Do you think any kind of instability could arise from the fact that I'm trying to simulate a stationary problem when actually it should be transient? I recall that once I've made a project (flow around a cylinder) where the clue to know if the grid was sufficiently refined to go for the non-stationary simulation was to simulate a stationary problem and verify instabilities in the wake past the cylinder, do you think that could be the reason why my solution is worse with more refined grids?
On Tue, Oct 21, 2014 at 12:37 PM, Rodrigo Broggi <rbrogg...@gmail.com> wrote: > Another thing that I've not mentioned earlier is that to validate the > results I've followed two separated approaches one using standart FEM and > the other using mixed hybrid FEM and both presents the same issues but they > actually "agree" for the coarse solutions.... > > > > On Tue, Oct 21, 2014 at 12:33 PM, Rodrigo Broggi <rbrogg...@gmail.com> > wrote: > >> >That indicates that the linear solve is not a >> >problem. -ksp_monitor_true_residual and/or -ksp_monitor_singular_value >> >can give you more confidence that the linear system is solved >> >successfully. >> >> >> I've run through the troubleshooting list and actually got some insights: >> - It seems like I have an ill conditioned matrix (for a small grid (40 >> d.o.f) the conditioning number is around 5.e8 and it grows linearly with >> the number of d.o.f) - I've got this result by running with (-pc_type >> svd -pc_svd_monitor) options. Here is a typical output of a Newton >> iteration (~40 d.o.f): >> >> SVD: condition number 1.336170852801e+09, 0 of 82 singular values are >> (nearly) zero >> SVD: smallest singular values: 1.000000000000e+00 1.000000000000e+00 >> 1.000000000000e+00 1.136056163817e+02 4.692147825673e+02 >> SVD: largest singular values : 1.275661165756e+09 1.298030680428e+09 >> 1.315681925775e+09 1.328427779148e+09 1.336170852801e+09 >> >> - The preconditioning seems to be effective since even the reasonable >> solutions achieved with coarse grids are not achieved as well with >> (-pc_type none) and there is a Mbig difference between true_residual and >> the preconditioned one when I've run with (-ksp_monitor_true_residual); >> >> - Something weird is that using direct solvers I didn't get any >> enhancements, actually it has worsened for some cases: it has given >> wrong solutions for coarser grids. >> >> - I am implementing the Newton's method manually using the technique >> showed in the Navier-Stokes example (even though my problem is on fluid >> structure interaction) in the site and I was asking myself if the >> tightening of tolerance for the linear solver at each step of Newton's >> method is actually important, it doesn't change my live but I get similar >> results with and without it and as the tolerance decreases the linear >> solver is not capable to converge and I get a bunch of iterations not >> needed, have I explained myself?! >> >> >> >Define "worse" >> >> My problem is about the interaction between currents and a cable and >> physically I expect my solution to have a certain profile and I actually >> have it for coarse grids (until 40 dof) but as I refine the grid the >> solution either not converges or converges to absurd results with a lot of >> instabilities and jumps. It made me greatly consider the possibility that >> you mentioned about scale-dependent nonlinearities... >> >> Thanks, >> >> Rodrigo Broggi >> >> >> >> >> >> >> On Sun, Oct 19, 2014 at 7:02 PM, Jed Brown <j...@jedbrown.org> wrote: >> >>> Rodrigo Broggi <rbrogg...@gmail.com> writes: >>> >>> > With this other options it actually works but I suspect the solver is >>> not >>> > really changing since the residual of all iterations of Newton's >>> method are >>> > the same between all solvers (direct or not). >>> >>> That indicates that the linear solve is not a >>> problem. -ksp_monitor_true_residual and/or -ksp_monitor_singular_value >>> can give you more confidence that the linear system is solved >>> successfully. >>> >>> Here are some solver debugging tips for nonlinear solvers: >>> >>> >>> https://scicomp.stackexchange.com/questions/30/why-is-newtons-method-not-converging >>> >>> > My issue is that the solution is worse whenever I increase the degrees >>> of >>> > freedom, maybe there is some singularities that I am not aware of... >>> >>> Define "worse". >>> >>> Nonlinearities are scale-dependent, so increasing resolution could be >>> making the problem fundamentally more nonlinear. Sometimes grid >>> sequencing or some other continuation is necessary to solve challenging >>> nonlinear problems. But try the diagnostics and tricks in the link. >>> >> >> > ------------------------------------------------------------------------------ Comprehensive Server Monitoring with Site24x7. Monitor 10 servers for $9/Month. Get alerted through email, SMS, voice calls or mobile push notifications. Take corrective actions from your mobile device. http://p.sf.net/sfu/Zoho _______________________________________________ Libmesh-users mailing list Libmesh-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/libmesh-users
