[petsc-users] SNES divergence

[Barry Smith]

On Jun 17, 2014, at 2:30 PM, Sang pham van <pvsang002 at gmail.com> wrote:

> Thanks Barry,
> 
> To refine the grid, I just put more points in the direction. For both fine and coarse meshes, I used simple initial guess (say constant values in whole domain for all variables). 
> 
> By using grid sequencing, is the finest mesh is the one I first input the solver?

  No, you pass in the coarse one.
> 
> Can you let me know what options should I use to have pure Newton method?

   Not sure what you mean by pure Newton method, maybe without grid sequencing? It simply may not be possible to get convergence from a “poor” initial guess. One should always use grid sequencing if possible.

   Barry

> 
> S.
> 
> 
> On Tue, Jun 17, 2014 at 3:20 PM, Barry Smith <bsmith at mcs.anl.gov> wrote:
> 
> On Jun 17, 2014, at 2:12 PM, Sang pham van <pvsang002 at gmail.com> wrote:
> 
> > Hi,
> >
> > I am using DM structure and SNES to solve a 3D problem. In the problem I have 3 variables.
> >
> > I got SNES converged with a grid. Obtain result are physically right. However when I refine the grid, SNES does not always converge,
> 
>    With the refined grid how are you starting the solution? Do you use the interpolated solution from the coarser grid (called grid sequencing) or just some “not good” initial guess?
> 
> > the reason of divergence is line search fail or linear solver failed. (I also tried other type of SNES, line search seems to be the one best fits my problem)
> >
> > Can you please give me a suggestion to figure out the problem with my solver? What options should I use to have pure Newton method in SNES? Is there any advance option I can use with line search to improve SNES convergence.
> >
> 
>    You should use grid sequencing, not only does it get convergence when you may not otherwise get it but it will also solve the problem faster. With PETSc DM you can use -snes_grid_sequence n  or SNESSetGridSequence() in the code to do n levels of grid sequencing.
> 
>    Barry
> 
> > Thank you very much.
> >
> > Minh.
> >
> 
>