This could be useful to solve Euler equation with a DG method that
employs a Riemann solver to compute the numerical fluxes
(discontinuous at element faces-edges) without dealing with Godunov
fluxes to compute the jacobian... Am I wrong?

Lorenzo

2008/2/1, Benjamin Kirk <[EMAIL PROTECTED]>:
>
> > Let me rewrite the expression you wrote as
> >
> > J*v = (F(u+epsilon*v)-F(u)) / epsilon
> >
> > Where epsilon is a small perturbation and F(u) is the nonlinear residual
> > function and J is the jacobian matrix of the nonlinear system. The above
> > formula compute the action of a Jacobian on a given vector, or more
> > specifically the Krylov vector if you are using say GMRES or CG to solve
> > your system.
>
>
> That's absolutely true.  To expound a little more, by definition
>
> F = F(U)
> J = dF/dU
>
> J*v = [dF/dU]*v  (1)
>
> which is simply the directional derivative of F (in the direction of v.  As
> specified above, you can approximate this matrix-vector product as
>
> J*v ~ (F(u+epsilon*v)-F(u)) / epsilon (2)
>
> In Krylov subspace methods the operation (1) occurs repeatedly at each
> iteration.  So, if you are willing to approximate it, you can use (2)
> instead.
>
> There are a couple of reasons why you might want to do this:
>  - obviously, this finite difference of vectors eliminates the need
>    to store J, hence "matrix free"
>  - not to whine, but sometimes computing an accurate J is *hard* and/or
>    computationally intensive.  It can be error-prone. Using (2) you get
>
> Now of course any hard problem will need preconditioning in the Krylov
> solver.  You can accomplish this in several ways...  One would be to build
> an approximate Jacobian and use ILU or the like.  Now you have one matrix
> instead of two.  Also, this could be a much simpler matrix (block-diagonal
> for certain cases), thus limiting the requirements.
>
> But there are other options too, allowing for a matrix free preconditioner
> as well.  These include Gauss-Siedel, Geometric multigrid, another Krylov
> technique, etc...
>
> -Ben
>
>
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