Default is to use a total of 4 processors: 4 via shared-memory 1 via Linda Entering Link 1 = C:\G09W\l1.exe PID= 4856. Copyright (c) 1988,1990,1992,1993,1995,1998,2003,2009,2013, Gaussian, Inc. All Rights Reserved. This is part of the Gaussian(R) 09 program. It is based on the Gaussian(R) 03 system (copyright 2003, Gaussian, Inc.), the Gaussian(R) 98 system (copyright 1998, Gaussian, Inc.), the Gaussian(R) 94 system (copyright 1995, Gaussian, Inc.), the Gaussian 92(TM) system (copyright 1992, Gaussian, Inc.), the Gaussian 90(TM) system (copyright 1990, Gaussian, Inc.), the Gaussian 88(TM) system (copyright 1988, Gaussian, Inc.), the Gaussian 86(TM) system (copyright 1986, Carnegie Mellon University), and the Gaussian 82(TM) system (copyright 1983, Carnegie Mellon University). Gaussian is a federally registered trademark of Gaussian, Inc. This software contains proprietary and confidential information, including trade secrets, belonging to Gaussian, Inc. This software is provided under written license and may be used, copied, transmitted, or stored only in accord with that written license. The following legend is applicable only to US Government contracts under FAR: RESTRICTED RIGHTS LEGEND Use, reproduction and disclosure by the US Government is subject to restrictions as set forth in subparagraphs (a) and (c) of the Commercial Computer Software - Restricted Rights clause in FAR 52.227-19. Gaussian, Inc. 340 Quinnipiac St., Bldg. 40, Wallingford CT 06492 --------------------------------------------------------------- Warning -- This program may not be used in any manner that competes with the business of Gaussian, Inc. or will provide assistance to any competitor of Gaussian, Inc. The licensee of this program is prohibited from giving any competitor of Gaussian, Inc. access to this program. By using this program, the user acknowledges that Gaussian, Inc. is engaged in the business of creating and licensing software in the field of computational chemistry and represents and warrants to the licensee that it is not a competitor of Gaussian, Inc. and that it will not use this program in any manner prohibited above. --------------------------------------------------------------- Cite this work as: Gaussian 09, Revision D.01, M. J. Frisch, G. W. Trucks, H. B. Schlegel, G. E. Scuseria, M. A. Robb, J. R. Cheeseman, G. Scalmani, V. Barone, B. Mennucci, G. A. Petersson, H. Nakatsuji, M. Caricato, X. Li, H. P. Hratchian, A. F. Izmaylov, J. Bloino, G. Zheng, J. L. Sonnenberg, M. Hada, M. Ehara, K. Toyota, R. Fukuda, J. Hasegawa, M. Ishida, T. Nakajima, Y. Honda, O. Kitao, H. Nakai, T. Vreven, J. A. Montgomery, Jr., J. E. Peralta, F. Ogliaro, M. Bearpark, J. J. Heyd, E. Brothers, K. N. Kudin, V. N. Staroverov, T. Keith, R. Kobayashi, J. Normand, K. Raghavachari, A. Rendell, J. C. Burant, S. S. Iyengar, J. Tomasi, M. Cossi, N. Rega, J. M. Millam, M. Klene, J. E. Knox, J. B. Cross, V. Bakken, C. Adamo, J. Jaramillo, R. Gomperts, R. E. Stratmann, O. Yazyev, A. J. Austin, R. Cammi, C. Pomelli, J. W. Ochterski, R. L. Martin, K. Morokuma, V. G. Zakrzewski, G. A. Voth, P. Salvador, J. J. Dannenberg, S. Dapprich, A. D. Daniels, O. Farkas, J. B. Foresman, J. V. Ortiz, J. Cioslowski, and D. J. Fox, Gaussian, Inc., Wallingford CT, 2013. ****************************************** Gaussian 09: EM64W-G09RevD.01 13-Apr-2013 15-Oct-2015 ****************************************** %chk=\\icnas3.cc.ic.ac.uk\xd1013\Desktop\exercise\transition state 2.chk Default route: MaxDisk=10GB ------------------------------------------------------------------ # opt=qst2 freq hf/3-21g geom=connectivity integral=grid=ultrafine ------------------------------------------------------------------ 1/5=1,18=20,27=202,38=1,57=2/1,3; 2/9=110,12=2,17=6,18=5,40=1/2; 3/5=5,11=9,16=1,25=1,30=1,71=1,75=-5/1,2,3; 4//1; 5/5=2,38=5/2; 6/7=2,8=2,9=2,10=2,28=1/1; 7//1,2,3,16; 1/5=1,18=20,27=202/3(2); 2/9=110/2; 99//99; 2/9=110/2; 3/5=5,11=9,16=1,25=1,30=1,71=1,75=-5/1,2,3; 4/5=5,16=3,69=1/1; 5/5=2,38=5/2; 7//1,2,3,16; 1/5=1,18=20,27=202/3(-5); 2/9=110/2; 6/7=2,8=2,9=2,10=2,19=2,28=1/1; 99/9=1/99; ------------------- Title Card Required ------------------- Symbolic Z-matrix: Charge = 0 Multiplicity = 1 C -2.14503 -1.97013 -0.20278 C -3.42246 -2.21312 -0.39944 C -4.5782 0.06163 -0.5481 C -3.9424 1.19607 -0.77391 C -2.52408 1.48762 -0.47504 C -1.64808 0.66393 0.06935 H -1.49501 -2.68989 0.25781 H -1.69301 -1.04074 -0.49373 H -4.07248 -1.49336 -0.86004 H -3.87447 -3.14251 -0.1085 H -1.89814 -0.33909 0.35776 H -0.63512 0.96821 0.24837 H -2.20316 2.47903 -0.73914 H -4.48478 2.01003 -1.21993 H -4.1004 -0.79178 -0.10631 H -5.61414 -0.05526 -0.80083 Add virtual bond connecting atoms H11 and H8 Dist= 2.12D+00. Add virtual bond connecting atoms H15 and H9 Dist= 1.95D+00. ------------------- Title Card Required ------------------- Symbolic Z-matrix: Charge = 0 Multiplicity = 1 C -1.30028 -1.41847 -1.30428 C -2.0809 -2.74555 -1.30428 C -1.6945 -3.58223 -0.06924 C -1.68668 -2.74092 1.19071 C -1.6945 -1.4231 1.19071 C -1.68668 -0.58179 -0.06924 H -0.23632 -1.63138 -1.27586 H -1.50278 -0.85783 -2.20996 H -1.87841 -3.30619 -2.20996 H -3.14486 -2.53264 -1.27586 H -0.99213 0.24386 0.05189 H -2.67242 -0.14669 -0.21686 H -1.70669 -0.88957 2.12403 H -1.67449 -3.27445 2.12403 H -2.38905 -4.40788 0.05189 H -0.70876 -4.01733 -0.21686 Iteration 1 RMS(Cart)= 0.07821960 RMS(Int)= 0.97975325 Iteration 2 RMS(Cart)= 0.06405652 RMS(Int)= 0.95521563 Iteration 3 RMS(Cart)= 0.05298628 RMS(Int)= 0.94031529 Iteration 4 RMS(Cart)= 0.04582409 RMS(Int)= 0.93253923 Iteration 5 RMS(Cart)= 0.03942608 RMS(Int)= 0.93002819 Iteration 6 RMS(Cart)= 0.03389417 RMS(Int)= 0.93142443 Iteration 7 RMS(Cart)= 0.02384979 RMS(Int)= 0.93509056 Iteration 8 RMS(Cart)= 0.01844670 RMS(Int)= 0.93963360 Iteration 9 RMS(Cart)= 0.01534797 RMS(Int)= 0.94404694 Iteration 10 RMS(Cart)= 0.01310430 RMS(Int)= 0.94795785 Iteration 11 RMS(Cart)= 0.01187886 RMS(Int)= 0.95149423 Iteration 12 RMS(Cart)= 0.01110879 RMS(Int)= 0.95479017 Iteration 13 RMS(Cart)= 0.01047352 RMS(Int)= 0.95790964 Iteration 14 RMS(Cart)= 0.00966715 RMS(Int)= 0.96077138 Iteration 15 RMS(Cart)= 0.00905641 RMS(Int)= 0.96340283 Iteration 16 RMS(Cart)= 0.00865469 RMS(Int)= 0.96587847 Iteration 17 RMS(Cart)= 0.00838111 RMS(Int)= 0.96825488 Iteration 18 RMS(Cart)= 0.00808778 RMS(Int)= 0.97049602 Iteration 19 RMS(Cart)= 0.00784376 RMS(Int)= 0.97238898 Iteration 20 RMS(Cart)= 0.00734489 RMS(Int)= 0.97404370 Iteration 21 RMS(Cart)= 0.00690523 RMS(Int)= 0.97549354 Iteration 22 RMS(Cart)= 0.00656613 RMS(Int)= 0.97679044 Iteration 23 RMS(Cart)= 0.00630649 RMS(Int)= 0.97797936 Iteration 24 RMS(Cart)= 0.00609938 RMS(Int)= 0.97909608 Iteration 25 RMS(Cart)= 0.00592538 RMS(Int)= 0.98016773 Iteration 26 RMS(Cart)= 0.00577202 RMS(Int)= 0.98121398 Iteration 27 RMS(Cart)= 0.00563206 RMS(Int)= 0.98224871 Iteration 28 RMS(Cart)= 0.00550059 RMS(Int)= 0.98328139 Iteration 29 RMS(Cart)= 0.00537449 RMS(Int)= 0.98431821 Iteration 30 RMS(Cart)= 0.00525175 RMS(Int)= 0.98536297 Iteration 31 RMS(Cart)= 0.00513114 RMS(Int)= 0.98641780 Iteration 32 RMS(Cart)= 0.00501189 RMS(Int)= 0.98748359 Iteration 33 RMS(Cart)= 0.00489344 RMS(Int)= 0.98856038 Iteration 34 RMS(Cart)= 0.00478918 RMS(Int)= 0.98964764 Iteration 35 RMS(Cart)= 0.00469447 RMS(Int)= 0.99074501 Iteration 36 RMS(Cart)= 0.00460318 RMS(Int)= 0.99185231 Iteration 37 RMS(Cart)= 0.00451754 RMS(Int)= 0.99296932 Iteration 38 RMS(Cart)= 0.00443827 RMS(Int)= 0.99409593 Iteration 39 RMS(Cart)= 0.00436603 RMS(Int)= 0.99523215 Iteration 40 RMS(Cart)= 0.00430147 RMS(Int)= 0.99637818 Iteration 41 RMS(Cart)= 0.00424522 RMS(Int)= 0.99753445 Iteration 42 RMS(Cart)= 0.00419779 RMS(Int)= 0.99870158 Iteration 43 RMS(Cart)= 0.00415958 RMS(Int)= 0.99988045 Iteration 44 RMS(Cart)= 0.00403778 RMS(Int)= 1.00105889 Iteration 45 RMS(Cart)= 0.00328571 RMS(Int)= 1.00208252 Iteration 46 RMS(Cart)= 0.00277037 RMS(Int)= 1.00294827 Iteration 47 RMS(Cart)= 0.00238911 RMS(Int)= 1.00329441 Iteration 48 RMS(Cart)= 0.01577166 RMS(Int)= 0.99756665 Iteration 49 RMS(Cart)= 0.01231315 RMS(Int)= 0.99397564 Iteration 50 RMS(Cart)= 0.00829244 RMS(Int)= 0.99128253 Iteration 51 RMS(Cart)= 0.00606189 RMS(Int)= 0.98916638 Iteration 52 RMS(Cart)= 0.00483674 RMS(Int)= 0.98743031 Iteration 53 RMS(Cart)= 0.00406553 RMS(Int)= 0.98598289 Iteration 54 RMS(Cart)= 0.00358095 RMS(Int)= 0.98476638 Iteration 55 RMS(Cart)= 0.00327877 RMS(Int)= 0.98373819 Iteration 56 RMS(Cart)= 0.00303108 RMS(Int)= 0.98285644 Iteration 57 RMS(Cart)= 0.00290600 RMS(Int)= 0.98209610 Iteration 58 RMS(Cart)= 0.00284224 RMS(Int)= 0.98143818 Iteration 59 RMS(Cart)= 0.00281024 RMS(Int)= 0.98086660 Iteration 60 RMS(Cart)= 0.00279929 RMS(Int)= 0.98036781 Iteration 61 RMS(Cart)= 0.00280362 RMS(Int)= 0.97993043 Iteration 62 RMS(Cart)= 0.00250544 RMS(Int)= 0.97956601 Iteration 63 RMS(Cart)= 0.00217680 RMS(Int)= 0.97926058 Iteration 64 RMS(Cart)= 0.00191614 RMS(Int)= 0.97899614 Iteration 65 RMS(Cart)= 0.00169978 RMS(Int)= 0.97876083 Iteration 66 RMS(Cart)= 0.00151610 RMS(Int)= 0.97854704 Iteration 67 RMS(Cart)= 0.00135798 RMS(Int)= 0.97834991 Iteration 68 RMS(Cart)= 0.00122050 RMS(Int)= 0.97816631 Iteration 69 RMS(Cart)= 0.00110006 RMS(Int)= 0.97799421 Iteration 70 RMS(Cart)= 0.00099389 RMS(Int)= 0.97783225 Iteration 71 RMS(Cart)= 0.00089981 RMS(Int)= 0.97767955 Iteration 72 RMS(Cart)= 0.00081609 RMS(Int)= 0.97753544 Iteration 73 RMS(Cart)= 0.00074130 RMS(Int)= 0.97739945 Iteration 74 RMS(Cart)= 0.00067429 RMS(Int)= 0.97727119 Iteration 75 RMS(Cart)= 0.00061408 RMS(Int)= 0.97715032 Iteration 76 RMS(Cart)= 0.00055986 RMS(Int)= 0.97703653 Iteration 77 RMS(Cart)= 0.00051092 RMS(Int)= 0.97692953 Iteration 78 RMS(Cart)= 0.00046669 RMS(Int)= 0.97682903 Iteration 79 RMS(Cart)= 0.00042663 RMS(Int)= 0.97673474 Iteration 80 RMS(Cart)= 0.00039033 RMS(Int)= 0.97664637 Iteration 81 RMS(Cart)= 0.00035737 RMS(Int)= 0.97656364 Iteration 82 RMS(Cart)= 0.00032743 RMS(Int)= 0.97648626 Iteration 83 RMS(Cart)= 0.00030021 RMS(Int)= 0.97641395 Iteration 84 RMS(Cart)= 0.00027544 RMS(Int)= 0.97634643 Iteration 85 RMS(Cart)= 0.00025288 RMS(Int)= 0.97628343 Iteration 86 RMS(Cart)= 0.00023233 RMS(Int)= 0.97622470 Iteration 87 RMS(Cart)= 0.00021361 RMS(Int)= 0.97616996 Iteration 88 RMS(Cart)= 0.00019654 RMS(Int)= 0.97611899 Iteration 89 RMS(Cart)= 0.00018097 RMS(Int)= 0.97607154 Iteration 90 RMS(Cart)= 0.00016677 RMS(Int)= 0.97602739 Iteration 91 RMS(Cart)= 0.00015382 RMS(Int)= 0.97598633 Iteration 92 RMS(Cart)= 0.00014200 RMS(Int)= 0.97594814 Iteration 93 RMS(Cart)= 0.00013123 RMS(Int)= 0.97591265 Iteration 94 RMS(Cart)= 0.00012139 RMS(Int)= 0.97587966 Iteration 95 RMS(Cart)= 0.00011242 RMS(Int)= 0.97584900 Iteration 96 RMS(Cart)= 0.00010424 RMS(Int)= 0.97582052 Iteration 97 RMS(Cart)= 0.00009678 RMS(Int)= 0.97579406 Iteration 98 RMS(Cart)= 0.00008997 RMS(Int)= 0.97576949 Iteration 99 RMS(Cart)= 0.00008377 RMS(Int)= 0.97574665 Iteration100 RMS(Cart)= 0.00007811 RMS(Int)= 0.97572545 New curvilinear step not converged. FormGI is forming the generalized inverse of G from B-inverse, IUseBI=4. RedQX1 iteration 1 Try 1 RMS(Cart)= 0.06964691 RMS(Int)= 0.97348262 XScale= 10.72959181 RedQX1 iteration 1 Try 2 RMS(Cart)= 0.07015271 RMS(Int)= 0.94020194 XScale= 5.45106601 RedQX1 iteration 1 Try 3 RMS(Cart)= 0.07255276 RMS(Int)= 0.91525161 XScale= 3.66794164 RedQX1 iteration 1 Try 4 RMS(Cart)= 0.08005133 RMS(Int)= 0.89829597 XScale= 2.74119108 RedQX1 iteration 1 Try 5 RMS(Cart)= 0.10880571 RMS(Int)= 0.88959396 XScale= 2.11171996 RedQX1 iteration 1 Try 6 RMS(Cart)= 0.06431951 RMS(Int)= 0.88795430 XScale= 1.97334066 RedQX1 iteration 2 Try 1 RMS(Cart)= 0.00585069 RMS(Int)= 0.88763938 XScale= 1.97317009 RedQX1 iteration 2 Try 2 RMS(Cart)= 0.00631688 RMS(Int)= 0.88735635 XScale= 1.97490961 RedQX1 iteration 2 Try 3 RMS(Cart)= 0.00718747 RMS(Int)= 0.88708890 XScale= 1.98012747 RedQX1 iteration 2 Try 4 RMS(Cart)= 0.00914460 RMS(Int)= 0.88681711 XScale= 1.99254598 RedQX1 iteration 2 Try 5 RMS(Cart)= 0.01566184 RMS(Int)= 0.88656237 XScale= 2.02531931 RedQX1 iteration 2 Try 6 RMS(Cart)= 0.01369974 RMS(Int)= 0.88653251 XScale= 2.05385276 RedQX1 iteration 3 Try 1 RMS(Cart)= 0.00179112 RMS(Int)= 0.88653066 XScale= 2.05452996 RedQX1 iteration 3 Try 2 RMS(Cart)= 0.00195091 RMS(Int)= 0.88652575 XScale= 2.05469098 RedQX1 iteration 3 Try 3 RMS(Cart)= 0.00221150 RMS(Int)= 0.88651907 XScale= 2.05405186 RedQX1 iteration 3 Try 4 RMS(Cart)= 0.00273761 RMS(Int)= 0.88651253 XScale= 2.05198653 RedQX1 iteration 3 Try 5 RMS(Cart)= 0.00437423 RMS(Int)= 0.88651382 XScale= 2.04636680 RedQX1 iteration 3 Try 6 RMS(Cart)= 0.00352212 RMS(Int)= 0.88651309 XScale= 2.04155051 RedQX1 iteration 4 Try 1 RMS(Cart)= 0.00047320 RMS(Int)= 0.88651040 XScale= 2.04155666 RedQX1 iteration 4 Try 2 RMS(Cart)= 0.00052023 RMS(Int)= 0.88650711 XScale= 2.04171130 RedQX1 iteration 4 Try 3 RMS(Cart)= 0.00059782 RMS(Int)= 0.88650302 XScale= 2.04210289 RedQX1 iteration 4 Try 4 RMS(Cart)= 0.00075331 RMS(Int)= 0.88649780 XScale= 2.04292535 RedQX1 iteration 4 Try 5 RMS(Cart)= 0.00122303 RMS(Int)= 0.88649114 XScale= 2.04480834 RedQX1 iteration 4 Try 6 RMS(Cart)= 0.00098504 RMS(Int)= 0.88649078 XScale= 2.04612261 RedQX1 iteration 5 Try 1 RMS(Cart)= 0.00013641 RMS(Int)= 0.88649133 XScale= 2.04607996 RedQX1 iteration 5 Try 2 RMS(Cart)= 0.00015055 RMS(Int)= 0.88649201 XScale= 2.04598745 RedQX1 iteration 5 Try 3 RMS(Cart)= 0.00017387 RMS(Int)= 0.88649286 XScale= 2.04581782 RedQX1 iteration 5 Try 4 RMS(Cart)= 0.00022025 RMS(Int)= 0.88649397 XScale= 2.04551196 RedQX1 iteration 5 Try 5 RMS(Cart)= 0.00035798 RMS(Int)= 0.88649556 XScale= 2.04487851 RedQX1 iteration 5 Try 6 RMS(Cart)= 0.00028309 RMS(Int)= 0.88649564 XScale= 2.04447888 RedQX1 iteration 6 Try 1 RMS(Cart)= 0.00003936 RMS(Int)= 0.88649544 XScale= 2.04449341 RedQX1 iteration 6 Try 2 RMS(Cart)= 0.00004363 RMS(Int)= 0.88649520 XScale= 2.04452296 RedQX1 iteration 6 Try 3 RMS(Cart)= 0.00005071 RMS(Int)= 0.88649491 XScale= 2.04457574 RedQX1 iteration 6 Try 4 RMS(Cart)= 0.00006474 RMS(Int)= 0.88649453 XScale= 2.04466945 RedQX1 iteration 6 Try 5 RMS(Cart)= 0.00010591 RMS(Int)= 0.88649402 XScale= 2.04486090 RedQX1 iteration 6 Try 6 RMS(Cart)= 0.00008318 RMS(Int)= 0.88649399 XScale= 2.04497801 RedQX1 iteration 7 Try 1 RMS(Cart)= 0.00001162 RMS(Int)= 0.88649404 XScale= 2.04497320 RedQX1 iteration 7 Try 2 RMS(Cart)= 0.00001292 RMS(Int)= 0.88649411 XScale= 2.04496398 RedQX1 iteration 7 Try 3 RMS(Cart)= 0.00001506 RMS(Int)= 0.88649419 XScale= 2.04494801 RedQX1 iteration 7 Try 4 RMS(Cart)= 0.00001926 RMS(Int)= 0.88649429 XScale= 2.04492027 RedQX1 iteration 7 Try 5 RMS(Cart)= 0.00003146 RMS(Int)= 0.88649443 XScale= 2.04486482 RedQX1 iteration 7 Try 6 RMS(Cart)= 0.00002440 RMS(Int)= 0.88649444 XScale= 2.04483269 RedQX1 iteration 8 Try 1 RMS(Cart)= 0.00000343 RMS(Int)= 0.88649442 XScale= 2.04483447 RedQX1 iteration 8 Try 2 RMS(Cart)= 0.00000382 RMS(Int)= 0.88649440 XScale= 2.04483755 RedQX1 iteration 8 Try 3 RMS(Cart)= 0.00000447 RMS(Int)= 0.88649438 XScale= 2.04484261 RedQX1 iteration 8 Try 4 RMS(Cart)= 0.00000572 RMS(Int)= 0.88649435 XScale= 2.04485108 RedQX1 iteration 8 Try 5 RMS(Cart)= 0.00000932 RMS(Int)= 0.88649431 XScale= 2.04486742 RedQX1 iteration 8 Try 6 RMS(Cart)= 0.00000713 RMS(Int)= 0.88649431 XScale= 2.04487615 RedQX1 iteration 9 Try 1 RMS(Cart)= 0.00000101 RMS(Int)= 0.88649432 XScale= 2.04487550 RedQX1 iteration 9 Try 2 RMS(Cart)= 0.00000113 RMS(Int)= 0.88649432 XScale= 2.04487446 RedQX1 iteration 9 Try 3 RMS(Cart)= 0.00000132 RMS(Int)= 0.88649433 XScale= 2.04487283 RedQX1 iteration 9 Try 4 RMS(Cart)= 0.00000170 RMS(Int)= 0.88649434 XScale= 2.04487021 RedQX1 iteration 9 Try 5 RMS(Cart)= 0.00000276 RMS(Int)= 0.88649435 XScale= 2.04486534 RedQX1 iteration 9 Try 6 RMS(Cart)= 0.00000208 RMS(Int)= 0.88649435 XScale= 2.04486296 RedQX1 iteration 10 Try 1 RMS(Cart)= 0.00000030 RMS(Int)= 0.88649434 XScale= 2.04486319 RedQX1 iteration 10 Try 2 RMS(Cart)= 0.00000033 RMS(Int)= 0.88649434 XScale= 2.04486354 RedQX1 iteration 10 Try 3 RMS(Cart)= 0.00000039 RMS(Int)= 0.88649434 XScale= 2.04486406 RedQX1 iteration 10 Try 4 RMS(Cart)= 0.00000050 RMS(Int)= 0.88649434 XScale= 2.04486486 RedQX1 iteration 10 Try 5 RMS(Cart)= 0.00000081 RMS(Int)= 0.88649434 XScale= 2.04486632 RedQX1 iteration 10 Try 6 RMS(Cart)= 0.00000061 RMS(Int)= 0.88649434 XScale= 2.04486696 RedQX1 iteration 11 Try 1 RMS(Cart)= 0.00000009 RMS(Int)= 0.88649434 XScale= 2.04486689 Iteration 1 RMS(Cart)= 0.13759857 RMS(Int)= 1.89733835 Iteration 2 RMS(Cart)= 0.13876821 RMS(Int)= 1.82623287 Iteration 3 RMS(Cart)= 0.14085716 RMS(Int)= 1.75123265 Iteration 4 RMS(Cart)= 0.13952945 RMS(Int)= 1.67793699 Iteration 5 RMS(Cart)= 0.13555633 RMS(Int)= 1.60760268 Iteration 6 RMS(Cart)= 0.13021800 RMS(Int)= 1.54063177 Iteration 7 RMS(Cart)= 0.12181754 RMS(Int)= 1.47814003 Iteration 8 RMS(Cart)= 0.11179963 RMS(Int)= 1.42038522 Iteration 9 RMS(Cart)= 0.09763301 RMS(Int)= 1.36829788 Iteration 10 RMS(Cart)= 0.06483869 RMS(Int)= 1.33314748 Iteration 11 RMS(Cart)= 0.02595785 RMS(Int)= 1.32009333 Iteration 12 RMS(Cart)= 0.01060942 RMS(Int)= 1.31500580 Iteration 13 RMS(Cart)= 0.00673079 RMS(Int)= 1.31180731 Iteration 14 RMS(Cart)= 0.00626821 RMS(Int)= 1.30882960 Iteration 15 RMS(Cart)= 0.00530345 RMS(Int)= 1.30631584 Iteration 16 RMS(Cart)= 0.00472123 RMS(Int)= 1.30408087 Iteration 17 RMS(Cart)= 0.00455590 RMS(Int)= 1.30192058 Iteration 18 RMS(Cart)= 0.00433426 RMS(Int)= 1.29986188 Iteration 19 RMS(Cart)= 0.00409149 RMS(Int)= 1.29791462 Iteration 20 RMS(Cart)= 0.00378437 RMS(Int)= 1.29611113 Iteration 21 RMS(Cart)= 0.00339401 RMS(Int)= 1.29449262 Iteration 22 RMS(Cart)= 0.00318364 RMS(Int)= 1.29297243 Iteration 23 RMS(Cart)= 0.00305668 RMS(Int)= 1.29151074 Iteration 24 RMS(Cart)= 0.00292480 RMS(Int)= 1.29011044 Iteration 25 RMS(Cart)= 0.00278225 RMS(Int)= 1.28877715 Iteration 26 RMS(Cart)= 0.00261324 RMS(Int)= 1.28752406 Iteration 27 RMS(Cart)= 0.00238246 RMS(Int)= 1.28638150 Iteration 28 RMS(Cart)= 0.00206112 RMS(Int)= 1.28539344 Iteration 29 RMS(Cart)= 0.00196490 RMS(Int)= 1.28445150 Iteration 30 RMS(Cart)= 0.00194705 RMS(Int)= 1.28351805 Iteration 31 RMS(Cart)= 0.00193018 RMS(Int)= 1.28259268 Iteration 32 RMS(Cart)= 0.00191430 RMS(Int)= 1.28167498 Iteration 33 RMS(Cart)= 0.00189930 RMS(Int)= 1.28076458 Iteration 34 RMS(Cart)= 0.00188516 RMS(Int)= 1.27986113 Iteration 35 RMS(Cart)= 0.00187180 RMS(Int)= 1.27896430 Iteration 36 RMS(Cart)= 0.00185925 RMS(Int)= 1.27807375 Iteration 37 RMS(Cart)= 0.00184735 RMS(Int)= 1.27718922 Iteration 38 RMS(Cart)= 0.00183617 RMS(Int)= 1.27631039 Iteration 39 RMS(Cart)= 0.00182562 RMS(Int)= 1.27543699 Iteration 40 RMS(Cart)= 0.00181566 RMS(Int)= 1.27456877 Iteration 41 RMS(Cart)= 0.00180626 RMS(Int)= 1.27370550 Iteration 42 RMS(Cart)= 0.00179739 RMS(Int)= 1.27284694 Iteration 43 RMS(Cart)= 0.00178900 RMS(Int)= 1.27199290 Iteration 44 RMS(Cart)= 0.00178106 RMS(Int)= 1.27114317 Iteration 45 RMS(Cart)= 0.00081421 RMS(Int)= 1.27075614 Iteration 46 RMS(Cart)= 0.00081468 RMS(Int)= 1.27036899 Iteration 47 RMS(Cart)= 0.00081519 RMS(Int)= 1.26998171 Iteration 48 RMS(Cart)= 0.00081577 RMS(Int)= 1.26959426 Iteration 49 RMS(Cart)= 0.00081636 RMS(Int)= 1.26920664 Iteration 50 RMS(Cart)= 0.00081703 RMS(Int)= 1.26881882 Iteration 51 RMS(Cart)= 0.00081773 RMS(Int)= 1.26843079 Iteration 52 RMS(Cart)= 0.00081846 RMS(Int)= 1.26804252 Iteration 53 RMS(Cart)= 0.00081921 RMS(Int)= 1.26765402 Iteration 54 RMS(Cart)= 0.00082001 RMS(Int)= 1.26726526 Iteration 55 RMS(Cart)= 0.00082084 RMS(Int)= 1.26687623 Iteration 56 RMS(Cart)= 0.00082179 RMS(Int)= 1.26648689 Iteration 57 RMS(Cart)= 0.00082343 RMS(Int)= 1.26609697 Iteration 58 RMS(Cart)= 0.00082512 RMS(Int)= 1.26570646 Iteration 59 RMS(Cart)= 0.00082690 RMS(Int)= 1.26531531 Iteration 60 RMS(Cart)= 0.00082869 RMS(Int)= 1.26492353 Iteration 61 RMS(Cart)= 0.00083056 RMS(Int)= 1.26453107 Iteration 62 RMS(Cart)= 0.00083253 RMS(Int)= 1.26413788 Iteration 63 RMS(Cart)= 0.00083444 RMS(Int)= 1.26374401 Iteration 64 RMS(Cart)= 0.00083640 RMS(Int)= 1.26334943 Iteration 65 RMS(Cart)= 0.00083842 RMS(Int)= 1.26295411 Iteration 66 RMS(Cart)= 0.00084042 RMS(Int)= 1.26255806 Iteration 67 RMS(Cart)= 0.00084247 RMS(Int)= 1.26216126 Iteration 68 RMS(Cart)= 0.00084448 RMS(Int)= 1.26176373 Iteration 69 RMS(Cart)= 0.00084647 RMS(Int)= 1.26136547 Iteration 70 RMS(Cart)= 0.00084839 RMS(Int)= 1.26096654 Iteration 71 RMS(Cart)= 0.00085024 RMS(Int)= 1.26056695 Iteration 72 RMS(Cart)= 0.00085197 RMS(Int)= 1.26016677 Iteration 73 RMS(Cart)= 0.00085355 RMS(Int)= 1.25976606 Iteration 74 RMS(Cart)= 0.00085491 RMS(Int)= 1.25936494 Iteration 75 RMS(Cart)= 0.00085590 RMS(Int)= 1.25896357 Iteration 76 RMS(Cart)= 0.00085730 RMS(Int)= 1.25856177 Iteration 77 RMS(Cart)= 0.00085929 RMS(Int)= 1.25815928 Iteration 78 RMS(Cart)= 0.00086108 RMS(Int)= 1.25775619 Iteration 79 RMS(Cart)= 0.00086252 RMS(Int)= 1.25735267 Iteration 80 RMS(Cart)= 0.00086347 RMS(Int)= 1.25694894 Iteration 81 RMS(Cart)= 0.00086275 RMS(Int)= 1.25654577 Iteration 82 RMS(Cart)= 0.00086170 RMS(Int)= 1.25614327 Iteration 83 RMS(Cart)= 0.00086004 RMS(Int)= 1.25574171 Iteration 84 RMS(Cart)= 0.00085732 RMS(Int)= 1.25534159 Iteration 85 RMS(Cart)= 0.00085320 RMS(Int)= 1.25494356 Iteration 86 RMS(Cart)= 0.00095429 RMS(Int)= 1.25449841 Iteration 87 RMS(Cart)= 0.00094450 RMS(Int)= 1.25405796 Iteration 88 RMS(Cart)= 0.00092964 RMS(Int)= 1.25362458 Iteration 89 RMS(Cart)= 0.00090718 RMS(Int)= 1.25320181 Iteration 90 RMS(Cart)= 0.00094379 RMS(Int)= 1.25276204 Iteration 91 RMS(Cart)= 0.00092573 RMS(Int)= 1.25233081 Iteration 92 RMS(Cart)= 0.00090221 RMS(Int)= 1.25191066 Iteration 93 RMS(Cart)= 0.00087932 RMS(Int)= 1.25150129 Iteration 94 RMS(Cart)= 0.00086134 RMS(Int)= 1.25110040 Iteration 95 RMS(Cart)= 0.00084874 RMS(Int)= 1.25070546 Iteration 96 RMS(Cart)= 0.00084039 RMS(Int)= 1.25031448 Iteration 97 RMS(Cart)= 0.00083517 RMS(Int)= 1.24992601 Iteration 98 RMS(Cart)= 0.00083217 RMS(Int)= 1.24953900 Iteration 99 RMS(Cart)= 0.00082934 RMS(Int)= 1.24915340 Iteration100 RMS(Cart)= 0.00082677 RMS(Int)= 1.24876908 New curvilinear step not converged. FormGI is forming the generalized inverse of G from B-inverse, IUseBI=4. RedQX1 iteration 1 Try 1 RMS(Cart)= 0.38231300 RMS(Int)= 1.77987676 XScale= 6.79590146 RedQX1 iteration 1 Try 2 RMS(Cart)= 0.38077863 RMS(Int)= 1.61407739 XScale= 3.27161142 RedQX1 iteration 1 Try 3 RMS(Cart)= 0.37904140 RMS(Int)= 1.50437295 XScale= 2.10585303 RedQX1 iteration 1 Try 4 RMS(Cart)= 0.39256164 RMS(Int)= 1.84833910 XScale= 1.44250070 RedQX1 iteration 1 Try 5 RMS(Cart)= 0.86839350 RMS(Int)= 2.43671693 XScale= 1.30935364 RedQX1 iteration 1 Try 6 RMS(Cart)= 1.79548374 RMS(Int)= 3.32280057 XScale= 0.91778731 RedQX1 iteration 2 Try 1 RMS(Cart)= 0.35909675 RMS(Int)= 2.58900052 XScale= 1.26039269 RedQX1 iteration 2 Try 2 RMS(Cart)= 0.51253340 RMS(Int)= 2.78681314 XScale= 1.17039204 RedQX1 iteration 2 Try 3 RMS(Cart)= 0.85086901 RMS(Int)= 3.20540686 XScale= 0.96269626 RedQX1 iteration 3 Try 1 RMS(Cart)= 0.51052140 RMS(Int)= 3.01345256 XScale= 1.04813463 RedQX1 iteration 3 Try 2 RMS(Cart)= 0.73885616 RMS(Int)= 3.39748721 XScale= 0.86700057 RedQX1 iteration 4 Try 1 RMS(Cart)= 0.59108492 RMS(Int)= 3.35012484 XScale= 0.90086068 RedQX1 iteration 5 Try 1 RMS(Cart)= 0.11821698 RMS(Int)= 3.07765060 XScale= 1.01840263 RedQX1 iteration 5 Try 2 RMS(Cart)= 0.12712255 RMS(Int)= 3.14828153 XScale= 0.98648436 RedQX1 iteration 6 Try 1 RMS(Cart)= 0.12203765 RMS(Int)= 3.14542185 XScale= 0.98775940 RedQX1 iteration 7 Try 1 RMS(Cart)= 0.02440753 RMS(Int)= 3.09107251 XScale= 1.01227313 RedQX1 iteration 7 Try 2 RMS(Cart)= 0.02476437 RMS(Int)= 3.10475241 XScale= 1.00605770 RedQX1 iteration 7 Try 3 RMS(Cart)= 0.02512974 RMS(Int)= 3.11869757 XScale= 0.99975625 RedQX1 iteration 7 Try 4 RMS(Cart)= 0.02550391 RMS(Int)= 3.13291554 XScale= 0.99336863 RedQX1 iteration 8 Try 1 RMS(Cart)= 0.02489181 RMS(Int)= 3.13257347 XScale= 0.99352189 RedQX1 iteration 9 Try 1 RMS(Cart)= 0.00497836 RMS(Int)= 3.12146727 XScale= 0.99850916 RedQX1 iteration 10 Try 1 RMS(Cart)= 0.00099567 RMS(Int)= 3.11925129 XScale= 0.99950682 RedQX1 iteration 10 Try 2 RMS(Cart)= 0.00099625 RMS(Int)= 3.11980543 XScale= 0.99925727 RedQX1 iteration 10 Try 3 RMS(Cart)= 0.00099683 RMS(Int)= 3.12036000 XScale= 0.99900758 RedQX1 iteration 10 Try 4 RMS(Cart)= 0.00099741 RMS(Int)= 3.12091498 XScale= 0.99875775 RedQX1 iteration 11 Try 1 RMS(Cart)= 0.00099645 RMS(Int)= 3.12091445 XScale= 0.99875799 RedQX1 iteration 12 Try 1 RMS(Cart)= 0.00019929 RMS(Int)= 3.12047088 XScale= 0.99895766 RedQX1 iteration 13 Try 1 RMS(Cart)= 0.00003986 RMS(Int)= 3.12038217 XScale= 0.99899759 RedQX1 iteration 14 Try 1 RMS(Cart)= 0.00000797 RMS(Int)= 3.12036443 XScale= 0.99900558 RedQX1 iteration 14 Try 2 RMS(Cart)= 0.00000797 RMS(Int)= 3.12036887 XScale= 0.99900358 RedQX1 iteration 14 Try 3 RMS(Cart)= 0.00000797 RMS(Int)= 3.12037330 XScale= 0.99900159 RedQX1 iteration 14 Try 4 RMS(Cart)= 0.00000797 RMS(Int)= 3.12037774 XScale= 0.99899959 RedQX1 iteration 15 Try 1 RMS(Cart)= 0.00000797 RMS(Int)= 3.12037774 XScale= 0.99899959 RedQX1 iteration 16 Try 1 RMS(Cart)= 0.00000159 RMS(Int)= 3.12037419 XScale= 0.99900119 RedQX1 iteration 16 Try 2 RMS(Cart)= 0.00000159 RMS(Int)= 3.12037507 XScale= 0.99900079 RedQX1 iteration 16 Try 3 RMS(Cart)= 0.00000159 RMS(Int)= 3.12037596 XScale= 0.99900039 RedQX1 iteration 16 Try 4 RMS(Cart)= 0.00000159 RMS(Int)= 3.12037685 XScale= 0.99899999 RedQX1 iteration 17 Try 1 RMS(Cart)= 0.00000159 RMS(Int)= 3.12037685 XScale= 0.99899999 RedQX1 iteration 18 Try 1 RMS(Cart)= 0.00000032 RMS(Int)= 3.12037614 XScale= 0.99900031 RedQX1 iteration 18 Try 2 RMS(Cart)= 0.00000032 RMS(Int)= 3.12037632 XScale= 0.99900023 RedQX1 iteration 18 Try 3 RMS(Cart)= 0.00000032 RMS(Int)= 3.12037649 XScale= 0.99900015 RedQX1 iteration 18 Try 4 RMS(Cart)= 0.00000032 RMS(Int)= 3.12037667 XScale= 0.99900007 RedQX1 iteration 18 Try 5 RMS(Cart)= 0.00000032 RMS(Int)= 3.12037685 XScale= 0.99899999 RedQX1 iteration 19 Try 1 RMS(Cart)= 0.00000032 RMS(Int)= 3.12037685 XScale= 0.99899999 RedQX1 iteration 20 Try 1 RMS(Cart)= 0.00000006 RMS(Int)= 3.12037671 XScale= 0.99900005 Iteration 1 RMS(Cart)= 0.23456521 RMS(Int)= 2.74178963 Iteration 2 RMS(Cart)= 0.27291731 RMS(Int)= 2.65812737 Iteration 3 RMS(Cart)= 0.27625481 RMS(Int)= 2.58007735 Iteration 4 RMS(Cart)= 0.01574930 RMS(Int)= 2.57505352 Iteration 5 RMS(Cart)= 0.01219038 RMS(Int)= 2.57115426 Iteration 6 RMS(Cart)= 0.01207929 RMS(Int)= 2.56728660 Iteration 7 RMS(Cart)= 0.01197244 RMS(Int)= 2.56344904 Iteration 8 RMS(Cart)= 0.01186937 RMS(Int)= 2.55964024 Iteration 9 RMS(Cart)= 0.01176966 RMS(Int)= 2.55585898 Iteration 10 RMS(Cart)= 0.01167300 RMS(Int)= 2.55210416 Iteration 11 RMS(Cart)= 0.01157914 RMS(Int)= 2.54837477 Iteration 12 RMS(Cart)= 0.01148787 RMS(Int)= 2.54466987 Iteration 13 RMS(Cart)= 0.01139899 RMS(Int)= 2.54098856 Iteration 14 RMS(Cart)= 0.01131236 RMS(Int)= 2.53733004 Iteration 15 RMS(Cart)= 0.01122782 RMS(Int)= 2.53369351 Iteration 16 RMS(Cart)= 0.01114526 RMS(Int)= 2.53004447 Iteration 17 RMS(Cart)= 0.01055821 RMS(Int)= 2.52669007 Iteration 18 RMS(Cart)= 0.01047709 RMS(Int)= 2.52335747 Iteration 19 RMS(Cart)= 0.01039740 RMS(Int)= 2.52004617 Iteration 20 RMS(Cart)= 0.01031896 RMS(Int)= 2.51675572 Iteration 21 RMS(Cart)= 0.01024152 RMS(Int)= 2.51348577 Iteration 22 RMS(Cart)= 0.01016466 RMS(Int)= 2.51023619 Iteration 23 RMS(Cart)= 0.01008757 RMS(Int)= 2.50700744 Iteration 24 RMS(Cart)= 0.01000736 RMS(Int)= 2.50380763 Iteration 25 RMS(Cart)= 0.00988202 RMS(Int)= 2.49241877 Iteration 26 RMS(Cart)= 0.25370194 RMS(Int)= 2.41769033 Iteration 27 RMS(Cart)= 0.22194675 RMS(Int)= 2.33566548 Iteration 28 RMS(Cart)= 0.19723538 RMS(Int)= 2.25308663 Iteration 29 RMS(Cart)= 0.18485412 RMS(Int)= 2.17350761 Iteration 30 RMS(Cart)= 0.02426951 RMS(Int)= 2.16247959 Iteration 31 RMS(Cart)= 0.02050024 RMS(Int)= 2.15314450 Iteration 32 RMS(Cart)= 0.01949548 RMS(Int)= 2.14427582 Iteration 33 RMS(Cart)= 0.01896109 RMS(Int)= 2.13565912 Iteration 34 RMS(Cart)= 0.01860313 RMS(Int)= 2.12721244 Iteration 35 RMS(Cart)= 0.01831773 RMS(Int)= 2.11889713 Iteration 36 RMS(Cart)= 0.01126253 RMS(Int)= 2.11377521 Iteration 37 RMS(Cart)= 0.01127760 RMS(Int)= 2.10864551 Iteration 38 RMS(Cart)= 0.01129086 RMS(Int)= 2.10350818 Iteration 39 RMS(Cart)= 0.01130242 RMS(Int)= 2.09836316 Iteration 40 RMS(Cart)= 0.01131166 RMS(Int)= 2.09321041 Iteration 41 RMS(Cart)= 0.01131222 RMS(Int)= 2.08804853 Iteration 42 RMS(Cart)= 0.01130518 RMS(Int)= 2.08287588 Iteration 43 RMS(Cart)= 0.01128182 RMS(Int)= 2.11697096 Iteration 44 RMS(Cart)= 0.04098132 RMS(Int)= 2.09782460 Iteration 45 RMS(Cart)= 0.01254187 RMS(Int)= 2.09146188 Iteration 46 RMS(Cart)= 0.01259144 RMS(Int)= 2.08501462 Iteration 47 RMS(Cart)= 0.01269363 RMS(Int)= 2.07846326 Iteration 48 RMS(Cart)= 0.01274756 RMS(Int)= 2.07184198 Iteration 49 RMS(Cart)= 0.01273066 RMS(Int)= 2.06519837 Iteration 50 RMS(Cart)= 0.01263810 RMS(Int)= 2.05858314 Iteration 51 RMS(Cart)= 0.01243866 RMS(Int)= 2.05204951 Iteration 52 RMS(Cart)= 0.00957702 RMS(Int)= 2.04697376 Iteration 53 RMS(Cart)= 0.00936155 RMS(Int)= 2.04198077 Iteration 54 RMS(Cart)= 0.00915134 RMS(Int)= 2.03711513 Iteration 55 RMS(Cart)= 0.00895243 RMS(Int)= 2.04832927 Iteration 56 RMS(Cart)= 0.04750857 RMS(Int)= 2.01587737 Iteration 57 RMS(Cart)= 0.02566941 RMS(Int)= 1.99768555 Iteration 58 RMS(Cart)= 0.02378076 RMS(Int)= 1.98081828 Iteration 59 RMS(Cart)= 0.02204469 RMS(Int)= 1.96536208 Iteration 60 RMS(Cart)= 0.02013733 RMS(Int)= 1.95146587 Iteration 61 RMS(Cart)= 0.01760992 RMS(Int)= 1.93954356 Iteration 62 RMS(Cart)= 0.01435000 RMS(Int)= 1.93002911 Iteration 63 RMS(Cart)= 0.01138258 RMS(Int)= 1.92262686 Iteration 64 RMS(Cart)= 0.00966710 RMS(Int)= 1.91643803 Iteration 65 RMS(Cart)= 0.00844989 RMS(Int)= 1.91109986 Iteration 66 RMS(Cart)= 0.00783224 RMS(Int)= 1.90620333 Iteration 67 RMS(Cart)= 0.00734081 RMS(Int)= 1.90165812 Iteration 68 RMS(Cart)= 0.00690592 RMS(Int)= 1.89742104 Iteration 69 RMS(Cart)= 0.00649933 RMS(Int)= 1.89346785 Iteration 70 RMS(Cart)= 0.00572720 RMS(Int)= 1.89001501 Iteration 71 RMS(Cart)= 0.00500151 RMS(Int)= 1.88702314 Iteration 72 RMS(Cart)= 0.00488974 RMS(Int)= 1.88411513 Iteration 73 RMS(Cart)= 0.00472748 RMS(Int)= 1.88131990 Iteration 74 RMS(Cart)= 0.00453679 RMS(Int)= 1.87865268 Iteration 75 RMS(Cart)= 0.00448934 RMS(Int)= 1.87602533 Iteration 76 RMS(Cart)= 0.00447993 RMS(Int)= 1.87341471 Iteration 77 RMS(Cart)= 0.00470177 RMS(Int)= 1.87068538 Iteration 78 RMS(Cart)= 0.00480246 RMS(Int)= 1.86791117 Iteration 79 RMS(Cart)= 0.00492372 RMS(Int)= 1.86508087 Iteration 80 RMS(Cart)= 0.00368747 RMS(Int)= 1.86297743 Iteration 81 RMS(Cart)= 0.00366642 RMS(Int)= 1.86089377 Iteration 82 RMS(Cart)= 0.00372706 RMS(Int)= 1.85878311 Iteration 83 RMS(Cart)= 0.00349590 RMS(Int)= 1.85681164 Iteration 84 RMS(Cart)= 0.00354247 RMS(Int)= 1.85482063 Iteration 85 RMS(Cart)= 0.00357260 RMS(Int)= 1.85281957 Iteration 86 RMS(Cart)= 0.00358591 RMS(Int)= 1.85081805 Iteration 87 RMS(Cart)= 0.00358396 RMS(Int)= 1.84882465 Iteration 88 RMS(Cart)= 0.00324131 RMS(Int)= 1.84702955 Iteration 89 RMS(Cart)= 0.00323690 RMS(Int)= 1.84524258 Iteration 90 RMS(Cart)= 0.00357511 RMS(Int)= 1.84327349 Iteration 91 RMS(Cart)= 0.00358933 RMS(Int)= 1.84130329 Iteration 92 RMS(Cart)= 0.00359945 RMS(Int)= 1.83933420 Iteration 93 RMS(Cart)= 0.00360704 RMS(Int)= 1.83736757 Iteration 94 RMS(Cart)= 0.00360981 RMS(Int)= 1.83540593 Iteration 95 RMS(Cart)= 0.00360797 RMS(Int)= 1.83345168 Iteration 96 RMS(Cart)= 0.00360591 RMS(Int)= 1.83150483 Iteration 97 RMS(Cart)= 0.00360286 RMS(Int)= 1.82956579 Iteration 98 RMS(Cart)= 0.00359629 RMS(Int)= 1.82763633 Iteration 99 RMS(Cart)= 0.00358103 RMS(Int)= 1.82572103 Iteration100 RMS(Cart)= 0.00300856 RMS(Int)= 1.82411983 New curvilinear step not converged. FormGI is forming the generalized inverse of G from B-inverse, IUseBI=4. RedQX1 iteration 1 Try 1 RMS(Cart)= 0.72153478 RMS(Int)= 2.44350753 XScale= 6.19602331 RedQX1 iteration 1 Try 2 RMS(Cart)= 0.72526560 RMS(Int)= 2.20803277 XScale= 3.27580697 RedQX1 iteration 1 Try 3 RMS(Cart)= 0.77083058 RMS(Int)= 2.32491917 XScale= 1.93932579 RedQX1 iteration 1 Try 4 RMS(Cart)= 1.09707345 RMS(Int)= 2.71155558 XScale= 1.68183989 RedQX1 iteration 1 Try 5 RMS(Cart)= 2.90342116 RMS(Int)= 4.56177127 XScale= 0.99931315 RedQX1 iteration 1 Try 6 RMS(Cart)= 5.34292365 RMS(Int)= 9.11884875 XScale= 0.39871192 RedQX1 iteration 2 Try 1 RMS(Cart)= 1.06858473 RMS(Int)= 5.36961381 XScale= 0.80549040 RedQX1 iteration 3 Try 1 RMS(Cart)= 0.21371695 RMS(Int)= 4.71540716 XScale= 0.95786337 RedQX1 iteration 4 Try 1 RMS(Cart)= 0.04274339 RMS(Int)= 4.59212724 XScale= 0.99096065 RedQX1 iteration 5 Try 1 RMS(Cart)= 0.00854868 RMS(Int)= 4.56782711 XScale= 0.99764068 RedQX1 iteration 6 Try 1 RMS(Cart)= 0.00170974 RMS(Int)= 4.56298182 XScale= 0.99897858 RedQX1 iteration 7 Try 1 RMS(Cart)= 0.00034195 RMS(Int)= 4.56201335 XScale= 0.99924623 RedQX1 iteration 7 Try 2 RMS(Cart)= 0.00034199 RMS(Int)= 4.56225548 XScale= 0.99917931 RedQX1 iteration 7 Try 3 RMS(Cart)= 0.00034203 RMS(Int)= 4.56249764 XScale= 0.99911238 RedQX1 iteration 7 Try 4 RMS(Cart)= 0.00034207 RMS(Int)= 4.56273983 XScale= 0.99904545 RedQX1 iteration 7 Try 5 RMS(Cart)= 0.00034211 RMS(Int)= 4.56298207 XScale= 0.99897851 RedQX1 iteration 8 Try 1 RMS(Cart)= 0.00034202 RMS(Int)= 4.56298201 XScale= 0.99897853 RedQX1 iteration 9 Try 1 RMS(Cart)= 0.00006840 RMS(Int)= 4.56278827 XScale= 0.99903206 RedQX1 iteration 9 Try 2 RMS(Cart)= 0.00006841 RMS(Int)= 4.56283670 XScale= 0.99901868 RedQX1 iteration 9 Try 3 RMS(Cart)= 0.00006841 RMS(Int)= 4.56288514 XScale= 0.99900529 RedQX1 iteration 9 Try 4 RMS(Cart)= 0.00006841 RMS(Int)= 4.56293358 XScale= 0.99899191 RedQX1 iteration 10 Try 1 RMS(Cart)= 0.00006841 RMS(Int)= 4.56293358 XScale= 0.99899191 RedQX1 iteration 11 Try 1 RMS(Cart)= 0.00001368 RMS(Int)= 4.56289483 XScale= 0.99900262 RedQX1 iteration 11 Try 2 RMS(Cart)= 0.00001368 RMS(Int)= 4.56290451 XScale= 0.99899994 RedQX1 iteration 12 Try 1 RMS(Cart)= 0.00001368 RMS(Int)= 4.56290451 XScale= 0.99899994 RedQX1 iteration 13 Try 1 RMS(Cart)= 0.00000274 RMS(Int)= 4.56289676 XScale= 0.99900208 RedQX1 iteration 13 Try 2 RMS(Cart)= 0.00000274 RMS(Int)= 4.56289870 XScale= 0.99900155 RedQX1 iteration 13 Try 3 RMS(Cart)= 0.00000274 RMS(Int)= 4.56290064 XScale= 0.99900101 RedQX1 iteration 13 Try 4 RMS(Cart)= 0.00000274 RMS(Int)= 4.56290258 XScale= 0.99900048 RedQX1 iteration 13 Try 5 RMS(Cart)= 0.00000274 RMS(Int)= 4.56290451 XScale= 0.99899994 RedQX1 iteration 14 Try 1 RMS(Cart)= 0.00000274 RMS(Int)= 4.56290451 XScale= 0.99899994 RedQX1 iteration 15 Try 1 RMS(Cart)= 0.00000055 RMS(Int)= 4.56290296 XScale= 0.99900037 RedQX1 iteration 15 Try 2 RMS(Cart)= 0.00000055 RMS(Int)= 4.56290335 XScale= 0.99900026 RedQX1 iteration 15 Try 3 RMS(Cart)= 0.00000055 RMS(Int)= 4.56290374 XScale= 0.99900016 RedQX1 iteration 15 Try 4 RMS(Cart)= 0.00000055 RMS(Int)= 4.56290413 XScale= 0.99900005 RedQX1 iteration 15 Try 5 RMS(Cart)= 0.00000055 RMS(Int)= 4.56290451 XScale= 0.99899994 RedQX1 iteration 16 Try 1 RMS(Cart)= 0.00000055 RMS(Int)= 4.56290451 XScale= 0.99899994 RedQX1 iteration 17 Try 1 RMS(Cart)= 0.00000011 RMS(Int)= 4.56290420 XScale= 0.99900003 RedQX1 iteration 17 Try 2 RMS(Cart)= 0.00000011 RMS(Int)= 4.56290428 XScale= 0.99900001 RedQX1 iteration 17 Try 3 RMS(Cart)= 0.00000011 RMS(Int)= 4.56290436 XScale= 0.99899998 RedQX1 iteration 18 Try 1 RMS(Cart)= 0.00000011 RMS(Int)= 4.56290436 XScale= 0.99899998 RedQX1 iteration 19 Try 1 RMS(Cart)= 0.00000002 RMS(Int)= 4.56290430 XScale= 0.99900000 Iteration 1 RMS(Cart)= 0.60740231 RMS(Int)= 4.35716501 Iteration 2 RMS(Cart)= 0.58358692 RMS(Int)= 4.32652657 Iteration 3 RMS(Cart)= 0.53570284 RMS(Int)= 4.29879395 Iteration 4 RMS(Cart)= 0.33991087 RMS(Int)= 4.27508472 Iteration 5 RMS(Cart)= 0.05607202 RMS(Int)= 4.26924263 Iteration 6 RMS(Cart)= 0.04777218 RMS(Int)= 4.26414150 Iteration 7 RMS(Cart)= 0.04298415 RMS(Int)= 4.25946597 Iteration 8 RMS(Cart)= 0.03976010 RMS(Int)= 4.25507030 Iteration 9 RMS(Cart)= 0.03742071 RMS(Int)= 4.25087260 Iteration 10 RMS(Cart)= 0.03561738 RMS(Int)= 4.24682340 Iteration 11 RMS(Cart)= 0.03416217 RMS(Int)= 4.24289066 Iteration 12 RMS(Cart)= 0.03294760 RMS(Int)= 4.23905236 Iteration 13 RMS(Cart)= 0.03190769 RMS(Int)= 4.23529266 Iteration 14 RMS(Cart)= 0.03099959 RMS(Int)= 4.23159972 Iteration 15 RMS(Cart)= 0.03019422 RMS(Int)= 4.22796443 Iteration 16 RMS(Cart)= 0.02947110 RMS(Int)= 4.22437961 Iteration 17 RMS(Cart)= 0.02881538 RMS(Int)= 4.22083945 Iteration 18 RMS(Cart)= 0.02821589 RMS(Int)= 4.21733917 Iteration 19 RMS(Cart)= 0.02765837 RMS(Int)= 4.21387495 Iteration 20 RMS(Cart)= 0.02713922 RMS(Int)= 4.21044348 Iteration 21 RMS(Cart)= 0.02665606 RMS(Int)= 4.20704188 Iteration 22 RMS(Cart)= 0.02620442 RMS(Int)= 4.20366766 Iteration 23 RMS(Cart)= 0.02578039 RMS(Int)= 4.20031874 Iteration 24 RMS(Cart)= 0.02537998 RMS(Int)= 4.19699359 Iteration 25 RMS(Cart)= 0.02499785 RMS(Int)= 4.19369248 Iteration 26 RMS(Cart)= 0.02462035 RMS(Int)= 4.19045625 Iteration 27 RMS(Cart)= 0.02404832 RMS(Int)= 4.18408348 Iteration 28 RMS(Cart)= 0.03889722 RMS(Int)= 4.17884561 Iteration 29 RMS(Cart)= 0.03865326 RMS(Int)= 4.17354491 Iteration 30 RMS(Cart)= 0.03857324 RMS(Int)= 4.16398954 Iteration 31 RMS(Cart)= 0.25751719 RMS(Int)= 4.13626265 Iteration 32 RMS(Cart)= 0.13892679 RMS(Int)= 4.11735681 Iteration 33 RMS(Cart)= 0.09339496 RMS(Int)= 4.10318860 Iteration 34 RMS(Cart)= 0.07694491 RMS(Int)= 4.09082095 Iteration 35 RMS(Cart)= 0.06805471 RMS(Int)= 4.07941727 Iteration 36 RMS(Cart)= 0.06207536 RMS(Int)= 4.06867216 Iteration 37 RMS(Cart)= 0.02246528 RMS(Int)= 4.06456566 Iteration 38 RMS(Cart)= 0.02278823 RMS(Int)= 4.06036784 Iteration 39 RMS(Cart)= 0.02311335 RMS(Int)= 4.05607796 Iteration 40 RMS(Cart)= 0.02344771 RMS(Int)= 4.05169409 Iteration 41 RMS(Cart)= 0.02379737 RMS(Int)= 4.04721348 Iteration 42 RMS(Cart)= 0.02416961 RMS(Int)= 4.04263220 Iteration 43 RMS(Cart)= 0.02457158 RMS(Int)= 4.03794520 Iteration 44 RMS(Cart)= 0.02500923 RMS(Int)= 4.03314639 Iteration 45 RMS(Cart)= 0.02548621 RMS(Int)= 4.02822910 Iteration 46 RMS(Cart)= 0.01016985 RMS(Int)= 4.02622392 Iteration 47 RMS(Cart)= 0.01055389 RMS(Int)= 4.02413861 Iteration 48 RMS(Cart)= 0.01097360 RMS(Int)= 4.02196575 Iteration 49 RMS(Cart)= 0.01143101 RMS(Int)= 4.01969749 Iteration 50 RMS(Cart)= 0.01193208 RMS(Int)= 4.01732474 Iteration 51 RMS(Cart)= 0.01247250 RMS(Int)= 4.01483910 Iteration 52 RMS(Cart)= 0.01307340 RMS(Int)= 4.01222659 Iteration 53 RMS(Cart)= 0.01382768 RMS(Int)= 4.00945429 Iteration 54 RMS(Cart)= 0.01466402 RMS(Int)= 4.00650380 Iteration 55 RMS(Cart)= 0.01557444 RMS(Int)= 4.00335780 Iteration 56 RMS(Cart)= 0.01654353 RMS(Int)= 4.00000120 Iteration 57 RMS(Cart)= 0.01753060 RMS(Int)= 3.99642629 Iteration 58 RMS(Cart)= 0.01848085 RMS(Int)= 3.99263556 Iteration 59 RMS(Cart)= 0.01933215 RMS(Int)= 3.98864364 Iteration 60 RMS(Cart)= 0.02016060 RMS(Int)= 3.98444665 Iteration 61 RMS(Cart)= 0.02160815 RMS(Int)= 3.97989590 Iteration 62 RMS(Cart)= 0.02267827 RMS(Int)= 3.97505599 Iteration 63 RMS(Cart)= 0.02272578 RMS(Int)= 3.97013281 Iteration 64 RMS(Cart)= 0.02109528 RMS(Int)= 3.96548667 Iteration 65 RMS(Cart)= 0.01788083 RMS(Int)= 3.96148302 Iteration 66 RMS(Cart)= 0.02901793 RMS(Int)= 3.95499432 Iteration 67 RMS(Cart)= 0.02289534 RMS(Int)= 3.94974638 Iteration 68 RMS(Cart)= 0.00904940 RMS(Int)= 3.94761622 Iteration 69 RMS(Cart)= 0.00953125 RMS(Int)= 3.94536470 Iteration 70 RMS(Cart)= 0.00987285 RMS(Int)= 3.94302372 Iteration 71 RMS(Cart)= 0.01004372 RMS(Int)= 3.94063288 Iteration 72 RMS(Cart)= 0.00995636 RMS(Int)= 3.93825326 Iteration 73 RMS(Cart)= 0.00904190 RMS(Int)= 3.93608234 Iteration 74 RMS(Cart)= 0.00816191 RMS(Int)= 3.93411497 Iteration 75 RMS(Cart)= 0.00588205 RMS(Int)= 3.93269052 Iteration 76 RMS(Cart)= 0.00543062 RMS(Int)= 3.93137215 Iteration 77 RMS(Cart)= 0.00523477 RMS(Int)= 3.93009875 Iteration 78 RMS(Cart)= 0.00513231 RMS(Int)= 3.92884803 Iteration 79 RMS(Cart)= 0.00507723 RMS(Int)= 3.92760868 Iteration 80 RMS(Cart)= 0.00505089 RMS(Int)= 3.92637387 Iteration 81 RMS(Cart)= 0.00428538 RMS(Int)= 3.92532401 Iteration 82 RMS(Cart)= 0.00432060 RMS(Int)= 3.92426434 Iteration 83 RMS(Cart)= 0.00436174 RMS(Int)= 3.92319342 Iteration 84 RMS(Cart)= 0.00440719 RMS(Int)= 3.92211023 Iteration 85 RMS(Cart)= 0.00445522 RMS(Int)= 3.92101413 Iteration 86 RMS(Cart)= 0.00450479 RMS(Int)= 3.91990482 Iteration 87 RMS(Cart)= 0.00455451 RMS(Int)= 3.91878238 Iteration 88 RMS(Cart)= 0.00460231 RMS(Int)= 3.91764731 Iteration 89 RMS(Cart)= 0.00464707 RMS(Int)= 3.91650039 Iteration 90 RMS(Cart)= 0.00468793 RMS(Int)= 3.91534260 Iteration 91 RMS(Cart)= 0.00472708 RMS(Int)= 3.91417389 Iteration 92 RMS(Cart)= 0.00476704 RMS(Int)= 3.91299394 Iteration 93 RMS(Cart)= 0.00480738 RMS(Int)= 3.91180271 Iteration 94 RMS(Cart)= 0.00484789 RMS(Int)= 3.91060016 Iteration 95 RMS(Cart)= 0.00488843 RMS(Int)= 3.90938634 Iteration 96 RMS(Cart)= 0.00492879 RMS(Int)= 3.90816134 Iteration 97 RMS(Cart)= 0.00496878 RMS(Int)= 3.90692530 Iteration 98 RMS(Cart)= 0.00500819 RMS(Int)= 3.90567841 Iteration 99 RMS(Cart)= 0.00504685 RMS(Int)= 3.90442091 Iteration100 RMS(Cart)= 0.00508455 RMS(Int)= 3.90315311 New curvilinear step not converged. FormGI is forming the generalized inverse of G from B-inverse, IUseBI=4. RedQX1 iteration 1 Try 1 RMS(Cart)= 1.55822896 RMS(Int)= 3.77843579 XScale= 6.57901124 RedQX1 iteration 1 Try 2 RMS(Cart)= 1.54897299 RMS(Int)= 3.61061817 XScale= 3.90580239 RedQX1 iteration 1 Try 3 RMS(Cart)= 1.69585341 RMS(Int)= 3.94220518 XScale= 2.88241687 RedQX1 iteration 1 Try 4 RMS(Cart)= 2.38133031 RMS(Int)= 5.29093052 XScale= 1.76405899 RedQX1 iteration 1 Try 5 RMS(Cart)= 6.78920205 RMS(Int)= 11.18411792 XScale= 0.56691361 RedQX1 iteration 2 Try 1 RMS(Cart)= 1.35784041 RMS(Int)= 6.31090825 XScale= 1.32761584 RedQX1 iteration 2 Try 2 RMS(Cart)= 1.82427742 RMS(Int)= 7.76245517 XScale= 0.97465601 RedQX1 iteration 3 Try 1 RMS(Cart)= 1.45942194 RMS(Int)= 7.46902250 XScale= 1.03423929 RedQX1 iteration 3 Try 2 RMS(Cart)= 2.35241692 RMS(Int)= 9.48526828 XScale= 0.72336239 RedQX1 iteration 4 Try 1 RMS(Cart)= 1.88193354 RMS(Int)= 9.06374374 XScale= 0.77281979 RedQX1 iteration 5 Try 1 RMS(Cart)= 0.37638671 RMS(Int)= 7.78167891 XScale= 0.97238549 RedQX1 iteration 6 Try 1 RMS(Cart)= 0.07527734 RMS(Int)= 7.53045378 XScale= 1.02158560 RedQX1 iteration 6 Try 2 RMS(Cart)= 0.07642623 RMS(Int)= 7.59362391 XScale= 1.00883500 RedQX1 iteration 6 Try 3 RMS(Cart)= 0.07758405 RMS(Int)= 7.65824234 XScale= 0.99606815 RedQX1 iteration 7 Try 1 RMS(Cart)= 0.07634270 RMS(Int)= 7.65720534 XScale= 0.99627091 RedQX1 iteration 8 Try 1 RMS(Cart)= 0.01526854 RMS(Int)= 7.60630686 XScale= 1.00630781 RedQX1 iteration 8 Try 2 RMS(Cart)= 0.01531381 RMS(Int)= 7.61904427 XScale= 1.00378060 RedQX1 iteration 8 Try 3 RMS(Cart)= 0.01535920 RMS(Int)= 7.63183504 XScale= 1.00125368 RedQX1 iteration 8 Try 4 RMS(Cart)= 0.01540473 RMS(Int)= 7.64467822 XScale= 0.99872732 RedQX1 iteration 9 Try 1 RMS(Cart)= 0.01533079 RMS(Int)= 7.64461653 XScale= 0.99873942 RedQX1 iteration 10 Try 1 RMS(Cart)= 0.00306616 RMS(Int)= 7.63439011 XScale= 1.00075022 RedQX1 iteration 10 Try 2 RMS(Cart)= 0.00306796 RMS(Int)= 7.63694726 XScale= 1.00024680 RedQX1 iteration 10 Try 3 RMS(Cart)= 0.00306977 RMS(Int)= 7.63950647 XScale= 0.99974340 RedQX1 iteration 10 Try 4 RMS(Cart)= 0.00307158 RMS(Int)= 7.64206774 XScale= 0.99924002 RedQX1 iteration 10 Try 5 RMS(Cart)= 0.00307339 RMS(Int)= 7.64463107 XScale= 0.99873668 RedQX1 iteration 11 Try 1 RMS(Cart)= 0.00306946 RMS(Int)= 7.64462779 XScale= 0.99873733 RedQX1 iteration 12 Try 1 RMS(Cart)= 0.00061389 RMS(Int)= 7.64257970 XScale= 0.99913946 RedQX1 iteration 12 Try 2 RMS(Cart)= 0.00061396 RMS(Int)= 7.64309175 XScale= 0.99903890 RedQX1 iteration 12 Try 3 RMS(Cart)= 0.00061404 RMS(Int)= 7.64360387 XScale= 0.99893834 RedQX1 iteration 13 Try 1 RMS(Cart)= 0.00061396 RMS(Int)= 7.64360381 XScale= 0.99893835 RedQX1 iteration 14 Try 1 RMS(Cart)= 0.00012279 RMS(Int)= 7.64319416 XScale= 0.99901879 RedQX1 iteration 14 Try 2 RMS(Cart)= 0.00012279 RMS(Int)= 7.64329657 XScale= 0.99899868 RedQX1 iteration 15 Try 1 RMS(Cart)= 0.00012279 RMS(Int)= 7.64329657 XScale= 0.99899868 RedQX1 iteration 16 Try 1 RMS(Cart)= 0.00002456 RMS(Int)= 7.64321464 XScale= 0.99901477 RedQX1 iteration 16 Try 2 RMS(Cart)= 0.00002456 RMS(Int)= 7.64323512 XScale= 0.99901074 RedQX1 iteration 16 Try 3 RMS(Cart)= 0.00002456 RMS(Int)= 7.64325560 XScale= 0.99900672 RedQX1 iteration 16 Try 4 RMS(Cart)= 0.00002456 RMS(Int)= 7.64327609 XScale= 0.99900270 RedQX1 iteration 16 Try 5 RMS(Cart)= 0.00002456 RMS(Int)= 7.64329657 XScale= 0.99899868 RedQX1 iteration 17 Try 1 RMS(Cart)= 0.00002456 RMS(Int)= 7.64329657 XScale= 0.99899868 RedQX1 iteration 18 Try 1 RMS(Cart)= 0.00000491 RMS(Int)= 7.64328018 XScale= 0.99900189 RedQX1 iteration 18 Try 2 RMS(Cart)= 0.00000491 RMS(Int)= 7.64328428 XScale= 0.99900109 RedQX1 iteration 18 Try 3 RMS(Cart)= 0.00000491 RMS(Int)= 7.64328838 XScale= 0.99900029 RedQX1 iteration 18 Try 4 RMS(Cart)= 0.00000491 RMS(Int)= 7.64329247 XScale= 0.99899948 RedQX1 iteration 19 Try 1 RMS(Cart)= 0.00000491 RMS(Int)= 7.64329247 XScale= 0.99899948 RedQX1 iteration 20 Try 1 RMS(Cart)= 0.00000098 RMS(Int)= 7.64328920 XScale= 0.99900012 RedQX1 iteration 20 Try 2 RMS(Cart)= 0.00000098 RMS(Int)= 7.64329002 XScale= 0.99899996 Old curvilinear step not converged, using linear step: SCX= 2.93D+01 DXMaxT= 1.25-314 SCLim= 6.24-315 Fact= 2.13-316 RedCar/ORedCr failed for GTrans. Error termination via Lnk1e in C:\G09W\l101.exe at Thu Oct 15 14:20:58 2015. Job cpu time: 0 days 0 hours 0 minutes 0.0 seconds. File lengths (MBytes): RWF= 5 Int= 0 D2E= 0 Chk= 1 Scr= 1