@@ -13,7 +13,7 @@ To summarize the problems differ in:
...
@@ -13,7 +13,7 @@ To summarize the problems differ in:
* exercise1_1p_b: a one-phase compressible, stationary problem
* exercise1_1p_b: a one-phase compressible, stationary problem
* exercise1_1p_c: a one-phase compressible, instationary problem
* exercise1_1p_c: a one-phase compressible, instationary problem
The problem set-up for all three examples is always the same: It is a two dimensional problem and the domain is $`1 m x 1 m`$. It is a heterogeneous set-up with a lens in the middle of the domain which has a lower permeability ($`1\cdot 10^{-12} m^2`$ compared to $`1\cdot 10^{-10} m^2`$ in the rest of the domain).
The problem set-up for all three examples is always the same: It is a two dimensional problem and the domain is $`1 m`$ by $`1 m`$. It is a heterogeneous set-up with a lens in the middle of the domain which has a lower permeability ($`1\cdot 10^{-12} m^2`$ compared to $`1\cdot 10^{-10} m^2`$ in the rest of the domain).
@@ -47,6 +47,8 @@ The general structure of any main file in DuMux is:
...
@@ -47,6 +47,8 @@ The general structure of any main file in DuMux is:
// define the type tag for this problem
// define the type tag for this problem
usingTypeTag=TTAG(OnePCompressible);
usingTypeTag=TTAG(OnePCompressible);
```
```
The TypeTag is created in the `1pproblem.hh`. There you can see that it inherits from the __OneP__ and additionally from the __CCTpfaModel__ which defines the discretization method, which is in this case the cell-centered tpfa method.
* a gridmanager tries to create the grid either from a grid file or the input file
* a gridmanager tries to create the grid either from a grid file or the input file
```c++
```c++
...
@@ -179,3 +181,6 @@ For the incompressible one phase problem it is possible to also have an analytic
...
@@ -179,3 +181,6 @@ For the incompressible one phase problem it is possible to also have an analytic
```c++
```c++
// TODO: dumux-course-task
// TODO: dumux-course-task
```
```
For the analytic solution of your immiscible problem you need analytic solutions for the derivatives of the jacobian. For that we have a special local residual, the `OneincompressibleLocalResidual` which provides that. You just need to include that in your `1pproblem.hh` and use that instead of the `immisciblelocalresidual.hh` which is used as a standard for all immiscible models.
Additionally you need to set the differentiation method in the main file `exercise1_1p_a.cc` to analytic.