0 TS dt 8.33333e-06 time 0. 1 TS dt 8.33333e-05 time 8.33333e-06 2 TS dt 0.000833333 time 9.16667e-05 3 TS dt 0.00833333 time 0.000925 4 TS dt 0.0132237 time 0.00925833 5 TS dt 0.0132566 time 0.022482 6 TS dt 0.0132919 time 0.0357387 7 TS dt 0.0133226 time 0.0490305 8 TS dt 0.0133482 time 0.0623531 9 TS dt 0.0133897 time 0.0757014 10 TS dt 0.0134319 time 0.0890911 11 TS dt 0.0134682 time 0.102523 12 TS dt 0.0134978 time 0.115991 13 TS dt 0.0135226 time 0.129489 14 TS dt 0.00489716 time 0.133803 15 TS dt 0.0100093 time 0.138701 16 TS dt 0.0135687 time 0.14871 17 TS dt 0.0136082 time 0.162279 18 TS dt 0.00446971 time 0.166008 19 TS dt 0.00866287 time 0.170477 20 TS dt 0.0135473 time 0.17914 21 TS dt 0.0136978 time 0.192687 22 TS dt 0.00526418 time 0.197319 23 TS dt 0.0107839 time 0.202584 24 TS dt 0.0137429 time 0.213367 25 TS dt 0.0137688 time 0.22711 26 TS dt 0.0037576 time 0.229776 27 TS dt 0.00611756 time 0.233534 28 TS dt 0.01188 time 0.239651 29 TS dt 0.0138528 time 0.251531 30 TS dt 0.0136247 time 0.265384 31 TS dt 0.00266463 time 0.26702 32 TS dt 0.00360038 time 0.269684 33 TS dt 0.00580701 time 0.273285 34 TS dt 0.0111362 time 0.279092 35 TS dt 0.013942 time 0.290228 36 TS dt 0.0138468 time 0.30417 TS Object: 1 MPI processes type: arkimex ARK IMEX 3 Stiff abscissa ct = 0.000000 0.871733 0.600000 1.000000 Fully implicit: no Stiffly accurate: yes Explicit first stage: yes FSAL property: yes Nonstiff abscissa c = 0.000000 0.871733 0.600000 1.000000 maximum steps=1000 maximum time=0.3 using relative error tolerance of 0.0001, using absolute error tolerance of 0.0001 TSAdapt Object: 1 MPI processes type: basic safety factor 0.9 extra safety factor after step rejection 0.5 clip fastest increase 10. clip fastest decrease 0.1 maximum allowed timestep 1e+20 minimum allowed timestep 1e-20 maximum solution absolute value to be ignored -1. SNES Object: 1 MPI processes type: newtonls maximum iterations=50, maximum function evaluations=10000 tolerances: relative=1e-08, absolute=1e-50, solution=1e-08 norm schedule ALWAYS 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: mg type is MULTIPLICATIVE, levels=3 cycles=v Cycles per PCApply=1 Not using Galerkin computed coarse grid matrices Coarse grid solver -- level ------------------------------- KSP Object: (mg_coarse_) 1 MPI processes type: preonly maximum iterations=10000, initial guess is zero tolerances: relative=1e-05, absolute=1e-50, divergence=10000. left preconditioning using NONE norm type for convergence test PC Object: (mg_coarse_) 1 MPI processes type: lu out-of-place factorization tolerance for zero pivot 2.22045e-14 using diagonal shift on blocks to prevent zero pivot [INBLOCKS] matrix ordering: nd factor fill ratio given 5., needed 1.63333 Factored matrix follows: Mat Object: 1 MPI processes type: seqaij rows=60, cols=60 package used to perform factorization: petsc total: nonzeros=294, allocated nonzeros=294 not using I-node routines linear system matrix = precond matrix: Mat Object: 1 MPI processes type: seqaij rows=60, cols=60 total: nonzeros=180, allocated nonzeros=180 not using I-node routines Down solver (pre-smoother) on level 1 ------------------------------- KSP Object: (mg_levels_1_) 1 MPI processes type: chebyshev eigenvalue estimates used: min = 0.1, max = 1.1 eigenvalues estimate via gmres min 1., max 1. eigenvalues estimated using gmres with translations [0. 0.1; 0. 1.1] KSP Object: (mg_levels_1_esteig_) 1 MPI processes type: gmres restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement happy breakdown tolerance 1e-30 maximum iterations=10, initial guess is zero tolerances: relative=1e-12, absolute=1e-50, divergence=10000. left preconditioning using PRECONDITIONED norm type for convergence test estimating eigenvalues using noisy right hand side maximum iterations=3, nonzero initial guess tolerances: relative=1e-05, absolute=1e-50, divergence=10000. left preconditioning using NONE norm type for convergence test PC Object: (mg_levels_1_) 1 MPI processes type: sor type = local_symmetric, iterations = 1, local iterations = 1, omega = 1. linear system matrix = precond matrix: Mat Object: 1 MPI processes type: seqaij rows=120, cols=120 total: nonzeros=360, allocated nonzeros=360 not using I-node routines Up solver (post-smoother) same as down solver (pre-smoother) Down solver (pre-smoother) on level 2 ------------------------------- KSP Object: (mg_levels_2_) 1 MPI processes type: chebyshev eigenvalue estimates used: min = 0.1, max = 1.1 eigenvalues estimate via gmres min 1., max 1. eigenvalues estimated using gmres with translations [0. 0.1; 0. 1.1] KSP Object: (mg_levels_2_esteig_) 1 MPI processes type: gmres restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement happy breakdown tolerance 1e-30 maximum iterations=10, initial guess is zero tolerances: relative=1e-12, absolute=1e-50, divergence=10000. left preconditioning using PRECONDITIONED norm type for convergence test estimating eigenvalues using noisy right hand side maximum iterations=3, nonzero initial guess tolerances: relative=1e-05, absolute=1e-50, divergence=10000. left preconditioning using NONE norm type for convergence test PC Object: (mg_levels_2_) 1 MPI processes type: sor type = local_symmetric, iterations = 1, local iterations = 1, omega = 1. linear system matrix = precond matrix: Mat Object: 1 MPI processes type: seqaij rows=240, cols=240 total: nonzeros=720, allocated nonzeros=720 not using I-node routines Up solver (post-smoother) same as down solver (pre-smoother) linear system matrix = precond matrix: Mat Object: 1 MPI processes type: seqaij rows=240, cols=240 total: nonzeros=720, allocated nonzeros=720 not using I-node routines