51 research outputs found
Parallel Schwarz wave form relaxation algorithm for an n-dimensional semilinear heat equation
We present in this paper a proof of well-posedness and convergence for the parallel Schwarz Waveform Relaxation Algorithm adapted to an N-dimensional semilinear heat equation. Since the equation we study is an evolution one, each subproblem at each step has its own local existence time, we then determine a common existence time for every problem in any subdomain at any step. We also introduce a new technique: Exponential Decay Error Estimates, to prove the convergence of the Schwarz Methods, with multisubdomains, and then apply it to our problem
Nonlinear Preconditioning: How to use a Nonlinear Schwarz Method to Precondition Newton's Method
For linear problems, domain decomposition methods can be used directly as
iterative solvers, but also as preconditioners for Krylov methods. In practice,
Krylov acceleration is almost always used, since the Krylov method finds a much
better residual polynomial than the stationary iteration, and thus converges
much faster. We show in this paper that also for non-linear problems, domain
decomposition methods can either be used directly as iterative solvers, or one
can use them as preconditioners for Newton's method. For the concrete case of
the parallel Schwarz method, we show that we obtain a preconditioner we call
RASPEN (Restricted Additive Schwarz Preconditioned Exact Newton) which is
similar to ASPIN (Additive Schwarz Preconditioned Inexact Newton), but with all
components directly defined by the iterative method. This has the advantage
that RASPEN already converges when used as an iterative solver, in contrast to
ASPIN, and we thus get a substantially better preconditioner for Newton's
method. The iterative construction also allows us to naturally define a coarse
correction using the multigrid full approximation scheme, which leads to a
convergent two level non-linear iterative domain decomposition method and a two
level RASPEN non-linear preconditioner. We illustrate our findings with
numerical results on the Forchheimer equation and a non-linear diffusion
problem
Optimized Schwarz Waveform Relaxation for Advection Reaction Diffusion Equations in Two Dimensions
Optimized Schwarz Waveform Relaxation methods have been developed over the
last decade for the parallel solution of evolution problems. They are based on
a decomposition in space and an iteration, where only subproblems in space-time
need to be solved. Each subproblem can be simulated using an adapted numerical
method, for example with local time stepping, or one can even use a different
model in different subdomains, which makes these methods very suitable also
from a modeling point of view. For rapid convergence however, it is important
to use effective transmission conditions between the space-time subdomains, and
for best performance, these transmission conditions need to take the physics of
the underlying evolution problem into account. The optimization of these
transmission conditions leads to a mathematically hard best approximation
problem of homographic type. We study in this paper in detail this problem for
the case of linear advection reaction diffusion equations in two spatial
dimensions. We prove comprehensively best approximation results for
transmission conditions of Robin and Ventcel type. We give for each case closed
form asymptotic values for the parameters, which guarantee asymptotically best
performance of the iterative methods. We finally show extensive numerical
experiments, and we measure performance corresponding to our analysisComment: 42 page
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