diff --git a/src/pseudotransient.jl b/src/pseudotransient.jl index debd4b3b9..8e70f2350 100644 --- a/src/pseudotransient.jl +++ b/src/pseudotransient.jl @@ -9,8 +9,26 @@ please see the paper: [Coffey, Todd S. and Kelley, C. T. and Keyes, David E. (20 SIAM Journal on Scientific Computing,25, 553-569.](https://doi.org/10.1137/S106482750241044X) ### Keyword Arguments - -- `alpha_initial` : the initial pseudo time step. it defaults to 1e-3. If it is small, you are going to need more iterations to converge. + - `autodiff`: determines the backend used for the Jacobian. Note that this argument is + ignored if an analytical Jacobian is passed, as that will be used instead. Defaults to + `nothing` which means that a default is selected according to the problem specification! + Valid choices are types from ADTypes.jl. + - `concrete_jac`: whether to build a concrete Jacobian. If a Krylov-subspace method is used, + then the Jacobian will not be constructed and instead direct Jacobian-vector products + `J*v` are computed using forward-mode automatic differentiation or finite differencing + tricks (without ever constructing the Jacobian). However, if the Jacobian is still needed, + for example for a preconditioner, `concrete_jac = true` can be passed in order to force + the construction of the Jacobian. + - `linsolve`: the [LinearSolve.jl](https://github.com/SciML/LinearSolve.jl) used for the + linear solves within the Newton method. Defaults to `nothing`, which means it uses the + LinearSolve.jl default algorithm choice. For more information on available algorithm + choices, see the [LinearSolve.jl documentation](https://docs.sciml.ai/LinearSolve/stable/). + - `precs`: the choice of preconditioners for the linear solver. Defaults to using no + preconditioners. For more information on specifying preconditioners for LinearSolve + algorithms, consult the + [LinearSolve.jl documentation](https://docs.sciml.ai/LinearSolve/stable/). + - `alpha_initial` : the initial pseudo time step. it defaults to 1e-3. If it is small, + you are going to need more iterations to converge but it can be more stable.