It seems you are correct. In theory, the problem should not be over constrained. It is 1/4 of a simple hollow cylinder geometry with rotational symmetry around the z-axis. I restrict movement completely on the upper and lower (z) end as well as movement in x- and y- direction respectively on the symmetry planes. I am not completely sure what I am looking at with the output of -dm_petscsection_view. But these lines struck me as odd:
(5167) dim 3 offset 0 constrained 0 1 1 2 (5168) dim 3 offset 6 constrained 0 1 1 2 . . . (5262) dim 3 offset 0 constrained 0 0 1 2 (5263) dim 3 offset 6 constrained 0 0 1 2 It seems that vertices that are part of the closures of both Face Sets get restricted twice in their respective degree of freedom. This does however also happen when restricting movement in x- direction only for upper and lower faces. In that case without the solver producing an error: (20770) dim 3 offset 24 constrained 0 0 (20771) dim 3 offset 30 constrained 0 0 (20772) dim 3 offset 36 constrained 0 0 (20773) dim 3 offset 42 constrained 0 0 Thanks, Max > On 6 Mar 2017, at 14:43, Matthew Knepley <[email protected]> wrote: > > On Mon, Mar 6, 2017 at 8:38 AM, Maximilian Hartig <[email protected] > <mailto:[email protected]>> wrote: > Of course, please find the source as well as the mesh attached below. I run > with: > > -def_petscspace_order 2 -vel_petscspace_order 2 -snes_monitor > -snes_converged_reason -ksp_converged_reason -ksp_monitor _true_residual > -ksp_type fgmres -pc_type sor > > This sounds like over-constraining a point to me. I will try and run it soon, > but I have a full schedule this week. The easiest > way to see if this is happening should be to print out the Section that gets > made > > -dm_petscsection_view > > Thanks, > > Matt > > Thanks, > Max > > > > >> On 4 Mar 2017, at 11:34, Sander Arens <[email protected] >> <mailto:[email protected]>> wrote: >> >> Hmm, strange you also get the error in serial. Can you maybe send a minimal >> working which demonstrates the error? >> >> Thanks, >> Sander >> >> On 3 March 2017 at 23:07, Maximilian Hartig <[email protected] >> <mailto:[email protected]>> wrote: >> Yes Sander, your assessment is correct. I use DMPlex and specify the BC >> using DMLabel. I do however get this error also when running in serial. >> >> Thanks, >> Max >> >>> On 3 Mar 2017, at 22:14, Matthew Knepley <[email protected] >>> <mailto:[email protected]>> wrote: >>> >>> On Fri, Mar 3, 2017 at 12:56 PM, Sander Arens <[email protected] >>> <mailto:[email protected]>> wrote: >>> Max, >>> >>> I'm assuming you use DMPlex for your mesh? If so, did you only specify the >>> faces in the DMLabel (and not vertices or edges). Do you get this error >>> only in parallel? >>> >>> If so, I can confirm this bug. I submitted a pull request for this >>> yesterday. >>> >>> Yep, I saw Sander's pull request. I will get in merged in tomorrow when I >>> get home to Houston. >>> >>> Thanks, >>> >>> Matt >>> >>> On 3 March 2017 at 18:43, Lukas van de Wiel <[email protected] >>> <mailto:[email protected]>> wrote: >>> You have apparently preallocated the non-zeroes of you matrix, and the room >>> was insufficient to accommodate all your equations. >>> >>> What happened after you tried: >>> >>> MatSetOption(A, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_FALSE) >>> >>> >>> Cheers >>> Lukas >>> >>> On Fri, Mar 3, 2017 at 6:37 PM, Maximilian Hartig <[email protected] >>> <mailto:[email protected]>> wrote: >>> Hello, >>> >>> I am working on a transient structural FEM code with PETSc. I managed to >>> create a slow but functioning program with the use of petscFE and a TS >>> solver. The code runs fine until I try to restrict movement in all three >>> spatial directions for one face. I then get the error which is attached >>> below. >>> So apparently DMPlexMatSetClosure tries to write/read beyond what was >>> priorly allocated. I do however not call MatSeqAIJSetPreallocation myself >>> in the code. So I’m unsure where to start looking for the bug. In my >>> understanding, PETSc should know from the DM how much space to allocate. >>> Could you kindly give me a hint? >>> >>> Thanks, >>> >>> Max >>> >>> 0 SNES Function norm 2.508668036663e-06 >>> [0]PETSC ERROR: --------------------- Error Message >>> -------------------------------------------------------------- >>> [0]PETSC ERROR: Argument out of range >>> [0]PETSC ERROR: New nonzero at (41754,5) caused a malloc >>> Use MatSetOption(A, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_FALSE) to turn >>> off this check >>> [0]PETSC ERROR: See http://www.mcs.anl.gov/petsc/documentation/faq.html >>> <http://www.mcs.anl.gov/petsc/documentation/faq.html> for trouble shooting. >>> [0]PETSC ERROR: Petsc Development GIT revision: v3.7.5-3223-g99077fc GIT >>> Date: 2017-02-28 13:41:43 -0600 >>> [0]PETSC ERROR: ./S3 on a arch-linux-gnu-intel named XXXXXXX by hartig Fri >>> Mar 3 17:55:57 2017 >>> [0]PETSC ERROR: Configure options PETSC_ARCH=arch-linux-gnu-intel >>> --with-cc=/opt/intel/compilers_and_libraries/linux/mpi/intel64/bin/mpiicc >>> --with-cxx=/opt/intel/compilers_and_libraries/linux/mpi/intel64/bin/mpiicpc >>> --with-fc=/opt/intel/compilers_and_libraries/linux/mpi/intel64/bin/mpiifort >>> --download-ml >>> [0]PETSC ERROR: #1 MatSetValues_SeqAIJ() line 455 in >>> /home/hartig/petsc/src/mat/impls/aij/seq/aij.c >>> [0]PETSC ERROR: #2 MatSetValues() line 1270 in >>> /home/hartig/petsc/src/mat/interface/matrix.c >>> [0]PETSC ERROR: [0]ERROR in DMPlexMatSetClosure >>> [0]mat for sieve point 60 >>> [0]mat row indices[0] = 41754 >>> [0]mat row indices[1] = 41755 >>> [0]mat row indices[2] = 41756 >>> [0]mat row indices[3] = 41760 >>> [0]mat row indices[4] = 41761 >>> [0]mat row indices[5] = 41762 >>> [0]mat row indices[6] = 41766 >>> [0]mat row indices[7] = -41768 >>> [0]mat row indices[8] = 41767 >>> [0]mat row indices[9] = 41771 >>> [0]mat row indices[10] = -41773 >>> [0]mat row indices[11] = 41772 >>> [0]mat row indices[12] = 41776 >>> [0]mat row indices[13] = 41777 >>> [0]mat row indices[14] = 41778 >>> [0]mat row indices[15] = 41782 >>> [0]mat row indices[16] = -41784 >>> [0]mat row indices[17] = 41783 >>> [0]mat row indices[18] = 261 >>> [0]mat row indices[19] = -263 >>> [0]mat row indices[20] = 262 >>> [0]mat row indices[21] = 24318 >>> [0]mat row indices[22] = 24319 >>> [0]mat row indices[23] = 24320 >>> [0]mat row indices[24] = -7 >>> [0]mat row indices[25] = -8 >>> [0]mat row indices[26] = 6 >>> [0]mat row indices[27] = 1630 >>> [0]mat row indices[28] = -1632 >>> [0]mat row indices[29] = 1631 >>> [0]mat row indices[30] = 41757 >>> [0]mat row indices[31] = 41758 >>> [0]mat row indices[32] = 41759 >>> [0]mat row indices[33] = 41763 >>> [0]mat row indices[34] = 41764 >>> [0]mat row indices[35] = 41765 >>> [0]mat row indices[36] = 41768 >>> [0]mat row indices[37] = 41769 >>> [0]mat row indices[38] = 41770 >>> [0]mat row indices[39] = 41773 >>> [0]mat row indices[40] = 41774 >>> [0]mat row indices[41] = 41775 >>> [0]mat row indices[42] = 41779 >>> [0]mat row indices[43] = 41780 >>> [0]mat row indices[44] = 41781 >>> [0]mat row indices[45] = 41784 >>> [0]mat row indices[46] = 41785 >>> [0]mat row indices[47] = 41786 >>> [0]mat row indices[48] = 263 >>> [0]mat row indices[49] = 264 >>> [0]mat row indices[50] = 265 >>> [0]mat row indices[51] = 24321 >>> [0]mat row indices[52] = 24322 >>> [0]mat row indices[53] = 24323 >>> [0]mat row indices[54] = 5 >>> [0]mat row indices[55] = 6 >>> [0]mat row indices[56] = 7 >>> [0]mat row indices[57] = 1632 >>> [0]mat row indices[58] = 1633 >>> [0]mat row indices[59] = 1634 >>> [0] 1.29801 0.0998428 -0.275225 1.18171 -0.0093323 0.055045 1.18146 >>> 0.00525527 -0.11009 -0.588378 0.264666 -0.0275225 -2.39586 -0.210511 >>> 0.22018 -0.621071 0.0500786 0.137613 -0.180869 -0.0974804 0.0344031 >>> -0.0302673 -0.09 0. -0.145175 -0.00383346 -0.00688063 0.300442 -0.00868618 >>> -0.0275225 8.34577e-11 0. 0. 4.17288e-11 0. 0. 4.17288e-11 0. 0. >>> 4.17288e-11 0. 0. 4.17288e-11 0. 0. 2.08644e-11 0. 0. -1.04322e-11 0. 0. >>> -1.04322e-11 0. 0. -1.56483e-11 0. 0. -1.56483e-11 0. 0. >>> [0] 0.0998428 0.590663 -0.0320009 0.0270594 0.360043 0.0297282 -0.0965489 >>> 0.270936 -0.0652389 0.32647 -0.171351 -0.00845384 -0.206902 -0.657189 >>> 0.0279137 0.0500786 -0.197561 -0.0160508 -0.12748 -0.138996 0.0408591 -0.06 >>> -0.105935 0.0192308 0.00161757 -0.0361182 0.0042968 -0.0141372 0.0855084 >>> -0.000284088 0. 8.34577e-11 0. 0. 4.17288e-11 0. 0. 4.17288e-11 0. 0. >>> 4.17288e-11 0. 0. 4.17288e-11 0. 0. 2.08644e-11 0. 0. -1.04322e-11 0. 0. >>> -1.04322e-11 0. 0. -1.56483e-11 0. 0. -1.56483e-11 0. >>> [0] -0.275225 -0.0320009 0.527521 -0.055045 0.0285918 0.234796 -0.165135 >>> -0.0658071 0.322754 0.0275225 -0.0207062 -0.114921 0.33027 0.0418706 >>> -0.678455 0.137613 -0.0160508 -0.235826 0.0344031 0.0312437 -0.0845583 0. >>> 0.0288462 -0.0302673 0.00688063 0.00443884 -0.0268103 -0.0412838 >>> -0.000426133 0.0857668 0. 0. 8.34577e-11 0. 0. 4.17288e-11 0. 0. >>> 4.17288e-11 0. 0. 4.17288e-11 0. 0. 4.17288e-11 0. 0. 2.08644e-11 0. 0. >>> -1.04322e-11 0. 0. -1.04322e-11 0. 0. -1.56483e-11 0. 0. -1.56483e-11 >>> [0] 1.18171 0.0270594 -0.055045 1.29651 -0.0821157 0.275225 1.1468 >>> -0.0675282 0.11009 -0.637271 0.141058 -0.137613 -2.37741 -0.0649437 >>> -0.22018 -0.588378 0.24647 0.0275225 -0.140937 -0.00838243 0.00688063 >>> -0.0175533 -0.09 0. -0.16373 -0.0747355 -0.0344031 0.300255 -0.026882 >>> 0.0275225 4.17288e-11 0. 0. 8.34577e-11 0. 0. 4.17288e-11 0. 0. 2.08644e-11 >>> 0. 0. 4.17288e-11 0. 0. 4.17288e-11 0. 0. -1.56483e-11 0. 0. -1.04322e-11 >>> 0. 0. -1.04322e-11 0. 0. -1.56483e-11 0. 0. >>> [0] -0.0093323 0.360043 0.0285918 -0.0821157 0.585404 -0.0263191 -0.205724 >>> 0.149643 0.0652389 0.141058 -0.254263 0.0452109 0.011448 -0.592598 >>> -0.0279137 0.344666 -0.171351 -0.0207062 0.00616654 -0.0212853 -0.0115868 >>> -0.06 -0.0614365 -0.0192308 -0.104736 -0.0790071 -0.0335691 -0.041431 >>> 0.084851 0.000284088 0. 4.17288e-11 0. 0. 8.34577e-11 0. 0. 4.17288e-11 0. >>> 0. 2.08644e-11 0. 0. 4.17288e-11 0. 0. 4.17288e-11 0. 0. -1.56483e-11 0. 0. >>> -1.04322e-11 0. 0. -1.04322e-11 0. 0. -1.56483e-11 0. >>> [0] 0.055045 0.0297282 0.234796 0.275225 -0.0263191 0.526019 0.165135 >>> 0.0658071 0.288099 -0.137613 0.0452109 -0.252027 -0.33027 -0.0418706 >>> -0.660001 -0.0275225 -0.00845384 -0.114921 -0.00688063 -0.0117288 >>> -0.0225723 0. -0.0288462 -0.0175533 -0.0344031 -0.0239537 -0.0674185 >>> 0.0412838 0.000426133 0.085579 0. 0. 4.17288e-11 0. 0. 8.34577e-11 0. 0. >>> 4.17288e-11 0. 0. 2.08644e-11 0. 0. 4.17288e-11 0. 0. 4.17288e-11 0. 0. >>> -1.56483e-11 0. 0. -1.04322e-11 0. 0. -1.04322e-11 0. 0. -1.56483e-11 >>> [0] 1.18146 -0.0965489 -0.165135 1.1468 -0.205724 0.165135 3.70665 0.626591 >>> 3.1198e-14 -2.37741 0.0332522 -0.275225 -2.44501 -0.417727 4.66207e-17 >>> -2.39586 -0.148706 0.275225 0.283843 0.0476669 0.0137613 0.00972927 0.06 0. >>> 0.288268 0.0567649 -0.0137613 0.601523 0.0444318 -1.2387e-17 4.17288e-11 0. >>> 0. 4.17288e-11 0. 0. 8.34577e-11 0. 0. 4.17288e-11 0. 0. 2.08644e-11 0. 0. >>> 4.17288e-11 0. 0. -1.04322e-11 0. 0. -1.56483e-11 0. 0. -1.04322e-11 0. 0. >>> -1.56483e-11 0. 0. >>> [0] 0.00525527 0.270936 -0.0658071 -0.0675282 0.149643 0.0658071 0.626591 >>> 1.29259 -0.02916 -0.0867478 -0.592598 -0.0413024 -0.417727 -0.829208 >>> 6.46318e-18 -0.268706 -0.657189 0.0413024 0.03402 0.0715157 0.0179272 0.04 >>> 0.0340524 1.77708e-18 0.0704117 0.0870061 0.0112328 0.0644318 0.17325 >>> -1.41666e-19 0. 4.17288e-11 0. 0. 4.17288e-11 0. 0. 8.34577e-11 0. 0. >>> 4.17288e-11 0. 0. 2.08644e-11 0. 0. 4.17288e-11 0. 0. -1.04322e-11 0. 0. >>> -1.56483e-11 0. 0. -1.04322e-11 0. 0. -1.56483e-11 0. >>> [0] -0.11009 -0.0652389 0.322754 0.11009 0.0652389 0.288099 3.12405e-14 >>> -0.02916 1.21876 -0.275225 -0.0284819 -0.660001 9.50032e-17 9.55728e-18 >>> -0.727604 0.275225 0.0284819 -0.678455 0.055045 0.0279687 0.0250605 0. >>> 1.71863e-18 0.00972927 -0.055045 0.00119132 0.0294863 -1.47451e-17 >>> -1.90582e-19 0.172172 0. 0. 4.17288e-11 0. 0. 4.17288e-11 0. 0. 8.34577e-11 >>> 0. 0. 4.17288e-11 0. 0. 2.08644e-11 0. 0. 4.17288e-11 0. 0. -1.04322e-11 0. >>> 0. -1.56483e-11 0. 0. -1.04322e-11 0. 0. -1.56483e-11 >>> [0] -0.588378 0.32647 0.0275225 -0.637271 0.141058 -0.137613 -2.37741 >>> -0.0867478 -0.275225 3.68138 0.0265907 3.13395e-14 1.1468 -0.107528 0.11009 >>> 1.18171 0.00886356 -3.13222e-14 -1.06248 -0.175069 0.158254 0.00657075 >>> -0.03 0. 0.152747 -0.00526446 0.0344031 -1.50368 -0.0983732 0.0825675 >>> 4.17288e-11 0. 0. 2.08644e-11 0. 0. 4.17288e-11 0. 0. 8.34577e-11 0. 0. >>> 4.17288e-11 0. 0. 4.17288e-11 0. 0. -1.04322e-11 0. 0. -1.56483e-11 0. 0. >>> -1.56483e-11 0. 0. -1.04322e-11 0. 0. >>> [0] 0.264666 -0.171351 -0.0207062 0.141058 -0.254263 0.0452109 0.0332522 >>> -0.592598 -0.0284819 0.0265907 1.20415 -0.0932626 -0.165724 0.149643 >>> 0.0524184 0.00886356 0.360043 0.0419805 -0.131422 -0.326529 0.0132913 -0.02 >>> 0.0229976 -0.00641026 -0.0152645 0.0405681 -0.00489246 -0.14202 -0.432665 >>> 0.000852265 0. 4.17288e-11 0. 0. 2.08644e-11 0. 0. 4.17288e-11 0. 0. >>> 8.34577e-11 0. 0. 4.17288e-11 0. 0. 4.17288e-11 0. 0. -1.04322e-11 0. 0. >>> -1.56483e-11 0. 0. -1.56483e-11 0. 0. -1.04322e-11 0. >>> [0] -0.0275225 -0.00845384 -0.114921 -0.137613 0.0452109 -0.252027 >>> -0.275225 -0.0413024 -0.660001 3.13785e-14 -0.0932626 1.19349 0.165135 >>> 0.0786276 0.288099 -3.12866e-14 0.0163395 0.234796 0.116971 0.0128652 >>> -0.322147 0. -0.00961538 0.00657075 0.0344031 -0.00168733 0.0564359 >>> 0.123851 0.0012784 -0.430298 0. 0. 4.17288e-11 0. 0. 2.08644e-11 0. 0. >>> 4.17288e-11 0. 0. 8.34577e-11 0. 0. 4.17288e-11 0. 0. 4.17288e-11 0. 0. >>> -1.04322e-11 0. 0. -1.56483e-11 0. 0. -1.56483e-11 0. 0. -1.04322e-11 >>> [0] -2.39586 -0.206902 0.33027 -2.37741 0.011448 -0.33027 -2.44501 >>> -0.417727 6.38053e-17 1.1468 -0.165724 0.165135 4.88671 0.435454 0. 1.18146 >>> -0.0565489 -0.165135 0.307839 0.0658628 -0.0412838 -0.00807774 0.18 0. >>> 0.303413 0.038569 0.0412838 -0.599871 0.115568 0. 4.17288e-11 0. 0. >>> 4.17288e-11 0. 0. 2.08644e-11 0. 0. 4.17288e-11 0. 0. 8.34577e-11 0. 0. >>> 4.17288e-11 0. 0. -1.56483e-11 0. 0. -1.04322e-11 0. 0. -1.56483e-11 0. 0. >>> -1.04322e-11 0. 0. >>> [0] -0.210511 -0.657189 0.0418706 -0.0649437 -0.592598 -0.0418706 -0.417727 >>> -0.829208 6.30468e-18 -0.107528 0.149643 0.0786276 0.435454 1.64686 0. >>> -0.0347447 0.270936 -0.0786276 0.0613138 0.111396 -0.0100415 0.12 >>> -0.0282721 0. 0.043118 0.0959058 0.0100415 0.175568 -0.167469 0. 0. >>> 4.17288e-11 0. 0. 4.17288e-11 0. 0. 2.08644e-11 0. 0. 4.17288e-11 0. 0. >>> 8.34577e-11 0. 0. 4.17288e-11 0. 0. -1.56483e-11 0. 0. -1.04322e-11 0. 0. >>> -1.56483e-11 0. 0. -1.04322e-11 0. >>> [0] 0.22018 0.0279137 -0.678455 -0.22018 -0.0279137 -0.660001 4.70408e-17 >>> 7.53383e-18 -0.727604 0.11009 0.0524184 0.288099 0. 0. 1.4519 -0.11009 >>> -0.0524184 0.322754 -0.0275225 -0.00669434 0.0931634 0. 0. -0.00807774 >>> 0.0275225 0.00669434 0.0887375 0. 0. -0.17052 0. 0. 4.17288e-11 0. 0. >>> 4.17288e-11 0. 0. 2.08644e-11 0. 0. 4.17288e-11 0. 0. 8.34577e-11 0. 0. >>> 4.17288e-11 0. 0. -1.56483e-11 0. 0. -1.04322e-11 0. 0. -1.56483e-11 0. 0. >>> -1.04322e-11 >>> [0] -0.621071 0.0500786 0.137613 -0.588378 0.344666 -0.0275225 -2.39586 >>> -0.268706 0.275225 1.18171 0.00886356 -3.12954e-14 1.18146 -0.0347447 >>> -0.11009 3.64748 0.0265907 3.12693e-14 0.152935 0.0174804 -0.0344031 >>> 0.00233276 -0.03 0. -1.0575 -0.0704425 -0.158254 -1.50311 -0.0437857 >>> -0.0825675 2.08644e-11 0. 0. 4.17288e-11 0. 0. 4.17288e-11 0. 0. >>> 4.17288e-11 0. 0. 4.17288e-11 0. 0. 8.34577e-11 0. 0. -1.56483e-11 0. 0. >>> -1.56483e-11 0. 0. -1.04322e-11 0. 0. -1.04322e-11 0. 0. >>> [0] 0.0500786 -0.197561 -0.0160508 0.24647 -0.171351 -0.00845384 -0.148706 >>> -0.657189 0.0284819 0.00886356 0.360043 0.0163395 -0.0565489 0.270936 >>> -0.0524184 0.0265907 1.08549 0.0349425 0.00748035 0.0412255 -0.00239755 >>> -0.02 0.00816465 0.00641026 -0.0540894 -0.309066 -0.00600133 -0.0601388 >>> -0.430693 -0.000852265 0. 2.08644e-11 0. 0. 4.17288e-11 0. 0. 4.17288e-11 >>> 0. 0. 4.17288e-11 0. 0. 4.17288e-11 0. 0. 8.34577e-11 0. 0. -1.56483e-11 0. >>> 0. -1.56483e-11 0. 0. -1.04322e-11 0. 0. -1.04322e-11 0. >>> [0] 0.137613 -0.0160508 -0.235826 0.0275225 -0.0207062 -0.114921 0.275225 >>> 0.0413024 -0.678455 -3.13299e-14 0.0419805 0.234796 -0.165135 -0.0786276 >>> 0.322754 3.12753e-14 0.0349425 1.15959 -0.0344031 -0.00560268 0.0566238 0. >>> 0.00961538 0.00233276 -0.116971 -0.00557519 -0.317157 -0.123851 -0.0012784 >>> -0.429734 0. 0. 2.08644e-11 0. 0. 4.17288e-11 0. 0. 4.17288e-11 0. 0. >>> 4.17288e-11 0. 0. 4.17288e-11 0. 0. 8.34577e-11 0. 0. -1.56483e-11 0. 0. >>> -1.56483e-11 0. 0. -1.04322e-11 0. 0. -1.04322e-11 >>> [0] -0.180869 -0.12748 0.0344031 -0.140937 0.00616654 -0.00688063 0.283843 >>> 0.03402 0.055045 -1.06248 -0.131422 0.116971 0.307839 0.0613138 -0.0275225 >>> 0.152935 0.00748035 -0.0344031 0.479756 0.112441 -0.103209 0.00698363 0.03 >>> 0. -0.14792 -0.0238335 -0.00688063 0.300855 0.0313138 -0.0275225 >>> -1.04322e-11 0. 0. -1.56483e-11 0. 0. -1.04322e-11 0. 0. -1.04322e-11 0. 0. >>> -1.56483e-11 0. 0. -1.56483e-11 0. 0. 1.56483e-11 0. 0. 2.60805e-12 0. 0. >>> 2.60805e-12 0. 0. 2.60805e-12 0. 0. >>> [0] -0.0974804 -0.138996 0.0312437 -0.00838243 -0.0212853 -0.0117288 >>> 0.0476669 0.0715157 0.0279687 -0.175069 -0.326529 0.0128652 0.0658628 >>> 0.111396 -0.00669434 0.0174804 0.0412255 -0.00560268 0.112441 0.197005 >>> -0.0360388 0.02 0.0244427 -0.00641026 -0.0283824 -0.045728 -0.00531859 >>> 0.0458628 0.0869535 -0.000284088 0. -1.04322e-11 0. 0. -1.56483e-11 0. 0. >>> -1.04322e-11 0. 0. -1.04322e-11 0. 0. -1.56483e-11 0. 0. -1.56483e-11 0. 0. >>> 1.56483e-11 0. 0. 2.60805e-12 0. 0. 2.60805e-12 0. 0. 2.60805e-12 0. >>> [0] 0.0344031 0.0408591 -0.0845583 0.00688063 -0.0115868 -0.0225723 >>> 0.0137613 0.0179272 0.0250605 0.158254 0.0132913 -0.322147 -0.0412838 >>> -0.0100415 0.0931634 -0.0344031 -0.00239755 0.0566238 -0.103209 -0.0360388 >>> 0.190822 0. -0.00961538 0.00698363 0.00688063 -0.00197142 -0.029556 >>> -0.0412838 -0.000426133 0.0861797 0. 0. -1.04322e-11 0. 0. -1.56483e-11 0. >>> 0. -1.04322e-11 0. 0. -1.04322e-11 0. 0. -1.56483e-11 0. 0. -1.56483e-11 0. >>> 0. 1.56483e-11 0. 0. 2.60805e-12 0. 0. 2.60805e-12 0. 0. 2.60805e-12 >>> [0] -0.0302673 -0.06 0. -0.0175533 -0.06 0. 0.00972927 0.04 0. 0.00657075 >>> -0.02 0. -0.00807774 0.12 0. 0.00233276 -0.02 0. 0.00698363 0.02 0. >>> 0.0279492 0. 0. 0.00274564 0.02 0. -0.000412882 -0.04 0. -1.04322e-11 0. 0. >>> -1.04322e-11 0. 0. -1.56483e-11 0. 0. -1.56483e-11 0. 0. -1.04322e-11 0. 0. >>> -1.56483e-11 0. 0. 2.60805e-12 0. 0. 1.56483e-11 0. 0. 2.60805e-12 0. 0. >>> 2.60805e-12 0. 0. >>> [0] -0.09 -0.105935 0.0288462 -0.09 -0.0614365 -0.0288462 0.06 0.0340524 >>> 3.0201e-18 -0.03 0.0229976 -0.00961538 0.18 -0.0282721 0. -0.03 0.00816465 >>> 0.00961538 0.03 0.0244427 -0.00961538 0. 0.097822 0. 0.03 0.00960973 >>> 0.00961538 -0.06 -0.00144509 0. 0. -1.04322e-11 0. 0. -1.04322e-11 0. 0. >>> -1.56483e-11 0. 0. -1.56483e-11 0. 0. -1.04322e-11 0. 0. -1.56483e-11 0. 0. >>> 2.60805e-12 0. 0. 1.56483e-11 0. 0. 2.60805e-12 0. 0. 2.60805e-12 0. >>> [0] 0. 0.0192308 -0.0302673 0. -0.0192308 -0.0175533 0. 1.8315e-18 >>> 0.00972927 0. -0.00641026 0.00657075 0. 0. -0.00807774 0. 0.00641026 >>> 0.00233276 0. -0.00641026 0.00698363 0. 0. 0.0279492 0. 0.00641026 >>> 0.00274564 0. 0. -0.000412882 0. 0. -1.04322e-11 0. 0. -1.04322e-11 0. 0. >>> -1.56483e-11 0. 0. -1.56483e-11 0. 0. -1.04322e-11 0. 0. -1.56483e-11 0. 0. >>> 2.60805e-12 0. 0. 1.56483e-11 0. 0. 2.60805e-12 0. 0. 2.60805e-12 >>> [0] -0.145175 0.00161757 0.00688063 -0.16373 -0.104736 -0.0344031 0.288268 >>> 0.0704117 -0.055045 0.152747 -0.0152645 0.0344031 0.303413 0.043118 >>> 0.0275225 -1.0575 -0.0540894 -0.116971 -0.14792 -0.0283824 0.00688063 >>> 0.00274564 0.03 0. 0.466478 0.0442066 0.103209 0.300667 0.013118 0.0275225 >>> -1.56483e-11 0. 0. -1.04322e-11 0. 0. -1.04322e-11 0. 0. -1.56483e-11 0. 0. >>> -1.56483e-11 0. 0. -1.04322e-11 0. 0. 2.60805e-12 0. 0. 2.60805e-12 0. 0. >>> 1.56483e-11 0. 0. 2.60805e-12 0. 0. >>> [0] -0.00383346 -0.0361182 0.00443884 -0.0747355 -0.0790071 -0.0239537 >>> 0.0567649 0.0870061 0.00119132 -0.00526446 0.0405681 -0.00168733 0.038569 >>> 0.0959058 0.00669434 -0.0704425 -0.309066 -0.00557519 -0.0238335 -0.045728 >>> -0.00197142 0.02 0.00960973 0.00641026 0.0442066 0.150534 0.0141688 >>> 0.018569 0.0862961 0.000284088 0. -1.56483e-11 0. 0. -1.04322e-11 0. 0. >>> -1.04322e-11 0. 0. -1.56483e-11 0. 0. -1.56483e-11 0. 0. -1.04322e-11 0. 0. >>> 2.60805e-12 0. 0. 2.60805e-12 0. 0. 1.56483e-11 0. 0. 2.60805e-12 0. >>> [0] -0.00688063 0.0042968 -0.0268103 -0.0344031 -0.0335691 -0.0674185 >>> -0.0137613 0.0112328 0.0294863 0.0344031 -0.00489246 0.0564359 0.0412838 >>> 0.0100415 0.0887375 -0.158254 -0.00600133 -0.317157 -0.00688063 -0.00531859 >>> -0.029556 0. 0.00961538 0.00274564 0.103209 0.0141688 0.177545 0.0412838 >>> 0.000426133 0.0859919 0. 0. -1.56483e-11 0. 0. -1.04322e-11 0. 0. >>> -1.04322e-11 0. 0. -1.56483e-11 0. 0. -1.56483e-11 0. 0. -1.04322e-11 0. 0. >>> 2.60805e-12 0. 0. 2.60805e-12 0. 0. 1.56483e-11 0. 0. 2.60805e-12 >>> [0] 0.300442 -0.0141372 -0.0412838 0.300255 -0.041431 0.0412838 0.601523 >>> 0.0644318 -1.72388e-17 -1.50368 -0.14202 0.123851 -0.599871 0.175568 0. >>> -1.50311 -0.0601388 -0.123851 0.300855 0.0458628 -0.0412838 -0.000412882 >>> -0.06 0. 0.300667 0.018569 0.0412838 1.80333 0.0132953 0. -1.56483e-11 0. >>> 0. -1.56483e-11 0. 0. -1.56483e-11 0. 0. -1.04322e-11 0. 0. -1.04322e-11 0. >>> 0. -1.04322e-11 0. 0. 2.60805e-12 0. 0. 2.60805e-12 0. 0. 2.60805e-12 0. 0. >>> 1.56483e-11 0. 0. >>> [0] -0.00868618 0.0855084 -0.000426133 -0.026882 0.084851 0.000426133 >>> 0.0444318 0.17325 -1.17738e-19 -0.0983732 -0.432665 0.0012784 0.115568 >>> -0.167469 0. -0.0437857 -0.430693 -0.0012784 0.0313138 0.0869535 >>> -0.000426133 -0.04 -0.00144509 0. 0.013118 0.0862961 0.000426133 0.0132953 >>> 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1.99342e-06 0. 0. >>> 1.32894e-06 0. 0. 1.99342e-06 0. 0. 1.32894e-06 0. 0. 2.65789e-09 0. 0. >>> 2.65789e-09 0. 0. 1.32894e-09 0. 0. 2.65789e-09 0. 0. 5.31578e-09 0. 0. >>> 2.65789e-09 0. 0. -9.96708e-10 0. 0. -6.64472e-10 0. 0. -9.96708e-10 0. 0. >>> -6.64472e-10 0. >>> [0] 0. 0. -5.31578e-06 0. 0. -5.31578e-06 0. 0. -2.65789e-06 0. 0. >>> -5.31578e-06 0. 0. -1.06316e-05 0. 0. -5.31578e-06 0. 0. 1.99342e-06 0. 0. >>> 1.32894e-06 0. 0. 1.99342e-06 0. 0. 1.32894e-06 0. 0. 2.65789e-09 0. 0. >>> 2.65789e-09 0. 0. 1.32894e-09 0. 0. 2.65789e-09 0. 0. 5.31578e-09 0. 0. >>> 2.65789e-09 0. 0. -9.96708e-10 0. 0. -6.64472e-10 0. 0. -9.96708e-10 0. 0. >>> -6.64472e-10 >>> [0] -2.65789e-06 0. 0. -5.31578e-06 0. 0. -5.31578e-06 0. 0. -5.31578e-06 >>> 0. 0. -5.31578e-06 0. 0. -1.06316e-05 0. 0. 1.99342e-06 0. 0. 1.99342e-06 >>> 0. 0. 1.32894e-06 0. 0. 1.32894e-06 0. 0. 1.32894e-09 0. 0. 2.65789e-09 0. >>> 0. 2.65789e-09 0. 0. 2.65789e-09 0. 0. 2.65789e-09 0. 0. 5.31578e-09 0. 0. >>> -9.96708e-10 0. 0. -9.96708e-10 0. 0. -6.64472e-10 0. 0. -6.64472e-10 0. 0. >>> [0] 0. -2.65789e-06 0. 0. -5.31578e-06 0. 0. -5.31578e-06 0. 0. >>> -5.31578e-06 0. 0. -5.31578e-06 0. 0. -1.06316e-05 0. 0. 1.99342e-06 0. 0. >>> 1.99342e-06 0. 0. 1.32894e-06 0. 0. 1.32894e-06 0. 0. 1.32894e-09 0. 0. >>> 2.65789e-09 0. 0. 2.65789e-09 0. 0. 2.65789e-09 0. 0. 2.65789e-09 0. 0. >>> 5.31578e-09 0. 0. -9.96708e-10 0. 0. -9.96708e-10 0. 0. -6.64472e-10 0. 0. >>> -6.64472e-10 0. >>> [0] 0. 0. -2.65789e-06 0. 0. -5.31578e-06 0. 0. -5.31578e-06 0. 0. >>> -5.31578e-06 0. 0. -5.31578e-06 0. 0. -1.06316e-05 0. 0. 1.99342e-06 0. 0. >>> 1.99342e-06 0. 0. 1.32894e-06 0. 0. 1.32894e-06 0. 0. 1.32894e-09 0. 0. >>> 2.65789e-09 0. 0. 2.65789e-09 0. 0. 2.65789e-09 0. 0. 2.65789e-09 0. 0. >>> 5.31578e-09 0. 0. -9.96708e-10 0. 0. -9.96708e-10 0. 0. -6.64472e-10 0. 0. >>> -6.64472e-10 >>> [0] 1.32894e-06 0. 0. 1.99342e-06 0. 0. 1.32894e-06 0. 0. 1.32894e-06 0. 0. >>> 1.99342e-06 0. 0. 1.99342e-06 0. 0. -1.99342e-06 0. 0. -3.32236e-07 0. 0. >>> -3.32236e-07 0. 0. -3.32236e-07 0. 0. -6.64472e-10 0. 0. -9.96708e-10 0. 0. >>> -6.64472e-10 0. 0. -6.64472e-10 0. 0. -9.96708e-10 0. 0. -9.96708e-10 0. 0. >>> 9.96708e-10 0. 0. 1.66118e-10 0. 0. 1.66118e-10 0. 0. 1.66118e-10 0. 0. >>> [0] 0. 1.32894e-06 0. 0. 1.99342e-06 0. 0. 1.32894e-06 0. 0. 1.32894e-06 0. >>> 0. 1.99342e-06 0. 0. 1.99342e-06 0. 0. -1.99342e-06 0. 0. -3.32236e-07 0. >>> 0. -3.32236e-07 0. 0. -3.32236e-07 0. 0. -6.64472e-10 0. 0. -9.96708e-10 0. >>> 0. -6.64472e-10 0. 0. -6.64472e-10 0. 0. -9.96708e-10 0. 0. -9.96708e-10 0. >>> 0. 9.96708e-10 0. 0. 1.66118e-10 0. 0. 1.66118e-10 0. 0. 1.66118e-10 0. >>> [0] 0. 0. 1.32894e-06 0. 0. 1.99342e-06 0. 0. 1.32894e-06 0. 0. 1.32894e-06 >>> 0. 0. 1.99342e-06 0. 0. 1.99342e-06 0. 0. -1.99342e-06 0. 0. -3.32236e-07 >>> 0. 0. -3.32236e-07 0. 0. -3.32236e-07 0. 0. -6.64472e-10 0. 0. -9.96708e-10 >>> 0. 0. -6.64472e-10 0. 0. -6.64472e-10 0. 0. -9.96708e-10 0. 0. -9.96708e-10 >>> 0. 0. 9.96708e-10 0. 0. 1.66118e-10 0. 0. 1.66118e-10 0. 0. 1.66118e-10 >>> [0] 1.32894e-06 0. 0. 1.32894e-06 0. 0. 1.99342e-06 0. 0. 1.99342e-06 0. 0. >>> 1.32894e-06 0. 0. 1.99342e-06 0. 0. -3.32236e-07 0. 0. -1.99342e-06 0. 0. >>> -3.32236e-07 0. 0. -3.32236e-07 0. 0. -6.64472e-10 0. 0. -6.64472e-10 0. 0. >>> -9.96708e-10 0. 0. -9.96708e-10 0. 0. -6.64472e-10 0. 0. -9.96708e-10 0. 0. >>> 1.66118e-10 0. 0. 9.96708e-10 0. 0. 1.66118e-10 0. 0. 1.66118e-10 0. 0. >>> [0] 0. 1.32894e-06 0. 0. 1.32894e-06 0. 0. 1.99342e-06 0. 0. 1.99342e-06 0. >>> 0. 1.32894e-06 0. 0. 1.99342e-06 0. 0. -3.32236e-07 0. 0. -1.99342e-06 0. >>> 0. -3.32236e-07 0. 0. -3.32236e-07 0. 0. -6.64472e-10 0. 0. -6.64472e-10 0. >>> 0. -9.96708e-10 0. 0. -9.96708e-10 0. 0. -6.64472e-10 0. 0. -9.96708e-10 0. >>> 0. 1.66118e-10 0. 0. 9.96708e-10 0. 0. 1.66118e-10 0. 0. 1.66118e-10 0. >>> [0] 0. 0. 1.32894e-06 0. 0. 1.32894e-06 0. 0. 1.99342e-06 0. 0. 1.99342e-06 >>> 0. 0. 1.32894e-06 0. 0. 1.99342e-06 0. 0. -3.32236e-07 0. 0. -1.99342e-06 >>> 0. 0. -3.32236e-07 0. 0. -3.32236e-07 0. 0. -6.64472e-10 0. 0. -6.64472e-10 >>> 0. 0. -9.96708e-10 0. 0. -9.96708e-10 0. 0. -6.64472e-10 0. 0. -9.96708e-10 >>> 0. 0. 1.66118e-10 0. 0. 9.96708e-10 0. 0. 1.66118e-10 0. 0. 1.66118e-10 >>> [0] 1.99342e-06 0. 0. 1.32894e-06 0. 0. 1.32894e-06 0. 0. 1.99342e-06 0. 0. >>> 1.99342e-06 0. 0. 1.32894e-06 0. 0. -3.32236e-07 0. 0. -3.32236e-07 0. 0. >>> -1.99342e-06 0. 0. -3.32236e-07 0. 0. -9.96708e-10 0. 0. -6.64472e-10 0. 0. >>> -6.64472e-10 0. 0. -9.96708e-10 0. 0. -9.96708e-10 0. 0. -6.64472e-10 0. 0. >>> 1.66118e-10 0. 0. 1.66118e-10 0. 0. 9.96708e-10 0. 0. 1.66118e-10 0. 0. >>> [0] 0. 1.99342e-06 0. 0. 1.32894e-06 0. 0. 1.32894e-06 0. 0. 1.99342e-06 0. >>> 0. 1.99342e-06 0. 0. 1.32894e-06 0. 0. -3.32236e-07 0. 0. -3.32236e-07 0. >>> 0. -1.99342e-06 0. 0. -3.32236e-07 0. 0. -9.96708e-10 0. 0. -6.64472e-10 0. >>> 0. -6.64472e-10 0. 0. -9.96708e-10 0. 0. -9.96708e-10 0. 0. -6.64472e-10 0. >>> 0. 1.66118e-10 0. 0. 1.66118e-10 0. 0. 9.96708e-10 0. 0. 1.66118e-10 0. >>> [0] 0. 0. 1.99342e-06 0. 0. 1.32894e-06 0. 0. 1.32894e-06 0. 0. 1.99342e-06 >>> 0. 0. 1.99342e-06 0. 0. 1.32894e-06 0. 0. -3.32236e-07 0. 0. -3.32236e-07 >>> 0. 0. -1.99342e-06 0. 0. -3.32236e-07 0. 0. -9.96708e-10 0. 0. -6.64472e-10 >>> 0. 0. -6.64472e-10 0. 0. -9.96708e-10 0. 0. -9.96708e-10 0. 0. -6.64472e-10 >>> 0. 0. 1.66118e-10 0. 0. 1.66118e-10 0. 0. 9.96708e-10 0. 0. 1.66118e-10 >>> [0] 1.99342e-06 0. 0. 1.99342e-06 0. 0. 1.99342e-06 0. 0. 1.32894e-06 0. 0. >>> 1.32894e-06 0. 0. 1.32894e-06 0. 0. -3.32236e-07 0. 0. -3.32236e-07 0. 0. >>> -3.32236e-07 0. 0. -1.99342e-06 0. 0. -9.96708e-10 0. 0. -9.96708e-10 0. 0. >>> -9.96708e-10 0. 0. -6.64472e-10 0. 0. -6.64472e-10 0. 0. -6.64472e-10 0. 0. >>> 1.66118e-10 0. 0. 1.66118e-10 0. 0. 1.66118e-10 0. 0. 9.96708e-10 0. 0. >>> [0] 0. 1.99342e-06 0. 0. 1.99342e-06 0. 0. 1.99342e-06 0. 0. 1.32894e-06 0. >>> 0. 1.32894e-06 0. 0. 1.32894e-06 0. 0. -3.32236e-07 0. 0. -3.32236e-07 0. >>> 0. -3.32236e-07 0. 0. -1.99342e-06 0. 0. -9.96708e-10 0. 0. -9.96708e-10 0. >>> 0. -9.96708e-10 0. 0. -6.64472e-10 0. 0. -6.64472e-10 0. 0. -6.64472e-10 0. >>> 0. 1.66118e-10 0. 0. 1.66118e-10 0. 0. 1.66118e-10 0. 0. 9.96708e-10 0. >>> [0] 0. 0. 1.99342e-06 0. 0. 1.99342e-06 0. 0. 1.99342e-06 0. 0. 1.32894e-06 >>> 0. 0. 1.32894e-06 0. 0. 1.32894e-06 0. 0. -3.32236e-07 0. 0. -3.32236e-07 >>> 0. 0. -3.32236e-07 0. 0. -1.99342e-06 0. 0. -9.96708e-10 0. 0. -9.96708e-10 >>> 0. 0. -9.96708e-10 0. 0. -6.64472e-10 0. 0. -6.64472e-10 0. 0. -6.64472e-10 >>> 0. 0. 1.66118e-10 0. 0. 1.66118e-10 0. 0. 1.66118e-10 0. 0. 9.96708e-10 >>> [0]PETSC ERROR: #3 DMPlexMatSetClosure() line 5480 in >>> /home/hartig/petsc/src/dm/impls/plex/plex.c >>> [0]PETSC ERROR: #4 DMPlexComputeJacobian_Internal() line 2301 in >>> /home/hartig/petsc/src/snes/utils/dmplexsnes.c >>> [0]PETSC ERROR: #5 DMPlexTSComputeIJacobianFEM() line 233 in >>> /home/hartig/petsc/src/ts/utils/dmplexts.c >>> [0]PETSC ERROR: #6 TSComputeIJacobian_DMLocal() line 131 in >>> /home/hartig/petsc/src/ts/utils/dmlocalts.c >>> [0]PETSC ERROR: #7 TSComputeIJacobian() line 882 in >>> /home/hartig/petsc/src/ts/interface/ts.c >>> [0]PETSC ERROR: #8 SNESTSFormJacobian_Theta() line 515 in >>> /home/hartig/petsc/src/ts/impls/implicit/theta/theta.c >>> [0]PETSC ERROR: #9 SNESTSFormJacobian() line 5044 in >>> /home/hartig/petsc/src/ts/interface/ts.c >>> [0]PETSC ERROR: #10 SNESComputeJacobian() line 2276 in >>> /home/hartig/petsc/src/snes/interface/snes.c >>> [0]PETSC ERROR: #11 SNESSolve_NEWTONLS() line 222 in >>> /home/hartig/petsc/src/snes/impls/ls/ls.c >>> [0]PETSC ERROR: #12 SNESSolve() line 3967 in >>> /home/hartig/petsc/src/snes/interface/snes.c >>> [0]PETSC ERROR: #13 TS_SNESSolve() line 171 in >>> /home/hartig/petsc/src/ts/impls/implicit/theta/theta.c >>> [0]PETSC ERROR: #14 TSStep_Theta() line 211 in >>> /home/hartig/petsc/src/ts/impls/implicit/theta/theta.c >>> [0]PETSC ERROR: #15 TSStep() line 3809 in >>> /home/hartig/petsc/src/ts/interface/ts.c >>> >>> >>> >>> >>> >>> >>> -- >>> What most experimenters take for granted before they begin their >>> experiments is infinitely more interesting than any results to which their >>> experiments lead. >>> -- Norbert Wiener >> >> > > > > > > -- > What most experimenters take for granted before they begin their experiments > is infinitely more interesting than any results to which their experiments > lead. > -- Norbert Wiener
