[CIG-SHORT] not convergence for dynamic fault

Brad Aagaard baagaard at usgs.gov
Tue Apr 17 10:56:53 PDT 2012


Huihui,

There are a number of reasons why the friction may converge slowly. It 
is not an issue with the Jacobian that is the problem, but an issue with 
the estimate of slip associated with the change in tractions necessary 
to match the friction model. This nonlinear feedback depends on the 
initial conditions, including the shear and normal stress on the fault 
and the spatial variation of any parameters. If you describe your 
problem in more detail and include a simple diagram of your setup, we 
might be able to provide further guidance on how to improve convergence. 
Also please make sure you are using the latest release (v1.6.3).

Regards,
Brad


On 4/16/12 7:12 PM, 翁辉辉 wrote:
>
>
> Hi:
>
>     I find some convergence problems, When I use the dynamic fault in the subduction example(only use the fault_slabtop).
> It is the partial input about the fault below:
>
> [pylithapp.timedependent.implicit]
> solver = pylith.problems.SolverNonlinear
>
> [pylithapp.timedependent.interfaces]
> fault_slabtop = pylith.faults.FaultCohesiveDyn
> [pylithapp.timedependent.interfaces.fault_slabtop]
> label = fault_slabtop
> quadrature.cell = pylith.feassemble.FIATSimplex
> quadrature.cell.shape = line
> friction = pylith.friction.StaticFriction
> friction.label = Static friction
> friction.db_properties = spatialdata.spatialdb.UniformDB
> friction.db_properties.label = Static friction
> friction.db_properties.values = [friction-coefficient,cohesion]
> friction.db_properties.data = [5.0,0.0*MPa]
>
>    and for the initial stress I set the west boundry's displacement +10m,east boundry's displacement -10m. I use the default SNES linesearch method for the problems,though the  linear solve converges very well (norm<  1e-10),but the SNES fnorm decrease slowly(Fnorm>  1e-2) and some times the line search failed. When I set friction-coefficient very large or very small , it can almost convergence well.Then I think maybe the Jacobian is bad, but can I change that ?
>
> Thank you very much,
>
>   huihui weng
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>



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