Default is to use a total of 4 processors: 4 via shared-memory 1 via Linda Entering Link 1 = C:\G09W\l1.exe PID= 4652. 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 31-Oct-2013 ****************************************** %chk=\\ic.ac.uk\homes\jrh111\3rdyearlabPhysical\DielsAlder\New folder\jhootonDA_ QST2.chk Default route: MaxDisk=10GB ------------------------------------- # opt=qst2 freq am1 geom=connectivity ------------------------------------- 1/5=1,14=-1,18=20,26=1,27=202,38=1,57=2/1,3; 2/9=110,12=2,17=6,18=5,40=1/2; 3/5=2,16=1,25=1,41=700000,71=1/1,2,3; 4/35=1/1; 5/5=2,35=1,38=5/2; 6/7=2,8=2,9=2,10=2,28=1/1; 7//1,2,3,16; 1/5=1,14=-1,18=20,26=1,27=202/3(2); 2/9=110/2; 99//99; 2/9=110/2; 3/5=2,16=1,25=1,41=700000,71=1,135=20/1,2,3; 4/5=5,16=3,35=1/1; 5/5=2,35=1,38=5/2; 7//1,2,3,16; 1/5=1,14=-1,18=20,26=1,27=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 -0.53471 1.49442 0. C -0.90079 0.21053 0. C 0. -0.92506 0. C 1.33351 -0.86078 0. C 1.25643 0.11812 1.49356 C 0.42438 1.15055 1.48378 H 0.51371 1.8194 0. H -1.27175 2.30786 0. H -1.97367 -0.05509 0. H -0.5028 -1.90935 0. H 1.88856 0.08617 0. H 1.95788 -1.7636 0. H 2.34844 0.23559 1.50025 H 0.90957 -0.92401 1.49564 H 0.77124 2.19268 1.4817 H -0.66763 1.03308 1.47709 Add virtual bond connecting atoms C5 and H11 Dist= 3.07D+00. Add virtual bond connecting atoms C6 and H7 Dist= 3.08D+00. Add virtual bond connecting atoms H13 and H11 Dist= 2.98D+00. Add virtual bond connecting atoms H14 and C4 Dist= 2.94D+00. Add virtual bond connecting atoms H15 and H7 Dist= 2.93D+00. -------------- jhootonDA_QST2 -------------- Symbolic Z-matrix: Charge = 0 Multiplicity = 1 C -1.47897 -0.04934 -0.11034 C -0.66917 -1.29049 -0.0446 C 0.66449 -1.29276 0.04465 C 1.47875 -0.0544 0.11001 C 0.69564 1.1771 -0.30387 C -0.6914 1.17924 0.30408 H -1.85191 0.07887 -1.16337 H -2.38178 -0.15321 0.54911 H -1.24008 -2.23117 -0.08794 H 1.23211 -2.23544 0.08857 H 2.38085 -0.16127 -0.54995 H 1.85272 0.07239 1.16289 H 0.61017 1.20634 -1.42191 H 1.24953 2.09781 0.01499 H -1.24221 2.10204 -0.01413 H -0.60551 1.20751 1.42214 Iteration 1 RMS(Cart)= 0.07851451 RMS(Int)= 0.83621568 Iteration 2 RMS(Cart)= 0.06282033 RMS(Int)= 0.81923521 Iteration 3 RMS(Cart)= 0.06276564 RMS(Int)= 0.80893044 Iteration 4 RMS(Cart)= 0.05966865 RMS(Int)= 0.80881232 Iteration 5 RMS(Cart)= 0.04687226 RMS(Int)= 0.81578411 Iteration 6 RMS(Cart)= 0.02811975 RMS(Int)= 0.82413321 Iteration 7 RMS(Cart)= 0.01360095 RMS(Int)= 0.82690809 Iteration 8 RMS(Cart)= 0.01386987 RMS(Int)= 0.82627550 Iteration 9 RMS(Cart)= 0.00486894 RMS(Int)= 0.82530252 Iteration 10 RMS(Cart)= 0.01811110 RMS(Int)= 0.81913461 Iteration 11 RMS(Cart)= 0.01781899 RMS(Int)= 0.81037701 Iteration 12 RMS(Cart)= 0.01601557 RMS(Int)= 0.80132719 Iteration 13 RMS(Cart)= 0.00650517 RMS(Int)= 0.79729607 Iteration 14 RMS(Cart)= 0.00352751 RMS(Int)= 0.79494504 Iteration 15 RMS(Cart)= 0.00236966 RMS(Int)= 0.79338582 Iteration 16 RMS(Cart)= 0.00185707 RMS(Int)= 0.79224694 Iteration 17 RMS(Cart)= 0.00162131 RMS(Int)= 0.79134372 Iteration 18 RMS(Cart)= 0.00150058 RMS(Int)= 0.79057771 Iteration 19 RMS(Cart)= 0.00142658 RMS(Int)= 0.78989718 Iteration 20 RMS(Cart)= 0.00137200 RMS(Int)= 0.78927327 Iteration 21 RMS(Cart)= 0.00132673 RMS(Int)= 0.78868947 Iteration 22 RMS(Cart)= 0.00128647 RMS(Int)= 0.78813628 Iteration 23 RMS(Cart)= 0.00124910 RMS(Int)= 0.78760811 Iteration 24 RMS(Cart)= 0.00121354 RMS(Int)= 0.78710156 Iteration 25 RMS(Cart)= 0.00120919 RMS(Int)= 0.78660954 Iteration 26 RMS(Cart)= 0.00121191 RMS(Int)= 0.78612775 Iteration 27 RMS(Cart)= 0.00121274 RMS(Int)= 0.78565433 Iteration 28 RMS(Cart)= 0.00121177 RMS(Int)= 0.78518832 Iteration 29 RMS(Cart)= 0.00120914 RMS(Int)= 0.78472914 Iteration 30 RMS(Cart)= 0.00120525 RMS(Int)= 0.78427638 Iteration 31 RMS(Cart)= 0.00120046 RMS(Int)= 0.78382974 Iteration 32 RMS(Cart)= 0.00119507 RMS(Int)= 0.78338898 Iteration 33 RMS(Cart)= 0.00118929 RMS(Int)= 0.78295393 Iteration 34 RMS(Cart)= 0.00118327 RMS(Int)= 0.78252441 Iteration 35 RMS(Cart)= 0.00117711 RMS(Int)= 0.78210029 Iteration 36 RMS(Cart)= 0.00117088 RMS(Int)= 0.78168143 Iteration 37 RMS(Cart)= 0.00116463 RMS(Int)= 0.78126772 Iteration 38 RMS(Cart)= 0.00115840 RMS(Int)= 0.78085906 Iteration 39 RMS(Cart)= 0.00115219 RMS(Int)= 0.78045532 Iteration 40 RMS(Cart)= 0.00114604 RMS(Int)= 0.78005643 Iteration 41 RMS(Cart)= 0.00113994 RMS(Int)= 0.77966229 Iteration 42 RMS(Cart)= 0.00113390 RMS(Int)= 0.77927281 Iteration 43 RMS(Cart)= 0.00112792 RMS(Int)= 0.77888791 Iteration 44 RMS(Cart)= 0.00112202 RMS(Int)= 0.77850749 Iteration 45 RMS(Cart)= 0.00111618 RMS(Int)= 0.77813150 Iteration 46 RMS(Cart)= 0.00111042 RMS(Int)= 0.77775984 Iteration 47 RMS(Cart)= 0.00110473 RMS(Int)= 0.77739244 Iteration 48 RMS(Cart)= 0.00109911 RMS(Int)= 0.77702923 Iteration 49 RMS(Cart)= 0.00109355 RMS(Int)= 0.77667013 Iteration 50 RMS(Cart)= 0.00108807 RMS(Int)= 0.77631509 Iteration 51 RMS(Cart)= 0.00108266 RMS(Int)= 0.77596402 Iteration 52 RMS(Cart)= 0.00107731 RMS(Int)= 0.77561686 Iteration 53 RMS(Cart)= 0.00107204 RMS(Int)= 0.77527356 Iteration 54 RMS(Cart)= 0.00106683 RMS(Int)= 0.77493403 Iteration 55 RMS(Cart)= 0.00106168 RMS(Int)= 0.77459823 Iteration 56 RMS(Cart)= 0.00105661 RMS(Int)= 0.77426609 Iteration 57 RMS(Cart)= 0.00105159 RMS(Int)= 0.77393755 Iteration 58 RMS(Cart)= 0.00104664 RMS(Int)= 0.77361255 Iteration 59 RMS(Cart)= 0.00104176 RMS(Int)= 0.77329104 Iteration 60 RMS(Cart)= 0.00103693 RMS(Int)= 0.77297295 Iteration 61 RMS(Cart)= 0.00103217 RMS(Int)= 0.77265825 Iteration 62 RMS(Cart)= 0.00102747 RMS(Int)= 0.77234686 Iteration 63 RMS(Cart)= 0.00102283 RMS(Int)= 0.77203874 Iteration 64 RMS(Cart)= 0.00101824 RMS(Int)= 0.77173383 Iteration 65 RMS(Cart)= 0.00101372 RMS(Int)= 0.77143210 Iteration 66 RMS(Cart)= 0.00100926 RMS(Int)= 0.77113347 Iteration 67 RMS(Cart)= 0.00100485 RMS(Int)= 0.77083792 Iteration 68 RMS(Cart)= 0.00100050 RMS(Int)= 0.77054539 Iteration 69 RMS(Cart)= 0.00099621 RMS(Int)= 0.77025583 Iteration 70 RMS(Cart)= 0.00099197 RMS(Int)= 0.76996920 Iteration 71 RMS(Cart)= 0.00098778 RMS(Int)= 0.76968545 Iteration 72 RMS(Cart)= 0.00098366 RMS(Int)= 0.76940454 Iteration 73 RMS(Cart)= 0.00097958 RMS(Int)= 0.76912642 Iteration 74 RMS(Cart)= 0.00097556 RMS(Int)= 0.76885106 Iteration 75 RMS(Cart)= 0.00097159 RMS(Int)= 0.76857841 Iteration 76 RMS(Cart)= 0.00096767 RMS(Int)= 0.76830844 Iteration 77 RMS(Cart)= 0.00096381 RMS(Int)= 0.76804109 Iteration 78 RMS(Cart)= 0.00096000 RMS(Int)= 0.76777634 Iteration 79 RMS(Cart)= 0.00095624 RMS(Int)= 0.76751414 Iteration 80 RMS(Cart)= 0.00095252 RMS(Int)= 0.76725446 Iteration 81 RMS(Cart)= 0.00094886 RMS(Int)= 0.76699726 Iteration 82 RMS(Cart)= 0.00094525 RMS(Int)= 0.76674250 Iteration 83 RMS(Cart)= 0.00094169 RMS(Int)= 0.76649015 Iteration 84 RMS(Cart)= 0.00093817 RMS(Int)= 0.76624017 Iteration 85 RMS(Cart)= 0.00093470 RMS(Int)= 0.76599253 Iteration 86 RMS(Cart)= 0.00093128 RMS(Int)= 0.76574719 Iteration 87 RMS(Cart)= 0.00092791 RMS(Int)= 0.76550412 Iteration 88 RMS(Cart)= 0.00092459 RMS(Int)= 0.76526330 Iteration 89 RMS(Cart)= 0.00092131 RMS(Int)= 0.76502468 Iteration 90 RMS(Cart)= 0.00091808 RMS(Int)= 0.76478823 Iteration 91 RMS(Cart)= 0.00091489 RMS(Int)= 0.76455393 Iteration 92 RMS(Cart)= 0.00091175 RMS(Int)= 0.76432175 Iteration 93 RMS(Cart)= 0.00090865 RMS(Int)= 0.76409165 Iteration 94 RMS(Cart)= 0.00090560 RMS(Int)= 0.76386361 Iteration 95 RMS(Cart)= 0.00090259 RMS(Int)= 0.76363759 Iteration 96 RMS(Cart)= 0.00089963 RMS(Int)= 0.76341357 Iteration 97 RMS(Cart)= 0.00089671 RMS(Int)= 0.76319153 Iteration 98 RMS(Cart)= 0.00089383 RMS(Int)= 0.76297143 Iteration 99 RMS(Cart)= 0.00089100 RMS(Int)= 0.76275324 Iteration100 RMS(Cart)= 0.00088821 RMS(Int)= 0.76253695 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)= 0.05876465 RMS(Int)= 0.82554687 XScale= 9.60968820 RedQX1 iteration 1 Try 2 RMS(Cart)= 0.05890002 RMS(Int)= 0.79066988 XScale= 4.82855698 RedQX1 iteration 1 Try 3 RMS(Cart)= 0.05996756 RMS(Int)= 0.76531417 XScale= 3.22862605 RedQX1 iteration 1 Try 4 RMS(Cart)= 0.06488686 RMS(Int)= 0.74935214 XScale= 2.40791514 RedQX1 iteration 1 Try 5 RMS(Cart)= 0.08993739 RMS(Int)= 0.74248277 XScale= 1.85979952 RedQX1 iteration 1 Try 6 RMS(Cart)= 0.06593219 RMS(Int)= 0.74125449 XScale= 1.76555533 RedQX1 iteration 2 Try 1 RMS(Cart)= 0.00764341 RMS(Int)= 0.74128292 XScale= 1.77147529 RedQX1 iteration 2 Try 2 RMS(Cart)= 0.00851960 RMS(Int)= 0.74136593 XScale= 1.77880082 RedQX1 iteration 2 Try 3 RMS(Cart)= 0.01015568 RMS(Int)= 0.74146720 XScale= 1.78889225 RedQX1 iteration 2 Try 4 RMS(Cart)= 0.01380363 RMS(Int)= 0.74147754 XScale= 1.80619114 RedQX1 iteration 2 Try 5 RMS(Cart)= 0.02579325 RMS(Int)= 0.74103697 XScale= 1.85410575 RedQX1 iteration 2 Try 6 RMS(Cart)= 0.02598307 RMS(Int)= 0.74027928 XScale= 1.92073086 RedQX1 iteration 3 Try 1 RMS(Cart)= 0.00439248 RMS(Int)= 0.74017393 XScale= 1.92584642 RedQX1 iteration 3 Try 2 RMS(Cart)= 0.00490695 RMS(Int)= 0.74007706 XScale= 1.92908323 RedQX1 iteration 3 Try 3 RMS(Cart)= 0.00573115 RMS(Int)= 0.73999063 XScale= 1.92932000 RedQX1 iteration 3 Try 4 RMS(Cart)= 0.00736342 RMS(Int)= 0.73992813 XScale= 1.92406382 RedQX1 iteration 3 Try 5 RMS(Cart)= 0.01244609 RMS(Int)= 0.73998094 XScale= 1.90435996 RedQX1 iteration 3 Try 6 RMS(Cart)= 0.01144822 RMS(Int)= 0.74014235 XScale= 1.87926283 RedQX1 iteration 4 Try 1 RMS(Cart)= 0.00181191 RMS(Int)= 0.74014716 XScale= 1.87669296 RedQX1 iteration 4 Try 2 RMS(Cart)= 0.00202822 RMS(Int)= 0.74014920 XScale= 1.87437705 RedQX1 iteration 4 Try 3 RMS(Cart)= 0.00238125 RMS(Int)= 0.74014413 XScale= 1.87269799 RedQX1 iteration 4 Try 4 RMS(Cart)= 0.00310653 RMS(Int)= 0.74012088 XScale= 1.87273171 RedQX1 iteration 4 Try 5 RMS(Cart)= 0.00549016 RMS(Int)= 0.74004282 XScale= 1.87912084 RedQX1 iteration 4 Try 6 RMS(Cart)= 0.00556649 RMS(Int)= 0.73994593 XScale= 1.89245073 RedQX1 iteration 5 Try 1 RMS(Cart)= 0.00093012 RMS(Int)= 0.73993697 XScale= 1.89401635 RedQX1 iteration 5 Try 2 RMS(Cart)= 0.00103664 RMS(Int)= 0.73993005 XScale= 1.89540568 RedQX1 iteration 5 Try 3 RMS(Cart)= 0.00120689 RMS(Int)= 0.73992645 XScale= 1.89640728 RedQX1 iteration 5 Try 4 RMS(Cart)= 0.00154928 RMS(Int)= 0.73992939 XScale= 1.89648141 RedQX1 iteration 5 Try 5 RMS(Cart)= 0.00266048 RMS(Int)= 0.73995270 XScale= 1.89349970 RedQX1 iteration 5 Try 6 RMS(Cart)= 0.00263064 RMS(Int)= 0.73998801 XScale= 1.88745662 RedQX1 iteration 6 Try 1 RMS(Cart)= 0.00043484 RMS(Int)= 0.73999083 XScale= 1.88670300 RedQX1 iteration 6 Try 2 RMS(Cart)= 0.00048459 RMS(Int)= 0.73999308 XScale= 1.88599470 RedQX1 iteration 6 Try 3 RMS(Cart)= 0.00056342 RMS(Int)= 0.73999407 XScale= 1.88541373 RedQX1 iteration 6 Try 4 RMS(Cart)= 0.00072116 RMS(Int)= 0.73999198 XScale= 1.88518807 RedQX1 iteration 6 Try 5 RMS(Cart)= 0.00123774 RMS(Int)= 0.73997992 XScale= 1.88629003 RedQX1 iteration 6 Try 6 RMS(Cart)= 0.00125289 RMS(Int)= 0.73996092 XScale= 1.88917473 RedQX1 iteration 7 Try 1 RMS(Cart)= 0.00021258 RMS(Int)= 0.73995894 XScale= 1.88957534 RedQX1 iteration 7 Try 2 RMS(Cart)= 0.00023680 RMS(Int)= 0.73995726 XScale= 1.88995919 RedQX1 iteration 7 Try 3 RMS(Cart)= 0.00027458 RMS(Int)= 0.73995617 XScale= 1.89028855 RedQX1 iteration 7 Try 4 RMS(Cart)= 0.00034887 RMS(Int)= 0.73995645 XScale= 1.89045876 RedQX1 iteration 7 Try 5 RMS(Cart)= 0.00058999 RMS(Int)= 0.73996115 XScale= 1.89002495 RedQX1 iteration 7 Try 6 RMS(Cart)= 0.00059430 RMS(Int)= 0.73996963 XScale= 1.88868815 RedQX1 iteration 8 Try 1 RMS(Cart)= 0.00010183 RMS(Int)= 0.73997056 XScale= 1.88848842 RedQX1 iteration 8 Try 2 RMS(Cart)= 0.00011348 RMS(Int)= 0.73997140 XScale= 1.88829156 RedQX1 iteration 8 Try 3 RMS(Cart)= 0.00013145 RMS(Int)= 0.73997201 XScale= 1.88811285 RedQX1 iteration 8 Try 4 RMS(Cart)= 0.00016626 RMS(Int)= 0.73997203 XScale= 1.88799699 RedQX1 iteration 8 Try 5 RMS(Cart)= 0.00027847 RMS(Int)= 0.73997001 XScale= 1.88814284 RedQX1 iteration 8 Try 6 RMS(Cart)= 0.00028161 RMS(Int)= 0.73996587 XScale= 1.88876339 RedQX1 iteration 9 Try 1 RMS(Cart)= 0.00004920 RMS(Int)= 0.73996535 XScale= 1.88886483 RedQX1 iteration 9 Try 2 RMS(Cart)= 0.00005488 RMS(Int)= 0.73996488 XScale= 1.88896683 RedQX1 iteration 9 Try 3 RMS(Cart)= 0.00006354 RMS(Int)= 0.73996450 XScale= 1.88906298 RedQX1 iteration 9 Try 4 RMS(Cart)= 0.00008002 RMS(Int)= 0.73996438 XScale= 1.88913383 RedQX1 iteration 9 Try 5 RMS(Cart)= 0.00013243 RMS(Int)= 0.73996517 XScale= 1.88909037 RedQX1 iteration 9 Try 6 RMS(Cart)= 0.00013332 RMS(Int)= 0.73996708 XScale= 1.88880504 RedQX1 iteration 10 Try 1 RMS(Cart)= 0.00002365 RMS(Int)= 0.73996734 XScale= 1.88875462 RedQX1 iteration 10 Try 2 RMS(Cart)= 0.00002642 RMS(Int)= 0.73996759 XScale= 1.88870292 RedQX1 iteration 10 Try 3 RMS(Cart)= 0.00003060 RMS(Int)= 0.73996780 XScale= 1.88865246 RedQX1 iteration 10 Try 4 RMS(Cart)= 0.00003842 RMS(Int)= 0.73996790 XScale= 1.88861138 RedQX1 iteration 10 Try 5 RMS(Cart)= 0.00006291 RMS(Int)= 0.73996760 XScale= 1.88861876 RedQX1 iteration 10 Try 6 RMS(Cart)= 0.00006302 RMS(Int)= 0.73996670 XScale= 1.88874903 RedQX1 iteration 11 Try 1 RMS(Cart)= 0.00001138 RMS(Int)= 0.73996657 XScale= 1.88877405 RedQX1 iteration 11 Try 2 RMS(Cart)= 0.00001274 RMS(Int)= 0.73996644 XScale= 1.88880016 RedQX1 iteration 11 Try 3 RMS(Cart)= 0.00001477 RMS(Int)= 0.73996632 XScale= 1.88882637 RedQX1 iteration 11 Try 4 RMS(Cart)= 0.00001850 RMS(Int)= 0.73996625 XScale= 1.88884934 RedQX1 iteration 11 Try 5 RMS(Cart)= 0.00002999 RMS(Int)= 0.73996635 XScale= 1.88885204 RedQX1 iteration 11 Try 6 RMS(Cart)= 0.00002977 RMS(Int)= 0.73996677 XScale= 1.88879304 RedQX1 iteration 12 Try 1 RMS(Cart)= 0.00000547 RMS(Int)= 0.73996684 XScale= 1.88878074 RedQX1 iteration 12 Try 2 RMS(Cart)= 0.00000613 RMS(Int)= 0.73996690 XScale= 1.88876771 RedQX1 iteration 12 Try 3 RMS(Cart)= 0.00000712 RMS(Int)= 0.73996696 XScale= 1.88875428 RedQX1 iteration 12 Try 4 RMS(Cart)= 0.00000891 RMS(Int)= 0.73996701 XScale= 1.88874179 RedQX1 iteration 12 Try 5 RMS(Cart)= 0.00001432 RMS(Int)= 0.73996698 XScale= 1.88873751 RedQX1 iteration 12 Try 6 RMS(Cart)= 0.00001405 RMS(Int)= 0.73996678 XScale= 1.88876398 RedQX1 iteration 13 Try 1 RMS(Cart)= 0.00000262 RMS(Int)= 0.73996675 XScale= 1.88877000 RedQX1 iteration 13 Try 2 RMS(Cart)= 0.00000295 RMS(Int)= 0.73996672 XScale= 1.88877646 RedQX1 iteration 13 Try 3 RMS(Cart)= 0.00000343 RMS(Int)= 0.73996668 XScale= 1.88878327 RedQX1 iteration 13 Try 4 RMS(Cart)= 0.00000430 RMS(Int)= 0.73996666 XScale= 1.88878993 RedQX1 iteration 13 Try 5 RMS(Cart)= 0.00000685 RMS(Int)= 0.73996666 XScale= 1.88879338 RedQX1 iteration 13 Try 6 RMS(Cart)= 0.00000663 RMS(Int)= 0.73996675 XScale= 1.88878162 RedQX1 iteration 14 Try 1 RMS(Cart)= 0.00000126 RMS(Int)= 0.73996677 XScale= 1.88877870 RedQX1 iteration 14 Try 2 RMS(Cart)= 0.00000142 RMS(Int)= 0.73996679 XScale= 1.88877552 RedQX1 iteration 14 Try 3 RMS(Cart)= 0.00000165 RMS(Int)= 0.73996680 XScale= 1.88877210 RedQX1 iteration 14 Try 4 RMS(Cart)= 0.00000207 RMS(Int)= 0.73996682 XScale= 1.88876861 RedQX1 iteration 14 Try 5 RMS(Cart)= 0.00000328 RMS(Int)= 0.73996682 XScale= 1.88876630 RedQX1 iteration 14 Try 6 RMS(Cart)= 0.00000313 RMS(Int)= 0.73996678 XScale= 1.88877146 RedQX1 iteration 15 Try 1 RMS(Cart)= 0.00000060 RMS(Int)= 0.73996677 XScale= 1.88877287 RedQX1 iteration 15 Try 2 RMS(Cart)= 0.00000068 RMS(Int)= 0.73996676 XScale= 1.88877443 RedQX1 iteration 15 Try 3 RMS(Cart)= 0.00000080 RMS(Int)= 0.73996675 XScale= 1.88877613 RedQX1 iteration 15 Try 4 RMS(Cart)= 0.00000100 RMS(Int)= 0.73996675 XScale= 1.88877794 RedQX1 iteration 15 Try 5 RMS(Cart)= 0.00000158 RMS(Int)= 0.73996674 XScale= 1.88877935 RedQX1 iteration 15 Try 6 RMS(Cart)= 0.00000147 RMS(Int)= 0.73996676 XScale= 1.88877711 RedQX1 iteration 16 Try 1 RMS(Cart)= 0.00000029 RMS(Int)= 0.73996677 XScale= 1.88877644 RedQX1 iteration 16 Try 2 RMS(Cart)= 0.00000033 RMS(Int)= 0.73996677 XScale= 1.88877568 RedQX1 iteration 16 Try 3 RMS(Cart)= 0.00000038 RMS(Int)= 0.73996677 XScale= 1.88877484 RedQX1 iteration 16 Try 4 RMS(Cart)= 0.00000048 RMS(Int)= 0.73996678 XScale= 1.88877391 RedQX1 iteration 16 Try 5 RMS(Cart)= 0.00000076 RMS(Int)= 0.73996678 XScale= 1.88877310 RedQX1 iteration 16 Try 6 RMS(Cart)= 0.00000070 RMS(Int)= 0.73996677 XScale= 1.88877405 RedQX1 iteration 17 Try 1 RMS(Cart)= 0.00000014 RMS(Int)= 0.73996677 XScale= 1.88877437 RedQX1 iteration 17 Try 2 RMS(Cart)= 0.00000016 RMS(Int)= 0.73996677 XScale= 1.88877474 RedQX1 iteration 17 Try 3 RMS(Cart)= 0.00000018 RMS(Int)= 0.73996677 XScale= 1.88877515 RedQX1 iteration 17 Try 4 RMS(Cart)= 0.00000023 RMS(Int)= 0.73996676 XScale= 1.88877562 RedQX1 iteration 17 Try 5 RMS(Cart)= 0.00000036 RMS(Int)= 0.73996676 XScale= 1.88877607 RedQX1 iteration 17 Try 6 RMS(Cart)= 0.00000033 RMS(Int)= 0.73996677 XScale= 1.88877568 RedQX1 iteration 18 Try 1 RMS(Cart)= 0.00000007 RMS(Int)= 0.73996677 XScale= 1.88877552 Iteration 1 RMS(Cart)= 0.12940639 RMS(Int)= 1.83028635 Iteration 2 RMS(Cart)= 0.12927945 RMS(Int)= 1.75044154 Iteration 3 RMS(Cart)= 0.12590880 RMS(Int)= 1.67410135 Iteration 4 RMS(Cart)= 0.11998595 RMS(Int)= 1.60317573 Iteration 5 RMS(Cart)= 0.00810053 RMS(Int)= 1.59853010 Iteration 6 RMS(Cart)= 0.00670604 RMS(Int)= 1.59468953 Iteration 7 RMS(Cart)= 0.00670020 RMS(Int)= 1.59085631 Iteration 8 RMS(Cart)= 0.00669279 RMS(Int)= 1.58703127 Iteration 9 RMS(Cart)= 0.00668434 RMS(Int)= 1.58321495 Iteration 10 RMS(Cart)= 0.00667514 RMS(Int)= 1.57940773 Iteration 11 RMS(Cart)= 0.00666542 RMS(Int)= 1.57560992 Iteration 12 RMS(Cart)= 0.00665523 RMS(Int)= 1.57182179 Iteration 13 RMS(Cart)= 0.00664461 RMS(Int)= 1.56804362 Iteration 14 RMS(Cart)= 0.00663353 RMS(Int)= 1.56427572 Iteration 15 RMS(Cart)= 0.00662185 RMS(Int)= 1.56051849 Iteration 16 RMS(Cart)= 0.00660798 RMS(Int)= 1.55677329 Iteration 17 RMS(Cart)= 0.00658352 RMS(Int)= 1.55304652 Iteration 18 RMS(Cart)= 0.00655867 RMS(Int)= 1.54933271 Iteration 19 RMS(Cart)= 0.00653309 RMS(Int)= 1.54118009 Iteration 20 RMS(Cart)= 0.08356298 RMS(Int)= 1.49185227 Iteration 21 RMS(Cart)= 0.07902644 RMS(Int)= 1.44738002 Iteration 22 RMS(Cart)= 0.00670692 RMS(Int)= 1.44382655 Iteration 23 RMS(Cart)= 0.00553481 RMS(Int)= 1.44090672 Iteration 24 RMS(Cart)= 0.00526216 RMS(Int)= 1.43814104 Iteration 25 RMS(Cart)= 0.00511912 RMS(Int)= 1.43546030 Iteration 26 RMS(Cart)= 0.00501244 RMS(Int)= 1.43284493 Iteration 27 RMS(Cart)= 0.00492607 RMS(Int)= 1.43028401 Iteration 28 RMS(Cart)= 0.00486057 RMS(Int)= 1.42776634 Iteration 29 RMS(Cart)= 0.00480515 RMS(Int)= 1.42528652 Iteration 30 RMS(Cart)= 0.00475355 RMS(Int)= 1.42284248 Iteration 31 RMS(Cart)= 0.00467975 RMS(Int)= 1.42044687 Iteration 32 RMS(Cart)= 0.00460559 RMS(Int)= 1.41809988 Iteration 33 RMS(Cart)= 0.00453613 RMS(Int)= 1.41579877 Iteration 34 RMS(Cart)= 0.00447068 RMS(Int)= 1.41354122 Iteration 35 RMS(Cart)= 0.00440869 RMS(Int)= 1.41132519 Iteration 36 RMS(Cart)= 0.00434978 RMS(Int)= 1.40914889 Iteration 37 RMS(Cart)= 0.00429373 RMS(Int)= 1.40701064 Iteration 38 RMS(Cart)= 0.00424018 RMS(Int)= 1.40490898 Iteration 39 RMS(Cart)= 0.00417864 RMS(Int)= 1.40284791 Iteration 40 RMS(Cart)= 0.00411797 RMS(Int)= 1.40082675 Iteration 41 RMS(Cart)= 0.00406016 RMS(Int)= 1.39884379 Iteration 42 RMS(Cart)= 0.00400499 RMS(Int)= 1.39689745 Iteration 43 RMS(Cart)= 0.00395065 RMS(Int)= 1.39498716 Iteration 44 RMS(Cart)= 0.00389869 RMS(Int)= 1.39311149 Iteration 45 RMS(Cart)= 0.00384899 RMS(Int)= 1.39126912 Iteration 46 RMS(Cart)= 0.00380147 RMS(Int)= 1.38945875 Iteration 47 RMS(Cart)= 0.00375601 RMS(Int)= 1.38767920 Iteration 48 RMS(Cart)= 0.00371332 RMS(Int)= 1.38592895 Iteration 49 RMS(Cart)= 0.00370496 RMS(Int)= 1.38419240 Iteration 50 RMS(Cart)= 0.00370147 RMS(Int)= 1.38246725 Iteration 51 RMS(Cart)= 0.00370301 RMS(Int)= 1.38075123 Iteration 52 RMS(Cart)= 0.00370542 RMS(Int)= 1.37904405 Iteration 53 RMS(Cart)= 0.00370806 RMS(Int)= 1.37734576 Iteration 54 RMS(Cart)= 0.00371575 RMS(Int)= 1.37565416 Iteration 55 RMS(Cart)= 0.00372504 RMS(Int)= 1.37396890 Iteration 56 RMS(Cart)= 0.00373670 RMS(Int)= 1.37228933 Iteration 57 RMS(Cart)= 0.00375532 RMS(Int)= 1.37061258 Iteration 58 RMS(Cart)= 0.00378192 RMS(Int)= 1.36893545 Iteration 59 RMS(Cart)= 0.00381777 RMS(Int)= 1.36725430 Iteration 60 RMS(Cart)= 0.00384336 RMS(Int)= 1.36557453 Iteration 61 RMS(Cart)= 0.00388036 RMS(Int)= 1.36389169 Iteration 62 RMS(Cart)= 0.00393200 RMS(Int)= 1.36220011 Iteration 63 RMS(Cart)= 0.00400165 RMS(Int)= 1.36049303 Iteration 64 RMS(Cart)= 0.00409236 RMS(Int)= 1.35876281 Iteration 65 RMS(Cart)= 0.00420202 RMS(Int)= 1.35700314 Iteration 66 RMS(Cart)= 0.00430286 RMS(Int)= 1.35521935 Iteration 67 RMS(Cart)= 0.00441248 RMS(Int)= 1.35340999 Iteration 68 RMS(Cart)= 0.00450628 RMS(Int)= 1.35158421 Iteration 69 RMS(Cart)= 0.00449434 RMS(Int)= 1.34978638 Iteration 70 RMS(Cart)= 0.00415771 RMS(Int)= 1.34814155 Iteration 71 RMS(Cart)= 0.00307011 RMS(Int)= 1.34692975 Iteration 72 RMS(Cart)= 0.00202380 RMS(Int)= 1.34612910 Iteration 73 RMS(Cart)= 0.00162115 RMS(Int)= 1.34548825 Iteration 74 RMS(Cart)= 0.00143608 RMS(Int)= 1.34492165 Iteration 75 RMS(Cart)= 0.00133049 RMS(Int)= 1.34439789 Iteration 76 RMS(Cart)= 0.00126167 RMS(Int)= 1.34390242 Iteration 77 RMS(Cart)= 0.00121281 RMS(Int)= 1.34342731 Iteration 78 RMS(Cart)= 0.00117614 RMS(Int)= 1.34296772 Iteration 79 RMS(Cart)= 0.00114589 RMS(Int)= 1.34252101 Iteration 80 RMS(Cart)= 0.00111999 RMS(Int)= 1.34208542 Iteration 81 RMS(Cart)= 0.00109802 RMS(Int)= 1.34165937 Iteration 82 RMS(Cart)= 0.00107912 RMS(Int)= 1.34124163 Iteration 83 RMS(Cart)= 0.00106276 RMS(Int)= 1.34083120 Iteration 84 RMS(Cart)= 0.00104800 RMS(Int)= 1.34042742 Iteration 85 RMS(Cart)= 0.00103504 RMS(Int)= 1.34002958 Iteration 86 RMS(Cart)= 0.00102327 RMS(Int)= 1.33963720 Iteration 87 RMS(Cart)= 0.00101238 RMS(Int)= 1.33924993 Iteration 88 RMS(Cart)= 0.00100270 RMS(Int)= 1.33886728 Iteration 89 RMS(Cart)= 0.00099358 RMS(Int)= 1.33848904 Iteration 90 RMS(Cart)= 0.00098519 RMS(Int)= 1.33811491 Iteration 91 RMS(Cart)= 0.00097793 RMS(Int)= 1.33774444 Iteration 92 RMS(Cart)= 0.00097060 RMS(Int)= 1.33737763 Iteration 93 RMS(Cart)= 0.00096392 RMS(Int)= 1.33701424 Iteration 94 RMS(Cart)= 0.00095747 RMS(Int)= 1.33665418 Iteration 95 RMS(Cart)= 0.00095125 RMS(Int)= 1.33629736 Iteration 96 RMS(Cart)= 0.00094487 RMS(Int)= 1.33594383 Iteration 97 RMS(Cart)= 0.00093853 RMS(Int)= 1.33559358 Iteration 98 RMS(Cart)= 0.00093171 RMS(Int)= 1.33524678 Iteration 99 RMS(Cart)= 0.00092440 RMS(Int)= 1.33490359 Iteration100 RMS(Cart)= 0.00091645 RMS(Int)= 1.33456424 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)= 0.30452661 RMS(Int)= 1.71512679 XScale= 6.63203447 RedQX1 iteration 1 Try 2 RMS(Cart)= 0.30362008 RMS(Int)= 1.53194000 XScale= 3.05497107 RedQX1 iteration 1 Try 3 RMS(Cart)= 0.30509424 RMS(Int)= 1.43757488 XScale= 1.82904884 RedQX1 iteration 1 Try 4 RMS(Cart)= 0.34569863 RMS(Int)= 1.58757299 XScale= 1.23064209 RedQX1 iteration 1 Try 5 RMS(Cart)= 0.70811386 RMS(Int)= 2.38916958 XScale= 1.17471845 RedQX1 iteration 1 Try 6 RMS(Cart)= 1.44269097 RMS(Int)= 3.11871272 XScale= 0.96553665 RedQX1 iteration 2 Try 1 RMS(Cart)= 0.28853819 RMS(Int)= 2.54737033 XScale= 1.18321920 RedQX1 iteration 2 Try 2 RMS(Cart)= 0.42602942 RMS(Int)= 2.72275054 XScale= 1.16238579 RedQX1 iteration 2 Try 3 RMS(Cart)= 0.70706545 RMS(Int)= 3.04798291 XScale= 1.02444807 RedQX1 iteration 2 Try 4 RMS(Cart)= 1.34867156 RMS(Int)= 3.84198239 XScale= 0.72201521 RedQX1 iteration 3 Try 1 RMS(Cart)= 0.53946862 RMS(Int)= 3.35891349 XScale= 0.89595243 RedQX1 iteration 4 Try 1 RMS(Cart)= 0.10789372 RMS(Int)= 3.11142219 XScale= 1.00055109 RedQX1 iteration 4 Try 2 RMS(Cart)= 0.11650793 RMS(Int)= 3.17467390 XScale= 0.97265540 RedQX1 iteration 5 Try 1 RMS(Cart)= 0.11184761 RMS(Int)= 3.17207954 XScale= 0.97379411 RedQX1 iteration 6 Try 1 RMS(Cart)= 0.02236952 RMS(Int)= 3.12324888 XScale= 0.99533788 RedQX1 iteration 7 Try 1 RMS(Cart)= 0.00447390 RMS(Int)= 3.11377058 XScale= 0.99951786 RedQX1 iteration 7 Try 2 RMS(Cart)= 0.00448745 RMS(Int)= 3.11613538 XScale= 0.99847617 RedQX1 iteration 8 Try 1 RMS(Cart)= 0.00448027 RMS(Int)= 3.11613159 XScale= 0.99847784 RedQX1 iteration 9 Try 1 RMS(Cart)= 0.00089605 RMS(Int)= 3.11424208 XScale= 0.99931025 RedQX1 iteration 9 Try 2 RMS(Cart)= 0.00089660 RMS(Int)= 3.11471423 XScale= 0.99910230 RedQX1 iteration 9 Try 3 RMS(Cart)= 0.00089714 RMS(Int)= 3.11518704 XScale= 0.99889403 RedQX1 iteration 10 Try 1 RMS(Cart)= 0.00089657 RMS(Int)= 3.11518673 XScale= 0.99889416 RedQX1 iteration 11 Try 1 RMS(Cart)= 0.00017931 RMS(Int)= 3.11480871 XScale= 0.99906069 RedQX1 iteration 11 Try 2 RMS(Cart)= 0.00017933 RMS(Int)= 3.11490320 XScale= 0.99901906 RedQX1 iteration 11 Try 3 RMS(Cart)= 0.00017936 RMS(Int)= 3.11499773 XScale= 0.99897743 RedQX1 iteration 12 Try 1 RMS(Cart)= 0.00017933 RMS(Int)= 3.11499772 XScale= 0.99897743 RedQX1 iteration 13 Try 1 RMS(Cart)= 0.00003587 RMS(Int)= 3.11492211 XScale= 0.99901074 RedQX1 iteration 13 Try 2 RMS(Cart)= 0.00003587 RMS(Int)= 3.11494101 XScale= 0.99900241 RedQX1 iteration 13 Try 3 RMS(Cart)= 0.00003587 RMS(Int)= 3.11495991 XScale= 0.99899408 RedQX1 iteration 14 Try 1 RMS(Cart)= 0.00003587 RMS(Int)= 3.11495991 XScale= 0.99899408 RedQX1 iteration 15 Try 1 RMS(Cart)= 0.00000717 RMS(Int)= 3.11494479 XScale= 0.99900075 RedQX1 iteration 15 Try 2 RMS(Cart)= 0.00000717 RMS(Int)= 3.11494857 XScale= 0.99899908 RedQX1 iteration 16 Try 1 RMS(Cart)= 0.00000717 RMS(Int)= 3.11494857 XScale= 0.99899908 RedQX1 iteration 17 Try 1 RMS(Cart)= 0.00000143 RMS(Int)= 3.11494554 XScale= 0.99900041 RedQX1 iteration 17 Try 2 RMS(Cart)= 0.00000143 RMS(Int)= 3.11494630 XScale= 0.99900008 RedQX1 iteration 17 Try 3 RMS(Cart)= 0.00000143 RMS(Int)= 3.11494706 XScale= 0.99899975 RedQX1 iteration 18 Try 1 RMS(Cart)= 0.00000143 RMS(Int)= 3.11494706 XScale= 0.99899975 RedQX1 iteration 19 Try 1 RMS(Cart)= 0.00000029 RMS(Int)= 3.11494645 XScale= 0.99900001 RedQX1 iteration 19 Try 2 RMS(Cart)= 0.00000029 RMS(Int)= 3.11494660 XScale= 0.99899995 RedQX1 iteration 20 Try 1 RMS(Cart)= 0.00000029 RMS(Int)= 3.11494660 XScale= 0.99899995 Old curvilinear step not converged, using linear step: SCX= 8.91D+00 DXMaxT= 1.25-314 SCLim= 6.24-315 Fact= 7.01-316 RedCar/ORedCr failed for GTrans. Error termination via Lnk1e in C:\G09W\l101.exe at Thu Oct 31 15:43:04 2013. 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