@@ -25,14 +25,14 @@ __Table of contents__. This description is structured as follows:
## Scenario and mathematical model
We model a soil contamination problem where DNAPL infiltrates a porous medium. The initial distribution of DNAPL is known and we can read it from a txt-file.
To describe that problem we use a two phase model of two immiscible fluids with the multiphase Darcy's law as the description of momentum, i.e.:
We describe the problem using a two phase model with two immiscible fluid phases (subscripts $`w`$ and $`n`$). We use multiphase Darcy's law for the momentum balance equations of the fluid phases, i.e.:
@@ -40,10 +40,16 @@ If we insert this into the conservation equations for each phase $`\alpha`$ that
\right\} - q_\alpha = 0
```
To reduce the number of unknowns and close the system we need closure relations for this equations. For that, we make use of a $`p_c - S_w`$ as well as a $`k_r - S_w`$ - relationship. In this problem we use a Van-Genuchten parameterization. The parameters for that relationship are specified in the `spatialparams.hh` file.
To reduce the number of unknowns and close the system we need closure relations for these equations. In this example, we use the
for the capillary pressure $`pc = p_n - p_w`$ and the relative permeabilities $`k_r\alpha`$.
The parameters for these relationships are specified in the `spatialparams.hh` file.
With the additional constraint that $`S_w + S_n = 1`$ we reduce the number of primary variables to two.
In this example we use the wetting phase pressure $`p_0`$ and the saturation of the nonwetting phase $`S_1`$ as primary variables. It is also possible to switch that formulation to the nonwetting pressure and the wetting saturation.
With the additional constraint that $`S_w + S_n = 1`$, the number of unknowns is reduced to two.
In this example we use the wetting phase pressure $`p_w`$ and the saturation of the nonwetting phase $`S_n`$ as primary variables. It is also possible to switch that formulation to the nonwetting pressure and the wetting saturation.
The two-dimensional model domain is 6m x 4m and contains a lens with a lower permeability and porosity. We read the initial values for the DNAPL saturation and the water pressure from a file.
The lens and the initial saturation can be seen in Figures 1 and 2.
...
...
@@ -55,7 +61,7 @@ DNAPL enters the model domain at the upper boundary between 1.75m ≤ x ≤ 2m w
In addition, the DNAPL is injected at a point source at x = 0.502m and y = 3.02m with a rate of 0.1 kg/s.
We discretize the equations with a cell-centered finite volume TPFA scheme in space and an implicit Euler scheme in time. We use Newton's method to solve the system of nonlinear equations.
The grid is adapitvely refined around the injection. The adaptive behaviour can be changed with input parameters in the `params.input` file.
The grid is adaptively refined around the injection. The adaptive behaviour can be changed with input parameters in the `params.input` file.
@@ -23,14 +23,14 @@ __Table of contents__. This description is structured as follows:
## Scenario and mathematical model
We model a soil contamination problem where DNAPL infiltrates a porous medium. The initial distribution of DNAPL is known and we can read it from a txt-file.
To describe that problem we use a two phase model of two immiscible fluids with the multiphase Darcy's law as the description of momentum, i.e.:
We describe the problem using a two phase model with two immiscible fluid phases (subscripts $`w`$ and $`n`$). We use multiphase Darcy's law for the momentum balance equations of the fluid phases, i.e.:
@@ -38,10 +38,16 @@ If we insert this into the conservation equations for each phase $`\alpha`$ that
\right\} - q_\alpha = 0
```
To reduce the number of unknowns and close the system we need closure relations for this equations. For that, we make use of a $`p_c - S_w`$ as well as a $`k_r - S_w`$ - relationship. In this problem we use a Van-Genuchten parameterization. The parameters for that relationship are specified in the `spatialparams.hh` file.
To reduce the number of unknowns and close the system we need closure relations for these equations. In this example, we use the
for the capillary pressure $`pc = p_n - p_w`$ and the relative permeabilities $`k_r\alpha`$.
The parameters for these relationships are specified in the `spatialparams.hh` file.
With the additional constraint that $`S_w + S_n = 1`$ we reduce the number of primary variables to two.
In this example we use the wetting phase pressure $`p_0`$ and the saturation of the nonwetting phase $`S_1`$ as primary variables. It is also possible to switch that formulation to the nonwetting pressure and the wetting saturation.
With the additional constraint that $`S_w + S_n = 1`$, the number of unknowns is reduced to two.
In this example we use the wetting phase pressure $`p_w`$ and the saturation of the nonwetting phase $`S_n`$ as primary variables. It is also possible to switch that formulation to the nonwetting pressure and the wetting saturation.
The two-dimensional model domain is 6m x 4m and contains a lens with a lower permeability and porosity. We read the initial values for the DNAPL saturation and the water pressure from a file.
The lens and the initial saturation can be seen in Figures 1 and 2.
...
...
@@ -53,7 +59,7 @@ DNAPL enters the model domain at the upper boundary between 1.75m ≤ x ≤ 2m w
In addition, the DNAPL is injected at a point source at x = 0.502m and y = 3.02m with a rate of 0.1 kg/s.
We discretize the equations with a cell-centered finite volume TPFA scheme in space and an implicit Euler scheme in time. We use Newton's method to solve the system of nonlinear equations.
The grid is adapitvely refined around the injection. The adaptive behaviour can be changed with input parameters in the `params.input` file.
The grid is adaptively refined around the injection. The adaptive behaviour can be changed with input parameters in the `params.input` file.