... ... @@ -13,7 +13,7 @@ To summarize the problems differ in: * exercise1_1p_b: a one-phase compressible, stationary 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: // define the type tag for this problem using TypeTag = 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 c++ ... ... @@ -179,3 +181,6 @@ For the incompressible one phase problem it is possible to also have an analytic c++ // 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.