lid velocity = 0.00591716, prandtl # = 1., grashof # = 1. 0 SNES Function norm 7.886953101160e-02 0 KSP Residual norm 1.746381225827e-01 1 KSP Residual norm 7.004704630590e-02 2 KSP Residual norm 4.385856078301e-02 3 KSP Residual norm 2.991734996742e-02 4 KSP Residual norm 1.541826196440e-02 5 KSP Residual norm 6.602560554899e-03 6 KSP Residual norm 2.694428161302e-03 7 KSP Residual norm 1.622977097479e-03 8 KSP Residual norm 8.474224154098e-04 9 KSP Residual norm 3.360585541731e-04 10 KSP Residual norm 1.753532737046e-04 11 KSP Residual norm 7.356382477417e-05 12 KSP Residual norm 3.555027783012e-05 13 KSP Residual norm 2.522543733667e-05 14 KSP Residual norm 1.650061977888e-05 15 KSP Residual norm 1.317943743207e-05 16 KSP Residual norm 5.987224752271e-06 17 KSP Residual norm 2.746393568458e-06 18 KSP Residual norm 1.161746985368e-06 1 SNES Function norm 7.905777117971e-06 0 KSP Residual norm 7.310793191220e-06 1 KSP Residual norm 4.274292904265e-06 2 KSP Residual norm 2.554221716108e-06 3 KSP Residual norm 1.805162190427e-06 4 KSP Residual norm 1.302059663179e-06 5 KSP Residual norm 6.900263715957e-07 6 KSP Residual norm 3.865286574893e-07 7 KSP Residual norm 2.011026678421e-07 8 KSP Residual norm 1.279189993428e-07 9 KSP Residual norm 7.486230255819e-08 10 KSP Residual norm 4.486174933669e-08 11 KSP Residual norm 2.718057584265e-08 12 KSP Residual norm 1.522342632160e-08 13 KSP Residual norm 1.092746533309e-08 14 KSP Residual norm 4.600296733527e-09 15 KSP Residual norm 2.138995973823e-09 16 KSP Residual norm 1.188059540268e-09 17 KSP Residual norm 9.983011502733e-10 18 KSP Residual norm 8.037619089070e-10 19 KSP Residual norm 4.531479206633e-10 20 KSP Residual norm 2.327066112499e-10 21 KSP Residual norm 1.466975986836e-10 22 KSP Residual norm 1.046387755681e-10 23 KSP Residual norm 4.595843286107e-11 2 SNES Function norm 1.464393747580e-10 SNES Object: 1 MPI process 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=41 total number of function evaluations=3 norm schedule ALWAYS Jacobian is built using colored finite differences on a DMDA SNESLineSearch Object: 1 MPI process type: bt interpolation: cubic alpha=1.000000e-04 maxlambda=1.000000e+00, minlambda=1.000000e-12 tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08 maximum iterations=40 KSP Object: 1 MPI process 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 process type: hypre HYPRE Euclid preconditioning default factorization levels drop tolerance 0.1 use Block-Jacobi? 0 linear system matrix, which is also used to construct the preconditioner: Mat Object: 1 MPI process type: seqaij rows=676, cols=676, bs=4 total: nonzeros=12688, allocated nonzeros=12688 total number of mallocs used during MatSetValues calls=0 using I-node routines: found 169 nodes, limit used is 5 Number of SNES iterations = 2