Nonlinear solve did not converge due to DIVERGED_FUNCTION_COUNT

> SNES Object: 1 MPI processes
>   type: newtonls
>   maximum iterations=50, maximum function evaluations=10000

  You need to set a much higher count for number of function evaluations, say 
-snes_max_funcs  1.e12

   Barry

We should probably increase the default in PETSc.




> On Sep 19, 2018, at 10:26 AM, Yingjie Wu <[email protected]> wrote:
> 
> Dear Petsc developer:            
> Hi, 
> 
> Thank you very much for your previous reply .
> I recently wrote an example of neutron diffusion, which shows that the 
> nonlinear residuals are gradually decreasing, but the program terminates in 
> the tenth step of the nonlinear step.The program output information is as 
> follows.
> 
> -snes_fd -pc_type lu -snes_view -snes_converged_reason -snes_monitor_cancel 
> -ksp_converged_reason -ksp_monitor_true_residual
> 
> iter = 0, SNES Function norm 0.999045
>     0 KSP preconditioned resid norm 1.143042621777e+02 true resid norm 
> 9.990445435144e-01 ||r(i)||/||b|| 1.000000000000e+00
>     1 KSP preconditioned resid norm 2.250033129078e-12 true resid norm 
> 3.772661181818e-14 ||r(i)||/||b|| 3.776269242757e-14
>   Linear solve converged due to CONVERGED_RTOL iterations 1
> iter = 1, SNES Function norm 0.863398
>     0 KSP preconditioned resid norm 3.176569252473e+00 true resid norm 
> 8.633978674995e-01 ||r(i)||/||b|| 1.000000000000e+00
>     1 KSP preconditioned resid norm 7.360979829512e-14 true resid norm 
> 1.835881897914e-14 ||r(i)||/||b|| 2.126345184557e-14
>   Linear solve converged due to CONVERGED_RTOL iterations 1
> iter = 2, SNES Function norm 0.217885
>     0 KSP preconditioned resid norm 5.796196387015e+01 true resid norm 
> 2.178851605144e-01 ||r(i)||/||b|| 1.000000000000e+00
>     1 KSP preconditioned resid norm 9.643306967470e-13 true resid norm 
> 3.884638811957e-14 ||r(i)||/||b|| 1.782883608405e-13
>   Linear solve converged due to CONVERGED_RTOL iterations 1
> iter = 3, SNES Function norm 0.217871
>     0 KSP preconditioned resid norm 3.792350832110e+01 true resid norm 
> 2.178711262680e-01 ||r(i)||/||b|| 1.000000000000e+00
>     1 KSP preconditioned resid norm 1.369102629758e-12 true resid norm 
> 1.632695466260e-13 ||r(i)||/||b|| 7.493858843196e-13
>   Linear solve converged due to CONVERGED_RTOL iterations 1
> iter = 4, SNES Function norm 0.217839
>     0 KSP preconditioned resid norm 2.467674567895e+01 true resid norm 
> 2.178387732479e-01 ||r(i)||/||b|| 1.000000000000e+00
>     1 KSP preconditioned resid norm 1.336018611676e-12 true resid norm 
> 2.369440379931e-14 ||r(i)||/||b|| 1.087703692324e-13
>   Linear solve converged due to CONVERGED_RTOL iterations 1
> iter = 5, SNES Function norm 0.217793
>     0 KSP preconditioned resid norm 1.325333377704e+01 true resid norm 
> 2.177933144217e-01 ||r(i)||/||b|| 1.000000000000e+00
>     1 KSP preconditioned resid norm 2.663121116220e-13 true resid norm 
> 6.399802508715e-15 ||r(i)||/||b|| 2.938475189519e-14
>   Linear solve converged due to CONVERGED_RTOL iterations 1
> iter = 6, SNES Function norm 0.217546
>     0 KSP preconditioned resid norm 8.654271429945e+00 true resid norm 
> 2.175456199462e-01 ||r(i)||/||b|| 1.000000000000e+00
>     1 KSP preconditioned resid norm 2.103027422078e-12 true resid norm 
> 1.896269373207e-14 ||r(i)||/||b|| 8.716651586351e-14
>   Linear solve converged due to CONVERGED_RTOL iterations 1
> iter = 7, SNES Function norm 0.217024
>     0 KSP preconditioned resid norm 5.238463146996e+00 true resid norm 
> 2.170240974179e-01 ||r(i)||/||b|| 1.000000000000e+00
>     1 KSP preconditioned resid norm 1.538914082201e-13 true resid norm 
> 1.398699322805e-14 ||r(i)||/||b|| 6.444903305426e-14
>   Linear solve converged due to CONVERGED_RTOL iterations 1
> iter = 8, SNES Function norm 0.215661
>     0 KSP preconditioned resid norm 3.380654310210e+00 true resid norm 
> 2.156611254980e-01 ||r(i)||/||b|| 1.000000000000e+00
>     1 KSP preconditioned resid norm 5.676163043758e-14 true resid norm 
> 2.209776803347e-15 ||r(i)||/||b|| 1.024652355979e-14
>   Linear solve converged due to CONVERGED_RTOL iterations 1
> iter = 9, SNES Function norm 0.213573
>     0 KSP preconditioned resid norm 1.833370627403e+00 true resid norm 
> 2.135728351107e-01 ||r(i)||/||b|| 1.000000000000e+00
>     1 KSP preconditioned resid norm 1.237094085371e-13 true resid norm 
> 3.167085089319e-15 ||r(i)||/||b|| 1.482906329205e-14
>   Linear solve converged due to CONVERGED_RTOL iterations 1
> iter = 10, SNES Function norm 0.206951
>     0 KSP preconditioned resid norm 1.011617991320e+00 true resid norm 
> 2.069514796799e-01 ||r(i)||/||b|| 1.000000000000e+00
>     1 KSP preconditioned resid norm 3.789650938118e-13 true resid norm 
> 5.695302032970e-14 ||r(i)||/||b|| 2.751998701231e-13
>   Linear solve converged due to CONVERGED_RTOL iterations 1
> Nonlinear solve did not converge due to DIVERGED_FUNCTION_COUNT iterations 10
> SNES Object: 1 MPI processes
>   type: newtonls
>   maximum iterations=50, maximum function evaluations=10000
>   tolerances: relative=1e-08, absolute=1e-50, solution=1e-08
>   total number of linear solver iterations=11
>   total number of function evaluations=10623
>   norm schedule ALWAYS
>   Jacobian is built using finite differences one column at a time
>   SNESLineSearch Object: 1 MPI processes
>     type: bt
>       interpolation: cubic
>       alpha=1.000000e-04
>     maxstep=1.000000e+08, minlambda=1.000000e-12
>     tolerances: relative=1.000000e-08, absolute=1.000000e-15, 
> lambda=1.000000e-08
>     maximum iterations=40
>   KSP Object: 1 MPI processes
>     type: gmres
>       restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization 
> with no iterative refinement
>       happy breakdown tolerance 1e-30
>     maximum iterations=10000, initial guess is zero
>     tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
>     left preconditioning
>     using PRECONDITIONED norm type for convergence test
>   PC Object: 1 MPI processes
>     type: lu
>       out-of-place factorization
>       tolerance for zero pivot 2.22045e-14
>       matrix ordering: nd
>       factor fill ratio given 5., needed 5.81047
>         Factored matrix follows:
>           Mat Object: 1 MPI processes
>             type: seqaij
>             rows=961, cols=961
>             package used to perform factorization: petsc
>             total: nonzeros=38169, allocated nonzeros=38169
>             total number of mallocs used during MatSetValues calls =0
>               not using I-node routines
>     linear system matrix = precond matrix:
>     Mat Object: 1 MPI processes
>       type: seqaij
>       rows=961, cols=961
>       total: nonzeros=6569, allocated nonzeros=15485
>       total number of mallocs used during MatSetValues calls =712
>         not using I-node routines
> 
> 
> 
> I don't know why the program was terminated. I really need your help.
> 
> Thanks,
> Yingjie
> 
> 
> 

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