such as density and viscosity can then be defined for two different mediums, depending on which side of the interface they are located.
33    
34    
35    \subsection{Calculation of the Displacement of the Interface}
36    
37    The displacement of the interface at the zero isocontour of $\phi(x)$ is calculated each time-step by using the velocity field. This is achieved my solving the advection equation:
38    %
39  \begin{equation}  \begin{equation}
40  \frac{\partial \phi}{\partial t} + \vec{v} \cdot \nabla \phi = 0,  \frac{\partial \phi}{\partial t} + \vec{v} \cdot \nabla \phi = 0,
41  \label{ADVECTION}  \label{ADVECTION}
42  \end{equation}  \end{equation}
43    %
44  where $\vec{v}$ is the velocity field. The advection equation is solved using a mid-point method, which is a two step procedure:  where $\vec{v}$ is the velocity field. The advection equation is solved using a mid-point, which is a two step procedure:
45    
46  Firstly, $\phi^{1/2}$ is calculated solving:  Firstly, $\phi^{1/2}$ is calculated solving:
47    %
48  \begin{equation}  \begin{equation}
49  \frac{\phi^{1/2} - \phi^{-}}{dt/2} + \vec{v} \cdot \nabla \phi^{-} = 0.  \frac{\phi^{1/2} - \phi^{-}}{dt/2} + \vec{v} \cdot \nabla \phi^{-} = 0.
50  \label{MIDPOINT FIST}  \label{MIDPOINT FIST}
51  \end{equation}  \end{equation}
52    %
53  Secondly, using $\phi^{1/2}$, $\phi^{+}$ is calculated solving:  Secondly, using $\phi^{1/2}$, $\phi^{+}$ is calculated solving:
54    %
55  \begin{equation}  \begin{equation}
56  \frac{\phi^{+} - \phi^{-}}{dt} + \vec{v} \cdot \nabla \phi^{1/2} = 0.  \frac{\phi^{+} - \phi^{-}}{dt} + \vec{v} \cdot \nabla \phi^{1/2} = 0.
57  \label{MIDPOINT SECOND}  \label{MIDPOINT SECOND}
58  \end{equation}  \end{equation}
59    %
60  For more details on the mid-point procedure see reference \cite{BOURGOUIN2006}. In certain situations the mid-point procedure has been shown to produce artifacts in the numerical solutions. A more robust procedure is to use the Taylor-Galerkin scheme with the presence of diffusion, which gives more stable solutions. The expression is derived by either inserting Equation (\ref{MIDPOINT FIST}) into Equation (\ref{MIDPOINT SECOND}), or by expanding $\phi$ into a Taylor series:  This procedure works provided that the discretization of the left-hand side of Equations (\ref{MIDPOINT FIST}) and (\ref{MIDPOINT SECOND}) is a lumped mass matrix. For more details on the mid-point procedure see reference \cite{BOURGOUIN2006}. In certain situations the mid-point procedure has been shown to produce artifacts in the numerical solutions. A more robust procedure is to use the Taylor-Galerkin scheme with the presence of diffusion, which gives more stable solutions. The expression is derived by either inserting Equation (\ref{MIDPOINT FIST}) into Equation (\ref{MIDPOINT SECOND}), or by expanding $\phi$ into a Taylor series:
61    %
62  \begin{equation}  \begin{equation}
63  \phi^{+} \simeq \phi^{-} + dt\frac{\partial \phi^{-}}{\partial t} + \frac{dt^2}{2}\frac{\partial^{2}\phi^{-}}{\partial t^{2}},  \phi^{+} \simeq \phi^{-} + dt\frac{\partial \phi^{-}}{\partial t} + \frac{dt^2}{2}\frac{\partial^{2}\phi^{-}}{\partial t^{2}},
64  \label{TAYLOR EXPANSION}  \label{TAYLOR EXPANSION}
65  \end{equation}  \end{equation}
66    %
67  by inserting  by inserting
68    %
69  \begin{equation}  \begin{equation}
70  \frac{\partial \phi^{-}}{\partial t} = - \vec{v} \cdot \nabla \phi^{-},  \frac{\partial \phi^{-}}{\partial t} = - \vec{v} \cdot \nabla \phi^{-},
71  \label{INSERT ADVECTION}  \label{INSERT ADVECTION}
72  \end{equation}  \end{equation}
73    %
74  and  and
75    %
76  \begin{equation}  \begin{equation}
77  \frac{\partial^{2} \phi^{-}}{\partial t^{2}} = \frac{\partial}{\partial t}(-\vec{v} \cdot \nabla \phi^{-}) = \vec{v}\cdot \nabla (\vec{v}\cdot \nabla \phi^{-}),  \frac{\partial^{2} \phi^{-}}{\partial t^{2}} = \frac{\partial}{\partial t}(-\vec{v} \cdot \nabla \phi^{-}) = \vec{v}\cdot \nabla (\vec{v}\cdot \nabla \phi^{-}),
78  \label{SECOND ORDER}  \label{SECOND ORDER}
79  \end{equation}  \end{equation}
80    %
81  into Equation \ref{TAYLOR EXPANSION}  into Equation (\ref{TAYLOR EXPANSION})
82    %
83  \begin{equation}  \begin{equation}
84  \phi^{+} = \phi^{-} - dt\vec{v}\cdot \nabla \phi^{-} + \frac{dt^2}{2}\vec{v}\cdot \nabla (\vec{v}\cdot \nabla \phi^{-}).  \phi^{+} = \phi^{-} - dt\vec{v}\cdot \nabla \phi^{-} + \frac{dt^2}{2}\vec{v}\cdot \nabla (\vec{v}\cdot \nabla \phi^{-}).
85  \label{TAYLOR GALERKIN}  \label{TAYLOR GALERKIN}
86  \end{equation}  \end{equation}
   
87    
 The fluid dynamics is governed by the Stokes equations. In geophysical problems the velocity of fluids are low; that is, the inertial forces are small compared with the viscous forces, therefore the inertial terms in the Navier-Stokes equations can be ignored. For a body force $f$ the governing equations are given by:  
88    
89    \subsection{Governing Equations for Fluid Flow}
90    
91    The fluid dynamics is governed by the Stokes equations. In geophysical problems the velocity of fluids are low; that is, the inertial forces are small compared with the viscous forces, therefore the inertial terms in the Navier-Stokes equations can be ignored. For a body force $f$ the governing equations are given by:
92    %
93  \begin{equation}  \begin{equation}
94  \nabla \cdot (\eta(\nabla \vec{v} + \nabla^{T} \vec{v})) - \nabla p = -f,  \nabla \cdot (\eta(\nabla \vec{v} + \nabla^{T} \vec{v})) - \nabla p = -f,
95  \label{GENERAL NAVIER STOKES}  \label{GENERAL NAVIER STOKES}
96  \end{equation}  \end{equation}
97    %
98  with the incompressibility condition  with the incompressibility condition
99    %
100  \begin{equation}  \begin{equation}
101  \nabla \cdot \vec{v} = 0.  \nabla \cdot \vec{v} = 0.
102  \label{INCOMPRESSIBILITY}  \label{INCOMPRESSIBILITY}
103  \end{equation}  \end{equation}
104    %
105  where $p$, $\eta$ and $f$ are the pressure, viscosity and body forces, respectively.  where $p$, $\eta$ and $f$ are the pressure, viscosity and body forces, respectively.
106  Alternatively, the Stokes equations can be represented in Einstein summation tensor notation (compact notation):  Alternatively, the Stokes equations can be represented in Einstein summation tensor notation (compact notation):
107    %
108  \begin{equation}  \begin{equation}
109  -(\eta(v\hackscore{i,j} + v\hackscore{j,i})),\hackscore{j} - p,\hackscore{i} = f\hackscore{i},  -(\eta(v\hackscore{i,j} + v\hackscore{j,i})),\hackscore{j} - p,\hackscore{i} = f\hackscore{i},
110  \label{GENERAL NAVIER STOKES COM}  \label{GENERAL NAVIER STOKES COM}
111  \end{equation}  \end{equation}
112    %
113  with the incompressibility condition  with the incompressibility condition
114    %
115  \begin{equation}  \begin{equation}
116  -v\hackscore{i,i} = 0.  -v\hackscore{i,i} = 0.
117  \label{INCOMPRESSIBILITY COM}  \label{INCOMPRESSIBILITY COM}
118  \end{equation}  \end{equation}
119    %
120  The subscript $,i$ denotes the derivative of the function with respect to $x\hackscore{i}$. A linear relationship between the deviatoric stress $\sigma^{'}\hackscore{ij}$ and the stretching $D\hackscore{ij} = \frac{1}{2}(v\hackscore{i,j} + v\hackscore{j,i})$ is defined as \cite{GROSS2006}:  The subscript comma $i$ denotes the derivative of the function with respect to $x\hackscore{i}$. A linear relationship between the deviatoric stress $\sigma^{'}\hackscore{ij}$ and the stretching $D\hackscore{ij} = \frac{1}{2}(v\hackscore{i,j} + v\hackscore{j,i})$ is defined as \cite{GROSS2006}:
121    %
122  \begin{equation}  \begin{equation}
123  \sigma^{'}\hackscore{ij} = 2\eta D^{'}\hackscore{ij},  \sigma^{'}\hackscore{ij} = 2\eta D^{'}\hackscore{ij},
124  \label{STRESS}  \label{STRESS}
125  \end{equation}  \end{equation}
126    %
127  where the deviatoric stretching $D^{'}\hackscore{ij}$ is defined as  where the deviatoric stretching $D^{'}\hackscore{ij}$ is defined as
128    %
129  \begin{equation}  \begin{equation}
130  D^{'}\hackscore{ij} = D^{'}\hackscore{ij} - \frac{1}{3}D\hackscore{kk}\delta\hackscore{ij}.  D^{'}\hackscore{ij} = D^{'}\hackscore{ij} - \frac{1}{3}D\hackscore{kk}\delta\hackscore{ij}.
131  \label{DEVIATORIC STRETCHING}  \label{DEVIATORIC STRETCHING}
132  \end{equation}  \end{equation}
133    %
134  The $\delta\hackscore{ij}$ is the Kronecker $\delta$-symbol, which is a matrix with ones for its diagonal entries ($i = j$) and zeros for the remaining entries ($i \neq j$). The body force $f$ in Equation (\ref{GENERAL NAVIER STOKES COM}) is the gravity acting in the $x\hackscore{3}$ direction and is given as $f = -g \rho \delta\hackscore{i3}$.  where $\delta\hackscore{ij}$ is the Kronecker $\delta$-symbol, which is a matrix with ones for its diagonal entries ($i = j$) and zeros for the remaining entries ($i \neq j$). The body force $f$ in Equation (\ref{GENERAL NAVIER STOKES COM}) is the gravity acting in the $x\hackscore{3}$ direction and is given as $f = -g \rho \delta\hackscore{i3}$.
   
135  The Stokes equations is a saddle point problem, and can be solved using a Uzawa scheme. A class called StokesProblemCartesian in Escript can be used to solve for velocity and pressure.  The Stokes equations is a saddle point problem, and can be solved using a Uzawa scheme. A class called StokesProblemCartesian in Escript can be used to solve for velocity and pressure.
136  In order to keep numerical stability, the time step size needs to be below a certain value, known as the Courant number. The Courant number is defined as:  In order to keep numerical stability, the time-step size needs to be below a certain value, known as the Courant number. The Courant number is defined as:
137    %
138  \begin{equation}  \begin{equation}
139  C = \frac{v \delta t}{h}.  C = \frac{v \delta t}{h}.
140  \label{COURANT}  \label{COURANT}
141  \end{equation}  \end{equation}
142    %
143    where $\delta t$, $v$, and $h$ are the time-step, velocity, and the width of an element in the mesh, respectively. The velocity $v$ may be chosen as the maximum velocity in the domain. In this problem the Courant number is taken to be 0.4 \cite{BOURGOUIN2006}.
144    
 where $\delta t$, $v$, and $h$ are the time step, velocity, and the width of an element in the mesh, respectively. The velocity $v$ may be chosen as the maximum velocity in the domain. In this problem the Courant number is taken to be 0.4 \cite{BOURGOUIN2006}.  
145    
146  As the computation of the distance function progresses, it becomes distorted, and so it needs to be updated in order to stay regular. This process is known as the reinitialization procedure. The aim is to iteratively find a solution to the reinitialization equation:  \subsection{Reinitialization of Interface}
147    
148    As the computation of the distance function progresses, it becomes distorted, and so it needs to be updated in order to stay regular \cite{SUSSMAN1994}. This process is known as the reinitialization procedure. The aim is to iteratively find a solution to the reinitialization equation:
149    %
150  \begin{equation}  \begin{equation}
151  \frac{\partial \psi}{\partial \tau} + sign(\psi)(1 - \nabla \psi) = 0.  \frac{\partial \psi}{\partial \tau} + sign(\phi)(1 - \nabla \psi) = 0.
152  \label{REINITIALISATION}  \label{REINITIALISATION}
153  \end{equation}  \end{equation}
154    %
155    where $\psi$ shares the same level set with $\phi$, $\tau$ is pseudo time, and $sign(\phi)$ is the smoothed sign function. This equation is solved to meet the definition of the level set function, $\lvert \nabla \psi \rvert = 1$; the normalization condition. Equation (\ref{REINITIALISATION}) can be rewritten in similar form to the advection equation:
156    %
157    \begin{equation}
158    \frac{\partial \psi}{\partial \tau} + \vec{w} \cdot \nabla \psi = sign(\phi),
159    \label{REINITIALISATION2}
160    \end{equation}
161    %
162    where
163    %
164    \begin{equation}
165    \vec{w} = sign(\phi)\frac{\nabla \psi}{|\nabla \psi|}.
166    \label{REINITIALISATION3}
167    \end{equation}
168    %
169    $\vec{w}$ is the characteristic velocity pointing outward from the free surface. Equation (\ref{REINITIALISATION2}) can be solved by a similar technique to what was used in the advection step; either by the mid-point technique \cite{BOURGOUIN2006} or the Taylor-Galerkin procedure. For the mid-point technique, the reinitialization technique algorithm is:
170    
171    1. Calculate
172    %
173    \begin{equation}
174    \vec{w} = sign(\phi)\frac{\nabla \psi}{|\nabla \psi|},
175    \label{REINITIAL MIDPOINT1}
176    \end{equation}
177    %
178    
179    2. Calculate $\psi^{1/2}$ solving
180    %
181    \begin{equation}
182    \frac{\psi^{1/2} - \psi^{-}}{d\tau/2} + \vec{w} \cdot \nabla \psi^{-}= sign(\phi),
183    \label{REINITIAL MIDPOINT2}
184    \end{equation}
185    %
186    
187    3. using $\psi^{1/2}$, calculate $\psi^{+}$ solving
188    %
189    \begin{equation}
190    \frac{\psi^{+} - \psi^{-}}{d\tau} + \vec{w} \cdot \nabla \psi^{1/2}= sign(\phi),
191    \label{REINITIAL MIDPOINT3}
192    \end{equation}
193    %
194    
195  where $\tau$ is artificial time. This equation is solved to meet the definition of the level set function, $\lvert \nabla \psi \rvert = 1$; the normalization condition. However, it has been shown that in using this reinitialization procedure it is prone to mass loss and inconsistent positioning of the interface \cite{SUCKALE2008}.  4. if the convergence criterion has not been met, go back to step 2. Convergence is declared if
196    %
197    \begin{equation}
198    ||\nabla \psi \hackscore{\infty}| - 1| < \epsilon \hackscore{\psi}.
199    \label{REINITIAL CONVERGE}
200    \end{equation}
201    %
202    where $\epsilon$ is the convergence tolerance. Normally, the reinitialization procedure is performed every third time-step of solving the Stokes equation.
203    
204    The mid-point technique works provided that the left-hand side of Equations (\ref{REINITIAL MIDPOINT2}) and (\ref{REINITIAL MIDPOINT3}) is a lumped mass matrix. Alternatively, for a one-step procedure, the reinitialization equation can be given by:
205    %
206    \begin{equation}
207    \psi^{+} = \psi^{-} - \tau \vec{w} \cdot \nabla \psi^{-} + \frac{d \tau^{2}}{2} \vec{w} \cdot \nabla(\vec{w} \cdot \nabla \psi^{-}).
208    \label{REINITIAL ONESTEP}
209    \end{equation}
210    %
211    The accuracy of $\phi$ is only needed within the transition zone; and so it can be calculated in a narrow band between the interface of the fluids.
212    %
213    \begin{figure}
214    \center
215    \scalebox{0.45}{\includegraphics{figures/LevelSetFlowChart.eps}}
216    \caption{Flow chart of level set procedure \cite{LIN2005}.}
217    \label{LEVELSET FLOWCHART}
218    \end{figure}
219    %
220    When the distance function, $\phi$, is calculated, the physical parameters, density and viscosity, are updated using the sign of $\phi$. The jump in material properties between two fluids, such as air and water can be extreme, and so the transition of the properties from one medium to another is smoothed. The region of the interface is assumed to be of finite thickness of $\alpha h$, where $h$ is the size of the elements in the computational mesh and $\alpha$ is a smoothing parameter. The parameters are updated by the following expression:
221    %
222    \begin{equation}
223    P =
224    \left \{ \begin{array}{l}
225    P\hackscore{1} \hspace{5cm}  where \ \ \psi < - \alpha h \\
226    P\hackscore{2} \hspace{5cm}  where \ \ \psi > \alpha h \\
227    (P\hackscore{2} - P\hackscore{1}) \psi/2\alpha h + (P\hackscore{1} + P\hackscore{2})/2 \ \ \ \ \ \ where \ \ |\psi| < \alpha h.
228    \end{array}
229    \right.
230    \label{UPDATE PARAMETERS}
231    \end{equation}
232    %
233    where the subscripts $1$ and $2$ denote the different fluids. The procedure of the level set calculation is shown in Figure \ref{LEVELSET FLOWCHART}.
234    Further work is needed in the reinitialization procedure, as it has been shown that it is prone to mass loss and inconsistent positioning of the interface \cite{SUCKALE2008}.
235    
236  The Rayleigh-Taylor instability problem is used as a benchmark to validate CFD implementations \cite{VANKEKEN1997}. Figure \ref{RT2DSETUP} shows the setup of the problem. A rectangular domain with two different fluids is considered, with the greater density fluid on the top and the lighter density fluid on the bottom. The viscosities of the two fluids are equal (isoviscos). An initial perturbation is given to the interface of $\phi=0.02cos(\frac{\pi x}{\lambda}) + 0.2$. The aspect ratio, $\lambda = L/H = 0.9142$, is chosen such that it gives the greatest disturbance of the fluids.  \subsection{Benchmark Problem}
237    
238    The Rayleigh-Taylor instability problem is used as a benchmark to validate CFD implementations \cite{VANKEKEN1997}. Figure \ref{RT2DSETUP} shows the setup of the problem. A rectangular domain with two different fluids is considered, with the greater density fluid on the top and the lighter density fluid on the bottom. The viscosities of the two fluids are equal (isoviscous). An initial perturbation is given to the interface of $\phi=0.02cos(\frac{\pi x}{\lambda}) + 0.2$. The aspect ratio $\lambda = L/H = 0.9142$ is chosen such that it gives the greatest disturbance of the fluids.
239    %
240  \begin{figure}  \begin{figure}
241  \center  \center
242  \scalebox{0.7}{\includegraphics{figures/RT2Dsetup.eps}}  \scalebox{0.7}{\includegraphics{figures/RT2Dsetup.eps}}
243  \caption{Parameters, initial interface and boundary conditions for the Rayleigh-Taylor instability problem. The interface is defined as $\phi=0.02cos(\frac{\pi x}{\lambda}) + 0.2$. The fluids have been assigned different densities and equal viscosity (isovisous).}  \caption{Parameters, initial interface and boundary conditions for the Rayleigh-Taylor instability problem. The interface is defined as $\phi=0.02cos(\frac{\pi x}{\lambda}) + 0.2$. The fluids have been assigned different densities and equal viscosity (isoviscous) \cite{BOURGOUIN2006}.}
244  \label{RT2DSETUP}  \label{RT2DSETUP}
245  \end{figure}  \end{figure}
246    
247  %The Level Set Method can be applied to many areas of science, for example simulating subduction zones in geophysics, motion of bubbles, and flame propagation. Its also used in image processing. However, the Level Set Method does have limitations. The level set function can still become irregular after reinitialisation, leading to artifacts in the simulations, requiring more thought into the implementation of the reinitialisation step.  %The Level Set Method can be applied to many areas of science, for example simulating subduction zones in geophysics, motion of bubbles, and flame propagation. Its also used in image processing. However, the Level Set Method does have limitations. The level set function can still become irregular after reinitialisation, leading to artifacts in the simulations, requiring more thought into the implementation of the reinitialisation step.
248    
249    \begin{python}
250    
251    from esys.escript import *
252    import esys.finley
253    from esys.escript.models import StokesProblemCartesian
254    from esys.finley import finley
255    from LevelSet import *
256    
257    #physical properties
258    rho1 = 1000     #fluid density on bottom
259    rho2 = 1010     #fluid density on top
260    eta1 = 100.0        #fluid viscosity on bottom
261    eta2 = 100.0        #fluid viscosity on top
262    penalty = 100.0
263    g=10.0
264    
265    #solver settings
266    dt = 0.001
267    t_step = 0
268    t_step_end = 2000
269    TOL = 1.0e-5
270    max_iter=400
271    verbose=True
272    useUzawa=True
273    
274    #define mesh
275    l0=0.9142
276    l1=1.0
277    n0=100      
278    n1=100
279    
280    mesh=esys.finley.Rectangle(l0=l0, l1=l1, order=2, n0=n0, n1=n1)
281    #get mesh dimensions
282    numDim = mesh.getDim()
283    #get element size
284    h = Lsup(mesh.getSize())
285    print "element size",h
286    
287    #level set parameters
288    tolerance = 1.0e-6
289    reinit_max = 30
290    reinit_each = 3
291    alpha = 1
292    smooth = alpha*h
293    
294    #boundary conditions
295    x = mesh.getX()
296    #left + bottom + right + top
297    b_c = whereZero(x[0])*[1.0,0.0] + whereZero(x[1])*[1.0,1.0] + whereZero(x[0]-l0)*[1.0,0.0] + whereZero(x[1]-l1)*[1.0,1.0]
298    
299    velocity = Vector(0.0, ContinuousFunction(mesh))
300    pressure = Scalar(0.0, ContinuousFunction(mesh))
301    Y = Vector(0.0,Function(mesh))
302    
303    #define initial interface between fluids
304    xx = mesh.getX()[0]
305    yy = mesh.getX()[1]
306    func = Scalar(0.0, ContinuousFunction(mesh))
307    h_interface = Scalar(0.0, ContinuousFunction(mesh))
308    h_interface = h_interface + (0.02*cos(math.pi*xx/l0) + 0.2)
309    func = yy - h_interface
310    func_new = func.interpolate(ReducedSolution(mesh))
311    
312    #Stokes cartesian
313    solution=StokesProblemCartesian(mesh,debug=True)
314    solution.setTolerance(TOL)
315    solution.setSubProblemTolerance(TOL**2)
316    
317    #level set
318    levelset = LevelSet(mesh, func_new, reinit_max, reinit_each, tolerance, smooth)    
319    
320    while t_step <= t_step_end:
321      #update density and viscosity
322      rho = levelset.update_parameter(rho1, rho2)
323      eta = levelset.update_parameter(eta1, eta2)
324    
325      #get velocity and pressue of fluid
326      Y[1] = -rho*g
327      solution.initialize(fixed_u_mask=b_c,eta=eta,f=Y)
328      velocity,pressure=solution.solve(velocity,pressure,max_iter=max_iter,verbose=verbose,useUzawa=useUzawa)
329      
330      #update the interface
331      func = levelset.update_phi(velocity, dt, t_step)  
332    
333      print "##########################################################"
334      print "time step:", t_step, " completed with dt:", dt
335      print "Velocity: min =", inf(velocity), "max =", Lsup(velocity)
336      print "##########################################################"
337    
338      #save interface, velocity and pressure
339      saveVTK("phi2D.%2.4i.vtu"%t_step,interface=func,velocity=velocity,pressure=pressure)
340      #courant condition
341      dt = 0.4*Lsup(mesh.getSize())/Lsup(velocity)
342      t_step += 1
343    
344    \end{python}

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