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  1. .gitattributes +5 -0
  2. CylinderKnMa/Kn0p26/simulation0543_Kn0p26Ma6p2/output/grid.300000.dat +3 -0
  3. CylinderKnMa/Kn0p26/simulation0547_Kn0p26Ma6p6/output/grid.300000.dat +3 -0
  4. CylinderKnMa/Kn0p26/simulation0548_Kn0p26Ma6p7/output/grid.300000.dat +3 -0
  5. CylinderKnMa/Kn0p26/simulation0549_Kn0p26Ma6p8/output/grid.300000.dat +3 -0
  6. CylinderKnMa/Kn0p26/simulation0550_Kn0p26Ma6p9/output/grid.300000.dat +3 -0
  7. CylinderKnMa/Kn0p30/simulation0606_Kn0p30Ma2p5/Lambda/Lambda_2_300000.vtu +0 -0
  8. CylinderKnMa/Kn0p30/simulation0606_Kn0p30Ma2p5/Lambda/Lambda_300000.pvtu +21 -0
  9. CylinderKnMa/Kn0p30/simulation0606_Kn0p30Ma2p5/Lambda/Lambda_3_300000.vtu +27 -0
  10. CylinderKnMa/Kn0p30/simulation0606_Kn0p30Ma2p5/output/lambdakn.300000.dat +0 -0
  11. CylinderKnMa/Kn0p30/simulation0606_Kn0p30Ma2p5/output/surf.300000.dat +209 -0
  12. CylinderKnMa/Kn0p30/simulation0606_Kn0p30Ma2p5/surf/Surf_300000.vtu +38 -0
  13. CylinderKnMa/Kn0p30/simulation0606_Kn0p30Ma2p5/surf/geom.surf +610 -0
  14. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/Grid.pvd +9 -0
  15. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/Lambda.pvd +9 -0
  16. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/Lambda/Lambda_0_300000.vtu +0 -0
  17. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/Lambda/Lambda_1_300000.vtu +0 -0
  18. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/Lambda/Lambda_2_300000.vtu +0 -0
  19. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/Lambda/Lambda_300000.pvtu +21 -0
  20. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/Lambda/Lambda_3_300000.vtu +27 -0
  21. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/Surf.pvd +9 -0
  22. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/config.txt +78 -0
  23. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/cylinder.surf +410 -0
  24. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/gas.species +14 -0
  25. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/gas.vhs +9 -0
  26. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/grid/Grid_0_300000.vtu +0 -0
  27. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/grid/Grid_1_300000.vtu +0 -0
  28. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/grid/Grid_2_300000.vtu +0 -0
  29. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/grid/Grid_300000.pvtu +29 -0
  30. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/grid/Grid_3_300000.vtu +0 -0
  31. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/grid/final-grid.dat +0 -0
  32. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/log.sparta +318 -0
  33. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/mir.txt +3 -0
  34. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/output/lambdakn.300000.dat +0 -0
  35. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/output/surf.300000.dat +209 -0
  36. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/runmpirun128.sh +18 -0
  37. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/runmpirun64.sh +18 -0
  38. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/slurm-28429356.out +204 -0
  39. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/surf/Surf_300000.vtu +38 -0
  40. CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/surf/geom.surf +610 -0
  41. CylinderKnMa/Kn0p30/simulation0608_Kn0p30Ma2p7/Grid.pvd +9 -0
  42. CylinderKnMa/Kn0p30/simulation0608_Kn0p30Ma2p7/Lambda.pvd +9 -0
  43. CylinderKnMa/Kn0p30/simulation0608_Kn0p30Ma2p7/Lambda/Lambda_0_300000.vtu +0 -0
  44. CylinderKnMa/Kn0p30/simulation0608_Kn0p30Ma2p7/Lambda/Lambda_1_300000.vtu +0 -0
  45. CylinderKnMa/Kn0p30/simulation0608_Kn0p30Ma2p7/Lambda/Lambda_2_300000.vtu +0 -0
  46. CylinderKnMa/Kn0p30/simulation0608_Kn0p30Ma2p7/Lambda/Lambda_300000.pvtu +21 -0
  47. CylinderKnMa/Kn0p30/simulation0608_Kn0p30Ma2p7/Lambda/Lambda_3_300000.vtu +27 -0
  48. CylinderKnMa/Kn0p30/simulation0608_Kn0p30Ma2p7/Surf.pvd +9 -0
  49. CylinderKnMa/Kn0p30/simulation0608_Kn0p30Ma2p7/config.txt +78 -0
  50. CylinderKnMa/Kn0p30/simulation0608_Kn0p30Ma2p7/cylinder.surf +410 -0
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_AQAAAACAAABwLwAAnwcAAA==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AQAAAACAAABwLwAA0QEAAA==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eJzt1k0rAwAAxvHUMGZmxomDw9LchaYxpB28Hb0kMlZrJbF5mzGr0awxbDUJpSwTNlGUpEwj5eBkzfKyD4ASRy/zJZ7Tc/p9g39/x2c8ajMK1A4K0aNMabKLUynI9eni8Ow2RRm4aiifq0mjIM1lu1WtcYpyxnJ31D6cTkG6w1+KTomQglwVFmx07VCU/ma1rKcug4IMeXWO3keK8vTB+a0bzaQgI0UHQ3qpiIL0LUqSa0hRbt6XvlfUZ1GQe4UdfZXPFOWJ1hpTjYspyIvAVvIMsynI27eby9p9ijL6n3GNhIJMmPOCmgRFOfKyJvWrcijI7pXGfJeTokxOYct8lKI0PA06F+RSCnLAJoi4BylKk9z3u3hOUZqvS5TLolwK0mo4M3naKEq7uCXk9VOU/ZGfw4kPitKoX3q1VMsoyDGRXDHloigng8daa4yi/AOXsFq+AQAAAACAAABwLwAAGykAAA==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AQAAAACAAABwLwAAKCIAAA==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AQAAAACAAADoSgAAcA8AAA==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AgAAAACAAADAPQAATRQAAO4JAAA=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AQAAAACAAABwLwAA+wcAAA==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eJzj5BwFo2AUjIJRMPwBAGORNV8=
26
+ </AppendedData>
27
+ </VTKFile>
CylinderKnMa/Kn0p30/simulation0606_Kn0p30Ma2p5/output/lambdakn.300000.dat ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p30/simulation0606_Kn0p30Ma2p5/output/surf.300000.dat ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ITEM: TIMESTEP
2
+ 300000
3
+ ITEM: NUMBER OF SURFS
4
+ 200
5
+ ITEM: BOX BOUNDS oo oo pp
6
+ -5 6
7
+ -5 5
8
+ -0.5 0.5
9
+ ITEM: SURFS id v1x v1y v2x v2y f_2[1] f_2[2] f_2[3] f_2[4] f_2[5] f_2[6] f_2[7] f_2[8] f_2[9] f_2[10] f_2[11]
10
+ 1 0.5 0 0.49975 -0.015705 0.00499 0.059338 -0.05933 0.00093204 -3.3884e-06 -0.00021569 -0.00093198 1.1252e-05 3.2924 0 0
11
+ 129 -0.31871 0.38526 -0.30645 0.39508 0.09367 1.1506 0.71941 -0.89797 0.16536 0.13248 0.013897 -0.012024 104.49 0 0
12
+ 2 0.49975 -0.015705 0.49901 -0.031395 0.00553 0.064516 -0.064444 0.0030391 -2.8226e-05 -0.00059853 -0.0010127 3.8335e-05 3.4036 0 0
13
+ 130 -0.30645 0.39508 -0.29389 0.40451 0.09078 1.1085 0.66559 -0.88649 0.15947 0.11973 0.01296 -0.012044 93.178 0 0
14
+ 3 0.49901 -0.031395 0.49778 -0.047054 0.00464 0.055213 -0.055043 0.004332 -5.6582e-05 -0.00071894 -0.00086546 5.6751e-05 2.5612 0 0
15
+ 131 -0.29389 0.40451 -0.28104 0.41354 0.08788 1.0706 0.61557 -0.87587 0.17655 0.12408 0.012442 -0.011809 99.918 0 0
16
+ 4 0.49778 -0.047054 0.49606 -0.062667 0.00504 0.05999 -0.059627 0.0065829 -0.00015896 -0.0014398 -0.00093908 8.0785e-05 3.5596 0 0
17
+ 132 -0.28104 0.41354 -0.26791 0.42216 0.08461 1.0337 0.56753 -0.86398 0.16716 0.1098 0.01154 -0.011846 88.861 0 0
18
+ 5 0.49606 -0.062667 0.49384 -0.078217 0.00503 0.060348 -0.059746 0.008503 2.0022e-05 0.00014068 -0.00093813 0.00013577 2.475 0 0
19
+ 133 -0.26791 0.42216 -0.25452 0.43037 0.07956 0.96895 0.50627 -0.82616 0.16271 0.099709 0.010508 -0.011411 82.751 0 0
20
+ 6 0.49384 -0.078217 0.49114 -0.093691 0.00511 0.059372 -0.058488 0.010208 0.00036711 0.0021035 -0.00091292 0.00019338 1.7992 0 0
21
+ 134 -0.25452 0.43037 -0.24088 0.43815 0.07575 0.92785 0.45971 -0.80596 0.18083 0.10314 0.010061 -0.011039 82.57 0 0
22
+ 7 0.49114 -0.093691 0.48796 -0.10907 0.00505 0.057217 -0.056028 0.011603 -0.00052595 -0.0025397 -0.00088832 0.00014236 2.5988 0 0
23
+ 135 -0.24088 0.43815 -0.227 0.4455 0.07176 0.87285 0.40843 -0.77139 0.16156 0.085543 0.0089531 -0.010773 75.927 0 0
24
+ 8 0.48796 -0.10907 0.48429 -0.12434 0.00445 0.050959 -0.049551 0.011896 -0.00033362 -0.0013896 -0.00078356 0.00016503 0.94049 0 0
25
+ 136 -0.227 0.4455 -0.21289 0.45241 0.06838 0.83704 0.36825 -0.75168 0.18237 0.089341 0.0086487 -0.010404 77.364 0 0
26
+ 9 0.48429 -0.12434 0.48015 -0.1395 0.0044 0.050194 -0.048415 0.013245 -0.0010605 -0.0038764 -0.00077713 0.00014716 3.5587 0 0
27
+ 137 -0.21289 0.45241 -0.19857 0.45888 0.06464 0.78249 0.32201 -0.71317 0.16575 0.074841 0.0076614 -0.010026 71.237 0 0
28
+ 10 0.48015 -0.1395 0.47553 -0.15451 0.00422 0.046885 -0.044812 0.013786 -0.00018712 -0.00060823 -0.00070682 0.00020699 2.3615 0 0
29
+ 138 -0.19857 0.45888 -0.18406 0.46489 0.06108 0.73283 0.28044 -0.67704 0.17141 0.071 0.0070973 -0.0095193 70.154 0 0
30
+ 11 0.47553 -0.15451 0.47044 -0.16937 0.00444 0.04986 -0.047172 0.016151 4.826e-05 0.00014096 -0.00074019 0.0002559 2.5602 0 0
31
+ 139 -0.18406 0.46489 -0.16937 0.47044 0.05891 0.70983 0.25091 -0.66401 0.17668 0.06676 0.0067162 -0.0093812 70.16 0 0
32
+ 12 0.47044 -0.16937 0.46489 -0.18406 0.00391 0.044486 -0.041614 0.015725 -0.00064442 -0.0017054 -0.00066377 0.0002202 3.0228 0 0
33
+ 140 -0.16937 0.47044 -0.15451 0.47553 0.05411 0.65256 0.21138 -0.61738 0.16911 0.0579 0.0059764 -0.0087879 59.076 0 0
34
+ 13 0.46489 -0.18406 0.45888 -0.19857 0.00363 0.040065 -0.037016 0.015332 0.00070009 0.0016902 -0.00057042 0.00026738 1.8793 0 0
35
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AQAAAACAAABABgAA8AUAAA==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AQAAAACAAABABgAAFAYAAA==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AQAAAACAAABABgAAEwYAAA==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AQAAAACAAABABgAAHAYAAA==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AQAAAACAAABABgAAIQYAAA==eJwtk407FAYcxxO7sUJXSUgPWsIwKmHhN6+9aJWwktKRaJozLuUcud3YsVy7F/diEvJ+lfc7Oq7f3blNKqJlHSUaWehFJRVZe+rZ9w/4fJ/n83y/+xPn5/f72+OPu7cd7jvri68c/hr958wWtF1wLPWVYC/G7hK+T/jBCi7dLZ4J3xwJjVpWBmu6o9Fua3pprPpbnFvrGRujTMDjB2pmNzz1xXI/U8c+qhXwBPSdr6fCkbIiiLypPhxCloe89dUcgdz8cW0yIwTqpZQLzuuTYP8CPerLz1KB2lBgMn80BQJH16VmidOhe9JLarYhAwIJdDvyPQaw5ffnn0dkQUa/J3VfVRbsvvDIsMsjB2q7nS1o8tNwSLL+gXA2ByDBbk/k9xyYfyslVTuyISJ64SnW5xxwa7OwcnnChRoHjy+NzHhwzNbiSQadD6dWdXH4hwTA4Ahd6hVCWDN40/bqTQH8aezTPfdeBP5TyH+sEQFoLV8TOCaCya9CgrnJIjBQEPyyvxBCouWvwwHXBNBndV7UpiUAzy2jrXmyPJg2KjM5XcGDPdYuTVoaNtRd3Gj7yeAZeNjnToiuZcLyHZNr08oZYJ9zfoZYcwKMk19vj2sggVfC8SFaJwl3pejtTLegYueYmHrmKhMX2r+YZGrYeI+4c1HENB/V6wq3OvWdxbzYCIPWZ8X4bohoJC4oxcq6Pd7+fZX4XYc+FpCr0fIkscJGWIO5VxgbD/fWoYV+5Y0u1wZ0e6OKFpOa0MUHgmvDm9A37M3sfqEUFXpZum6ZMlx9r1By17ENmee/LrrKa8P5OIMlN3pb8a3heHOtNqJ3s3BjwKTif64C3TLtXGjFSkzQ/55PSlSg3PxB07B/Ozqd8/Z9r9OOVjkRAfX3VKgka6Q2jUq0PFHRQ2UpsfQDvqwdLxn7uvfWqJD909KYgX+VyDqb5flkCvGZNntA3alEu+plPX4aBeqbzq5r2afEN8Ej5QVqBSpSCPrzy9rwdE5Xh6REhuVypbF1sBzLTGdoUYVSJJ2UvVRTGlAntHSvdl4DxryVLX4/XoPNtquN+6zEKCcTV06aVaHrrMhQ93gF/mUyZCwUZyJB9/SXGXYU8LgekfbC3g3aeLt+jTcphp6n7Ci6XynYPZQslQWeh6Rjt+JzDlTBjrKNBR2RdVBUp9a+VtEEcSXRSXGxdWBwJ86QVtIC/WvFzQSpDBonKBKjuVZYOqezO9f+MtjYP6c32CIs+BgFMKrmFpRtUsL/fmCQ1jLaEqyCm9uemR2iqeAo50kauKhAE81KzQ5oBzEjaFshXQUbKq9HRb1UQu+BSo7gWjtYm7gvog0oYfPQLpaQrIJG2ou63cdUYBmm0CEPKiEqc+roSLYSBh7Udpq+UoDmXNjS4oorsD5pxUxTO8Kn3SZBA2Zt0DVhTmb+fBkMex8ZRMXKoPxOzOG1YxJosXL21h+SgktUTFGHTSPwVup8a+DQAEeCa6YcjevhdfLwWWL5Jai6avn3WIgYJHOh9GebKkGHle8nHy6FlWm/8Yzzi+HQx6ICeNFdsjjUmQ+jSxIpdiZsqHKncvTeZEEVv7Bf75dUMPimf/zT5EgguOraOqZHoGvjjuTmkhT04v95jkth4F7RlTtLVjGRUDQ26m/NxgwUOYQZcdBhXcl0FpuHYUOK0QAOH/HITuHvagGae437MaoFuI/Tq7VNI0SjzabM2YMiLOLoskgjv2G8+arH3yzOx0WNPd3frRAhMaEwo/WxEK+Z/LL5/qgQuToPPrO5zcPJsb8TaIw8vL86k56mx8fqwD+cuZ5cbJR+GBgXc/u5oUQyFz/el8RBeZI8vsInF/8oDVEtS2VhHfvy+qpN2bjlklN6rWU25k9N+W7fR0d1SfzkwSQGTru+66RoUnDVBfeHJ26n49bbodf/saahX7JtdOFwIiYi677sIgVldA9Se0oSlhOO8lPU3jiSeHEs724kBpjrUTxWErFz++DQxPZQvFXUXsic2ArmHUPhTglLkBrjFuITE48ht6i+PUxPpDyeKHp+5iC8TuxnjdgHwUFGOJv9ygdmLkq8Xf2DwKmgXI8uoKAl/Ybkkzte8B/28ikQAQAAAACAAABABgAAOAYAAA==eJwt1f0/FHYcAHCdEz2JW7V5jKy4y0OdhzzugzvO07lTkpA87NwdyUNNOvO4Gd08nIe783TuLi3K8xxh8/rG3UklRIqFV7XZFFNmxaxp+2H/wfu39/aY+FFVrj9idYcFlwrpqEiljbglzA+1dstWSpX+qHGoZbKqzx8JgkVKo1dUhBsRNin0qIjVkee90eSNUsu+W9t2yRsZ0M9+7oynoJXe54t4Ny90S8S317vtgeK/CxWrt7ujroUWO60Zd9T2StmRmkBGmsm737iFuqIawqAgiQ8oKzD4Z19zB4QzcgoaxNmjypS+lMjjDojlojI+/MAOUdRdNjNDbJDLoU5Fvh8RNRnVFTuJiCiaX5FvLTiMbJ7/0bF0DY/orFkrG+2DqONNUjr3xkF0/FJ8fqDyAMpoIRKeUo3RgGAJJ6PqIsfaO7uJ+troUoCANhiBReMhvT5yxofPPj+j7TDhogG4D+bxdXeM4O/8e37cHaYQnlxag6EdAf/5/aQFfWv4Z9cL/anaYyCmOAQdbXGC4DJMjI6LO+SmfhpeO+IB67E3q73rfMF3Fzkb+ysVtnWFzvB4xyEWF8nS7TkBDw2trslJwVCC25dIaA4BSwZBs31HBFzh9Nc7XI6EduvckbilKJjg3nu+rM4EeetVeoQvGywx0emqZXFAP93A+6YlAcYsHWUmR5JgKUJzWC8pGWJrh+wX1y+Cpk8F++9TKdDGIHmZhl2G0Ye02S2kNCCSseMyTjqEdsa5h0Rnwd7BfTn65Vkw8EfBAa3AHCj81K0bsz0XBvLTMWae38DZMXeMpzAPbPFqs+Hj+cDv+cvz4igXsEVY3XOvCqDe7aFzlkcRvPSufDS2lQcqg9asBTEPrLnzgiBSKezo0qalWJfBddmmQOV9GUx8JEh1nS6HfMuGhMoJPqz0ZvSfnxJAb24LWbIhBC85/sJqYQX0FCUplQGVwLYrlkdsVsHAJyVmsqZq6Dv5RFpVWgPnjIfctlmL4GDpAmPPfREEERoaNvi1YGHytvYeWwyoK2NjtEoMSWp7Xr00kYDhM+8dwpMS0Nv1zIInkYB84jBD54UENIIm77+2kcLcPZyIsU8KlgYXatutpMAueBwwiZVCz5zdCWNDKVwR1l/wwEvBraqd5egkhfRte/XDtaSQcoz2xdADCXwVryibHZaAJO8nu4IcCehzvs1b05dAIZmF1XsihlGma5+OrRgOGdLt5reL4ZxMf0HaJYLXiU425p4iiH07eTI7pAYcm59K3oVWw+RSdlDEUBWsB/qn+YxUwnxG3lVXcQVYhJvvLJkQgo5e7/R+MyEoUh80OjbygVOPWb68WQ4LVA9CgUU5rA7fj1wzKINfcBTDfPPS/70lwGq7sdqwXgx+th0CzHgR/CLWUainFMDYGPQruVx4ShtcP5J2BeQURbnX1TwQhClfHMvNBa+E7uKZqq+BYczvUwnKgerDDrOsrmwIaNNiFkdmgljD5Z0mLh16s+ttk3PSQGNa3tDJSYV6xyvNHm0psNKuNhI9dxHm3iSFfXk7GfYutn6v/XMiKKjv1SmZ5yEGu72RuRYL0t9dtvSwWcDq1JvK5TDgHdE1+Mu/ouEfciu90zQK+u+W4DlOZ2BKdY3aSDwDGY8Sn2pMngLEPnl91fkELIUcxfHmT0BhMy9vPYYGKss3ly3rfKBe96uEfVspcFdGIxT1u8OP7ZkHoM0F3F/IS5pY9rBoYB4nyySC0l3DJEBOBHbfb9O7D5pBX0rd+UWhAZjcSU9zHlaDmOaGIhJTFVhrUQQzNS3EPHde4v+rFurp/J5lof0xkmIPqdHjDNGjFdtTu3mHUM+FzcthfgRkVKY1ib+LR+/jabypZUs08SOT2h9IRPb8PUmi1aPot11G2oUPiGjjE6PihVtE5LvT+bGWhx0i3XDrD3lth6pXRTeMf3BGcwNZnowqJ/TDRU5atI8z0lVEWSWwXZHX9J1WRYMr6s57zd1SREZ9qsIDgVgSupmY+sG0gozivGaiX5Io6Fbw6T/brSiouSaKwzzthxhsPwsVojd6OdwfZpTmh7ae0mSeMf3vg+fvhZ3hVLT1+k2nGStfZGE59MUTDB2hx1/bfyDT0NvjzGvlg/7oX5ev5eI=AQAAAACAAABABgAAMwYAAA==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AQAAAACAAABABgAAFQAAAA==eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAABABgAAFQAAAA==eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAADAEgAA0gMAAA==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AQAAAACAAABABgAAXwEAAA==eJwtxVFEHAAAANBKkpzkJEmSJMlJkiRJkiRJkiQnSXKSJEmSJEmSJEmSZGYmmUmSJEmSJEkyMzOTzCRJkmT20Xs/LybqXazjHO8EB5zoJAed7BSnOs3pznCms5ztHOc6zyHnu8CFLnKxS1zqMpe7wpWucrVrXOs617vBjW5ys1vc6rDb3O4Od7rLEXe7x73uc78HPOghD3vEox7zuCc86SlPe8aznvO8F7zoJS97xate8wd/9Cd/9ro3/MVfvektb3vHu97zvg986CMf+8SnPvO5L3zpK1/7m7/7h3/6l3/7xrf+47++870f/OgnP/vFr37zP0dFvxfjWMc53gkOONFJDjrZKU51mtOd4UxnOds5znWeQ853gQtd5GKXuNRlLneFK13late41nWud4Mb3eRmt7jVYbe53R3udJcj7naPe93nfg940EMe9ohHPeZxT3jSU572jGc95/9sSVRSAQAAAACAAADIAAAADAAAAA==eJxjZh4eAADsVAJZ
37
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38
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_AQAAAACAAABwLwAAnwcAAA==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AQAAAACAAABwLwAA0QEAAA==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eJzt1k0rAwAAxvHUMGZmxomDw9LchaYxpB28Hb0kMlZrJbF5mzGr0awxbDUJpSwTNlGUpEwj5eBkzfKyD4ASRy/zJZ7Tc/p9g39/x2c8ajMK1A4K0aNMabKLUynI9eni8Ow2RRm4aiifq0mjIM1lu1WtcYpyxnJ31D6cTkG6w1+KTomQglwVFmx07VCU/ma1rKcug4IMeXWO3keK8vTB+a0bzaQgI0UHQ3qpiIL0LUqSa0hRbt6XvlfUZ1GQe4UdfZXPFOWJ1hpTjYspyIvAVvIMsynI27eby9p9ijL6n3GNhIJMmPOCmgRFOfKyJvWrcijI7pXGfJeTokxOYct8lKI0PA06F+RSCnLAJoi4BylKk9z3u3hOUZqvS5TLolwK0mo4M3naKEq7uCXk9VOU/ZGfw4kPitKoX3q1VMsoyDGRXDHloigng8daa4yi/AOXsFq+AQAAAACAAABwLwAA8CgAAA==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AQAAAACAAABwLwAAvyEAAA==eJxNWmVAVNsWVuwubLGxA7v97O7uxO5usbsbC7HFaytit0ycM6dnBrvFbkUw3tqbfe88flyUO8x49l7rq7U6rk07MF19HUlzKbvCQ3T8WpEuVYOTOvpXG9lzQ4yOnfUb/k2e04Djd8bGc+sa2J3udc8XEw2kK1pi9opzBk6Pu9ljZloTq1J+zNGsnYk8i1YvKbnWRJWSKe730U1c6H93t5TSQpaOhZf2aWIhY9tjGwYtsTC5YvUWfXZYePn0TrsKLgt6riN7ItK4Mf1h3J1KLd2IqjXibO+hbryum+RQ6+1ubHhQ7fJ3yY1+z9XCd3+6UW7C+TLFqnpw/tLeCj2aeiCvS1LlzEgPsjzbtSA00oOV2xfWeffRgzbb731o5+9FqHdmr7ylvBi9KO/Hn/29mPA17lLrEC++N27Q07XPi4p2W3ev4UXGzJL29IcXRS5nO9UnfQzYU/3KFYP55VvtT9skBmkea7ezjIjBAeeAAV/GxaDMrNh58ZtiMPnR9iz7LsVgWr2YDaUvxqBg0XRbrh6JEecUg1X1Lh7tezwGfebMmvjaoUGNGksv0dFRnH+xhyMnDJyuI6s/bt87o+PAqfXX2n/WMfza8svzKhtIXqj71eSjDbQfsXXK9t0Goopsz3Ex1kCzewNfNcxponKWqrUvdTDRbNSTZ7MXm2i1tOj03LdMFBv7ZvTO1ybGpu48/Hs9Cw+6X3jXYIKFLqWzzT4UZsF2JnzA9isWNlysGT3nrQV62AmerG6wp3A2dqN75R070q9yY9BY9go3LrGXfXMjYVON3jmyeXCtS5ociyt5cPemnSrEg2yZSmwbv9CDI6O/bf962YPhi68UG2F6kHXX/k1HvnlQ7mWHXp2/ezDPEfcjd04v0tHTZ2zhxeGedYpfGuPFiHkHE5Ls9YrP8+J9jwZ1Y2O8mLQ+V/IuGWMwpH/bWr+qxOBdMHtBDJoPdZ7z7xqDW+NbHi5E92HE2B+VmBaDMxUfb46n7wXrfxoo9dbQOLjbrbyhGtJ3v/+6xisN8e/eXK1RRMeuTgkTaw/WUd+claTDNh1+82pM//VAR3h4yLzl2Q1kGLmx37jqBsbn+H76Rl8D9fY+vJxxu4FjMze9vHbfwLW/XU4OLGKi2rjxVxq2N7GpZ48MS2eYSHK70tDYMBPtfySlKzGxJ+nFFFn9LWy5v37xwh4W6M2rbFlkoXVF9s4WWqR68zffCwsFytV4vyGjGyvi2kjTK7hx7vqFXjenuFFnW+eww0fcoMv5XF9xo0OZs6fzZPWAl0MRD14nZxXgwami9VqX7enBW3q6FjM8uOnyr3nshEf0mQfslGe+8yDp4nb7BmfyYm1UtL64nBdnOj1YNbaHF9NqXR92bbkXCxskz9dgI/XLsCpF35/wokRzT6vLdA87069a1/WlF6OoWq9njUGh58WtugEx2FuVHUAMsv7oFq+m0GDs9Z84o7mG9peqHO88T0Oe5fupojVcc4Q3jvyi4VBYteyHgnS4ru+cHDdCR7cnSQd1PKqjzeZbN188pbrPVvxHLX8DcSNONqnTyID98IT0tj4GSgX883fCFgODd1X8M+u2gRveBmvmZzWRY3jrL6s6mrjFynCuiSmZa3WMvWjibXwKgiATHU+l6jG3kIVmj6f7H21qocqH6o2bjreQL7KsY+QaCxeKZ0p3Zr+F+LT6isaGhSn8QtygS3pcZADhT0LAMr9ZbsQ+uBEYvcONrYFJhw+PccO4Fo/FhEf3dpy5W66yB7WStl6Qoa0HfrwRPQgKnnT45V4PSnwu+mqr3YOKBWdcSnjqw6cUV6emzPCb+iJfartfMS8al1pRNnkNr+hnL7oW+9UB1Bdlp2pd1wz2Yv2hee2b7/CCwOl5owte9Duel55ARUKsuVH5rAIrMucflY/Od2+betn607nfr/+2VbiGjBzgNPF5msBDHcNu7371NlhHh23Vzz0M13GuY81uf1/qmFuIdaSByW3z09Eaop8M9OVAbSDF8huhfWUDSwb2vtckmYmcF2NLN6tk4lvmle8LTjZFP5l4wMrdMLHj/OfuO1NZcLrjC4eXtdAz0p0zzSgLdwquX7F9IdU9f4GF7QdqPhscZeGffD2Caz309UNgEdb5buy9zi7cDVufD3+mHnOL/nIj+Zo7hEBuNKuUo/WQ4h5cCnh8+hHhkTZtZe/d0z2wXg4v/X2zB/uLl/k056QHhzemuWIqHuSukW7GncceXG//+XW+ZF4c9falR/biQ96+MwY392Lmu1C6aS+m3F34ouZKL3q9mNi91UgVjS+kLYlDKvIMO3Qx4LEKhi5N/6jIRCy5triGNZce/P7UR0OuWSnoiDUkPoaGgM6tM08qoGNJE1ahOk77NexylnB/RvOBp1dF6OjM2vCjLvDNwI91t4cGdDbAH2u+AfqQfo+Id39WeHE08JmBbvlcv4ZnNFGPN4yJO3ln9q/Y2USqvltaZV9h4sv64WGrok0MbJxhf/84U/z7CHfCv+S50MhCXO6cGRcEWzgwLbpkzXUWbnwr0Wv1dQuV55ytN++JhQHZxwTn/0k8ffvrgsD8bsRva7dkTkM3qvGDpPPO2/SfWwfceH6qdqb3Ljf+NMuSu8snN0Kypc0yNrUH+Su1y/23rgcJ0xjTeUCXQAjoQeHf3yc92u4RuODBWuvIzvUPPGjECdoj+s8L9q9Lmk3Fo7tfh6CDCmfm6PNRK1X4mebJM5dVsOqp807Fk2P2PN8ya7h+nxGchjmlY05kWaKhTOnWLeqf1bD617WrEz5oaBcxq2b+SjryncgR5tdPh6ri2q1lOvLnnTu19xX6OamDBXT+egBDTsL/PPHFo7oZ4LQxy8CwDmlJchjgcO00kJ7U0pw05n88wNh1RxMTGqmU2cNNnCrZderm5SbmrSnTz++siV9jAmtV9bOwmFClRVELSz/c/CdnQwvfzt1Z9nuQhdPd2Z8s9OvOPsnCvvnfQjJ+sXD3ykl9r78bjv29Hvcu5war4pJd3XCNTVYXK9xoNGzMx4V2N3ZwWHHjzmN2IG4wVJxY1ANv8MrpS5r4cImX2W4Pqh6u27Un8UNBfUzfVMQPIXuXpD88VUEsa5f7Cni511VRftH43b0Xqpg+dop79AUVav/LF5MkqGhIT9ujlAYCI2oIwncmVwZquBzzgipGw9hQY1CFExqS1yjRf/87DdTcScOo/oewb0189U+H8/7FIR2vCzHE0kFk8LEc6c76W08MrVnLwJXS8/4eCTaE3jIwjgssA4GM7t4YaHXjY5YKgSbmL/qTplwXExEMJufQvaxhhWUiruPTfdtumuJcTJB4G3UwF533ZNbYFkrGfqdOs9BxU6FVk8ZZePgoHUGthTacgC3U3jXSkf2BhXqLf372+z+ddHEiEyZuHGflt5J0U2DE2ZSRbvSa8qXT4ntu+KuNvB+/ukV9erBJ+Vw7qpZH6Amqf17gCt4zOdJCAVMxq/cpqGMVqnYjA9V72SOLbtZR/8Odm1MGuJeHq+L9fXW/fkzkuQp1NLzNavVM1lPD1jeV9Q7TNHzNvjf38v0aGl0t1OlQjIbfYTdmTktKun7LtwEliutCt+jgsnq2juN/FLpZHZyOqQ8Yy2cqYQjda4Cpv/erDTRaPvJlwiED80eXH7bCbYC3QzoTbtbG1UyUzrXRTDPUxLudtcuYW01sydmPIN7EEmKDi09NvGpW7m+h36Z4fwt0GS/HNLCQ5+CKkDA6/3XTnmVKSXywaWOxfbvuEi8s65SrZ2o3FiVjQpj0aES/Th2Ku8HcRWiwG2eWrieGdqPChmzvSu11g7F4DPXD8Afjlq165saJx682nkxPuodcwpHyLjB0n7PVhcWVrmxNllyBMoKdnAJ68ecCuiLqVBX6VEWuqe/r9BqvwlHt7r0tO1XB/yoqL3TRb2qijjTw7uil4V3TZbbjyzSU5IClCX2n4diJlp3GZNDB5WhTHSm9TQ8cnalj8tLXR+Ye0cHY6Jhdh3uCnnDbo8NSttGTG+DtQ/qzKn+hgaTftUOlwwzsKLd8qRxtgJfzSwMnsyzxfKN74PDYzIRn2N59n4mPm3+tuOz5JhPLq1UkKDRRcUrZQgW+mth358DTCsksnPqw7FFIaQupOfFa2Dira/K/PS3YV60k52IhG6nOwZaFJPzLjfxc8LhRngs8t+B9NwbwC3Hj71t2AG6MHt2qbbcn8n/nXrWAZ9GycS4cC3w2f6fsQh2qjhcBCrhdGa8IXaTg+qIDXR0VVaxmH99XRc2UwcemhKgI4kJNRSkGq3Eqyr4dRg5DEzypgX5IwllDm3R9qPTpXhgt3dHQalUtglLSo/OH5apbmPQ+swUtdZDoIoek41BQZOZnu3QUYbBN9Z9Ypzp2DO1KEtcAp4d+Boaz41xgYG1xJogN8Gt4biA+qmqnFV8MFMl+O8e8fD492mhR54trp5nYO7ZOWs8eU9wr6aWzWpIHxAMXMjHmtlCq5jpnSDML8+8fH9V+sAWmftqutHDkKgMwwqlVEcWWEB9w2fHdQspvZckBu8FpvoUbS77e9cydQPXPHmOBjPEHJlIryyBRS8zuAlOPZajet1fafbpanAsPDnchZalg6rklxEAK0s75lD5PvIIqA7WJk+nct1Ru8ubgcBV1iU2CiW9Tb2hNSEg/Zx/3WhV+TBM8qYHT5lANU7nhJdy5kZoQQ0OXjGVP7iDe9csY3kLOr4PL7ea6qEsdUxmcbddx68/JGZ+P6+jd7mHFA04dPQOZstERxGx3oIE+Q48azVoaQkcY4PC5nu4jpkffoqcNoW8N0GETcJhY/ZAJBhP7t90seHy8iZgpjT9e2WjiyiDmMMinvfWmvvnGV/8rwrfTTVtCv1t4XK9ZjqC55MuKas4SmyxxThZCGWzeoT4pyBDHErpbEnpPRqWbJ8qN3iODTOR+JMjgv97TBX9CpV97XRjJAdpX752SrBiiqorwMSqycIGgwv2kI/s/KLZSqxmxVQVj907XVGz7p30mLVZF17flqRM0weu+80/EZ03UC90Dizm+a8jAbFsuHdmf/mpdopGOlaeZ4dMxLm+GR2XX6Jj2qliF1P/o4HL6mY6nS87E+Scx8GrW0xFKGQPb6qhp03c38Ppla7IohPtXmZEzhL83ULNeUNPVD6kfSK08T0E+gJVnMRP3Z0Q9i6I+qM0Nmyn0oglZYl8+Pt7WgxkC8l3h59oUKevTpf/mFNSM/gF2C5M7VSFrIWHt7ISaY10SUhlBMxu1koXekDG7SqrUL2JlwZsu3CXX+3CBC5/Oz7422utCCP03soSCi9MiGo5epKAyN17Eoylnzs5VSBV1o4q6oXPueeLKW8L7s41DM1S0Ex+w9nulIqLZwhMLC2roywWKJvqW8D105il5pYY3+ZKd9FzQQKIw87E3dA/7CxMy+Pj28/F2ZN11FGySenXVVTqGciGqY/OEkkdLJej43ptVgoHepPaekP75Z/ndoUnG+Pg3MU8i/V/jtG0y4VAYo9kXxBPMZvw10DQZ60RT4LMp8i5T1JOJlDyYM5GmXUeyZCbKDMr9pFtO0js8gCP9PzQ27NEAC007Z2t0P5WE9Cz26y6BpWVREZLwETIOJ+dGEP0fnfsx1i4jxej7cscAF54116usH+NCcQ7kLoyOP1WgZGEFFqOloYqoGwV9Bm4++CCPKvyLijYh34s0DlaRvgBLDFXMTXPv/LYDKgb/eNY/3K2CVU+SXBqanx/8Wa6qoW5szD/xxLcsvZy3XENCr1EEJZrwExq4zf+pYX9UxNsLhPs9vEbGkNY6/HhB6Lh0iF0k9YF9HCGmjuRPJv2ed5/4eCT7k46mPUqNaVrdgMpkG+mfar9jVvuvpXsoxw6WzrlgH095wp2Aglv2RH8gv5aSIbKJpVuyEuX6fECiPqHzHlVj85MIE9dbMUVPvMzKiHxxilurK0wp+6/vdWJRdfetUZWpvk9UIoUh4YfEAk4JSYNYIisJnS1jxq7suU6el8Hl6GcZqVgZ13ZhwYVTpEhc4Md+g+p/BxN8iuAVBRymkqog806FomI4seL+RiqOXmCN4at7piYm31AxYeEUQkAVTJXNINxJ1AsaJn54vO5pGw15y98vmnKuJnIUDTXOPQwvoWpgqe7u9xpmcoIhfc/KqBXxbNzDFpNHku8axZyYjm6cnnQwlH/+jl6nzCYnYqArD5gM2PTF5Q5S/ftvmlovZoOButO6Hawikw/ozJCd9E8BZmBM/CZ0u1rIRK/qmdelaGWibcqm9sMTTPwZxArIxM87lVqSd8S6U8cPBPwxMYMbcScOn2QP5ASPn/0kcLrrJSH0Y8vfFw9JONIqbt/sB/S9fNY748vJ+Pro/T/3J8siP5WxW2NE6AK3t3TuGwexZITuYe7LBzcCFRy5P5mQjXA/FXtn8lfUXY1J30/I8nBp9/IqftTyTxFP55+Yg6rAxPqznNtVce8qyq3ZFVfhhSpyRA2HFavL2/IaluwoObHPQF/9d+WAoyEdF8CES3ueWTVS6jiAhLWFK+pw3s1C0kgXekqHtJkJcx13qItGEf4k+hUdeXf2IelKuL96RMNbVP8sdfgx1sA5FhceNMDp7A71w6puy9smNUWeasK18lWalrWJX5lsb2lijf/a/tnHUD/MYM7NRC7eAA6RazuFr3Niv7UmKlp3olbE1oKv60oib5EQSWjhPCfh629z6qtiMn7uGnLq9QQZPBaIkkXfyeDxcmMX5ldmAsYlPofwP8egqraipG/4oEBB/p/z6UZ8fJuYg6nwXmCSSAWXiaQzE/UrfS/EggpV6GVfvlbg/K7Lg6juD3ZgwaKGyCGbkh88pKFld9a5GlKFBj8r81YDiaXklbPoSF/7R/5yNXTsY7HoQF/elpjn+vh28J0/GzcWMxBThxW4AR5XtDPAH3eSgYYslt1qoBcPtg2R2xMfFGGKwcTjEBZ8mIL//sUbB1hqkvKjA+04gDhx7E3Ot4tGObH9p5Wv4BYnsid5mrvyVye4rG4jCR0vITsXxhLWxQ7yd5aVRZ4r48ckNvCQcbPv+iqvC7mE/nQhdOfxm8kI73e1ZQygIJjFg1MVPGFxh0b1z2wOnfu/OjPuejA5ORXxagqSDCput2tz+vAaFW8mnMme4CQ+3peJJKGKd3O79LO99tV/Yn6lIT0PAjUcbcqCXU3UkSaex4c7HM5q64JfdHzyMOGkQ2Uwc1hHXSZvCPebBE7y25raELkG6UpSM96m5LtsRYsM6W9gayj7MsCP4ZaBXcxOfzdAJnHLsAQDicbAgR48CHJglnqq+7dzDqG7HXBUZMjrBL+Wk07wGD2TJHBRwsFDg0bMWisJnS2BTPXx1W1kfCqXkyDcV/dMFU/yc+E9i5t6uLDNzoypC965E5ps+O4S+buCmVxo+HzVeG5wVbDq2FRXxaWEp5eGD1LRxeyXZ9FqVegQVeRg5HsZLZC/fdNFaf4hrybwmPxUW5bYayjKhaqGEf2YEtAwmAf4Gjis+/lyhkOt2SBOB5fzk3RcDgotlWujDh5zXdKRgQME4RIHJAMr3O2t5O0NENje6jzIwNPoLRc2rfHpzn/nXyx9Pf3ILnSzA5/7sKTaIXJUByoE8sr9D2eeExoGH3OK3FpCmBxBSCohnlzfxPUSSGxVeHNLEnmBjEl8UCmjNw9eZHSlKuxCvuoIk+EZXeK+XRh0vfy3L/tdiL3GAkiXwE1F6DUf30Y3YYKB6nwUS1hVMY8kXv1RlZSFipY82FTFeaiIZPSSRgMfdxbQQGBLDaxhw94RxR6O1IQ/1HCTlaGm4R6Dd6r78DgWEOuiv3RYaYYWHjlVxyoGz+RzJ/GgRwebsh41dDAXfoDOv/QDW+3PqQzMaXZlVgDhfq/V17+V6GUgJxuDTjBELmYX8z07+PgyI51zXzbZdGB0TpY8OcDdWEbnf3gj1Rv0K2GFE/1X5b9y9pUTE187hkzLL4lcRRK5hITC1W5kiPtFepMPOmQx15XBaZ54NuRiV6JiGbka1tCONnAJ/qLz39e8ZCzV/V5Gd8HEr4uzXN9DOudiL3ZxCvD0+tw1ZVSRu6goEdWt/fxhKpb5zSrcdh3hELF7p70qvhKqfCOdmch/xK9DJ5IE00QfaljM2maihl7j75UM+EcTOlYTz6XhHbOV8Rq4/KG6T6wPHZVZzDRBh/KDBZE6xrdjClAXvK4LfNNxJg+boOlI+sAvzTLqg8S5HtU3GwdtsoOl/ZklO/h4LIUDjYmtW3R34DKzn2ccWBiYv13V5w748QDVKeY2TqTd4fEGRhC+82DHKeYbEmpxIyiJObGEOv2ZQpGFz5PBr+ce6RzWfplcYOpx82gXWsxgE3GXyMFciN6hX4uHgt+LGREoYu6tiDmjilmo0ud8c1X4flXgo4q3rRiQqziVfhxZHNL/fACmCd2kgduM5hqKhJd92YF0fmL+Qv0wpx+duIZXn2Zs+0M82682S351NNpTiySRjlJPHw7pVV3HyKnT95VpqKP3lX7VRvbUcYWl0xN18JgkVEeOBOd7+w0dXC4+0kX92dCh/8hCtvp2kafYkTw5c1B2vMzFnL4dbbS1vf40dIhc34ERHAAcIg9xoueb5QsitzsRtio6fafbTqxmdpxwvkNU/oVv2kvowRtcgqtjwPhK9wjvy5e/WremjLPp5El5hslIP/lGZONQGSxV26/66j1nmB89qkvoNRfUTEUWNM2riHmvgpDFu+uF2RSQSCICVVBwIJugq8KHqOCxxFoVrxidH1EFX6vgdET6PnFfQ0O2MhmHzK6iYdqxHiSBCXd+MwGtoW3vn2WU+Rq4jd2lIYjJ4Vu+e+D0mVdHcS48dZGP6wjyZiAppiMJN+66yF91Mde2odZY1xL9gQ39+QKJHS14gdqxZxIz/HYxn3Pg+bvUB1KUdyCUleN0B/g49ZIDfJyQ2onaXBA7wbYSrmx1Cr3nBHOl4ytJ+B3UYOrpcRI0JjfOS+D2tqCMfnzQKYu5iyzmUDL+smlCPxfyVP7aduwJl9AHipjj+/L69ye+hqd7rYh8WsXGMLZYoCInN14q+nfqUHwX+dnZfPBN+N7p9hUlShV+UxV7J75c7WnVPFd7FtSQ7O2ejl2JbxPnExrosLx9J/v2GQq0ZEpUQ/TAlFTymjgnHWNP7E5pBOn44sfewKf7+fhxjg2L+ZjEJvJru8jX7GLPxI5wJrPP2MFSkrwf7VjYlyGCA6lfxNJNO8BlzR0HKvEvp8jlnMjd5VOTF2ud4LbUcoq5lc/HJuZYEthU6WgGGeELQiNDBslou+4oS07+w/fEe3bhfPP0fqUXu8BSwyYuF1i6uiFIEXpYwc5UU4a8i1TAumiOoiCIWLhwdhWM7aObqGDbS6Wp7hN9vorc3JCq2MXWDyJ9cxRe5r9VFGPwmVbDI/f92lYhDUxllG6mgcv5Yb58x8tscaQGpgIfS5qYD2kYyo2njrZFym48W4TqncnQtjYMZu22yIY2AzKzyAZ8TEE404sDgR3jWDw81i5yFB+vJvp5B26wNZABDpz0MKPiEDmIE4X5wdF3bhydIu9zgq/7lJZw7cnYF10nSGh5vDpJfQll67INAFnk5TL4OgjhzMKZ7EZlMb9xibm3C/XnPSHl5RJ7UL78JnF+qCBv8Lq1p44r0J8yAaMgbBxLTlWwrY09tVSM5ItNVN9xv6jzVASmnLux4XIVD54XvpztlCr2rlRxHj59z2mnpCZwURN7Pr6cYTCpZHUT6fwA+3Ps1cQcREPEJ731gMw2XDHZ4MSGDIxWhtrA1M/0fTacZmtVr204EMsGUHbB63ah6+k7u95XdvCxdHsHBvIg1QHnF2b4HWJ/wYnbP9kg3AkOyw6nmMNLeL5t1OhWbck38UKVML8VW/CREHUs2csVJWSUPzgm1KB6/3yGGUYZ0yatShrzRkbFZBs/fajkEvrEV/f/nn9tPghWxBxCQUm+aKSI/R6fvvTnRoj0pD87GFXMIVTwqiPe3a+yhQgVnIYIfxJzVHo9Ww8in2Wrn6bSqL8q5GMvklwjn3v5OwsgNNzXhze7N9DHvywlP7ZBE/sT0VAqMCSOhk1mA2mb4HkbCnc6FJOM8H0ID2ZtaJWHIbodi9iYOtgOPva4YkdRDqAOEBgeH0XnzseChDOJ+oh+vpcF9U5sZmtn25xiPu1ESS5QJVzYxhZHJOx59TZ4LJ17Mj5AkMQcWcbsMUbY72ayyO9kvJ/JBIkMTuPxMlgVHwhwQa7FmN03H5zIA0oXvrmvdkmTQ8G6TQ5CUgV9dgys9326Iu5fwcGnFegGFZF7E7+ysQDhf5YI8+3cLiqWs/HleB8ORXt2ds+6SwVj0wvUB4l5kSrydx8ePSN3dr081XlNNjnUBJ9Fi7lotKg7G/j6ST8bAjYEGd+P2UReYRO+3Y60vAHsYNtsXw7bwdR4ulQOwVMOHGvgaBsxywEu8z0OkQM7MTug+pBGw5w434YBmhNnt7cc1znGCYbyyCVBYeXXUgIfE02XsOw4M04SCLzj0+qSyPMk8Bi/mizyEhkSqa4GR2TMLD74Ui6HjMb8gOm8ecO7wFznpRUujGXrEp9c4OuoBRWsD2AdoICvJa5TwGOsiwoYW9an8685iW2iqP/p/YEhLEnx1f+/ufKQbXmNbJtU4T9VMY9UEfTx3owoOv9h3IBqIke0ITLOn6DcBh4nprchIx+k2MCm3IVH2sTeJuFNtUdfbqS2owdfmLDj6ktmROw494sJY7vI5R0gEjaLtXHAnJdzVophDrFX5hA5hEPofyfWMBsZ4hR5vxMMDSc9d4q9GEnUmSTmjBL4OGeXJPJlCUyFj0gj/5cjrO+gvgtcSedNpzvgnIwsnLBlpGUyJ49L5NbEt0snZ+8w2yXm9i5U5g3tEjmAIuaVCobxhSYfD/87T8nG1hACVZRtmO/Nk6oqmvMPIp3J2qUt+TAmV4b48rb2/rHZppEPS8yP7SjFAdaG8nu6jR5WxYYxpbgiF/1kA4fFTTZwGlRsQrfaUftO9QFl69qFjrYjlD3OMjvY7UYodixhtrCIA2w7rG99B/iYcbhD+AEHuE0iPc/U6KN0TvwpzRaInCjL2nSyE683niSn4sTTCBYYO0XuRvWfgSUaEi63ZgGThDTVF5SqMkMS9SWJ/SsJPxk9F5HBY7/BpC9fBpFz9unOxP1IWeQ0PjyazQ2zS8wv6e9sPG934WVNZuBcSMKDX/Jb1/LVmT1GEfMnBc8YLH1QBE6oIqdWxR6aKvhQArc9QQ6s4Os7NuHXbDA/bZnriIsGX4P9Ei18RbTIGW2C5+l++KIs/R4XJDYx57MhhDeUDaX5IqRNzDvsYl/CjiaRX36bUwmP2PjprF3sCdtFbucQPtqByZy4HOAyfLcDS/s0OXFPd4j9GafgRyf4mKiyE1eZ7JzoxLM2r/r9DnNiH1uHvOEU82inyMWJL1KyAaKEi4XZQEISe6gSMr86S4wtIT11Te+fEriMDJLB0oGrXWR0mXU0ckCIDE5PR2VU4gvhMrgNLecS/tAFlu4vGu8CY5MekS78D/ADFZs=AQAAAACAAADoSgAAcA8AAA==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AgAAAACAAADAPQAATRQAAO4JAAA=eJxd3UMQJVnbReEv7822bdu2qrur2rZt27Zt27Zt27Zt1T/48xm8Oyc7YsUar8mJPOd///v/r+l25m5nCt7rdpbw8H63s4aHt93OFh4+RLezh4cP2e0c4eFDdTtnePjQ3c4VHj5Mt3OHhw/b7Tzh4cN1O294+PDdzhcePkK384eHj9jtAuHhI3W7YHj4yN0uFB4+SrcDwsNH7Xbh8PDRul0kPHz0bhcNDx+j24Hh4WN2Oyg8fKxuFwsPH7vbxcPDx+l2ifDwcbtdMjx8vG6XCg8fv9ulw8Mn6HaZ8PAJu102PHyibpcLD5+42+XDwyfpdoXw8Em7XTE8fLJuVwoPn7zblcPDp+h2lfDwKbtdNTx8qm5XCw+futvVw8On6XaN8PBpu10zPHy6btcKD5++27XDw2fodp3w8Bm7XTc8ndbj9btdL7gebxAerscbhofr8Ubh4Xq8cXi4Hm8SHq7Hm4aH6/Fm4eF6vHl4uB5vER6ux1uGh+vxVuHherx1eLgebxMersfbhofr8Xbh4QO63T48XI93CA/X4x3Dw/V4p/BwPd45PFyPdwkP1+Ndw8P1eLfwcD3ePTxcj/cID9fjPcPD9Xiv8HA93js8XI/3CQ/X433Dw/V4v/BwPd4/PFyPDwgP1+MDw8P1+KDwcD0+ODxcjw8JD9fjQ8PD9fiw8HA9Pjw8XI+PCA/X4yPDw/X4qPBwPT46PFy3jwlPp/X4uG6PDb5Bt8eHh+vxCeHhenxieLgenxQerscnh4fr8Snh4Xp8ani4Hp8WHq7Hp4eH6/EZ4eF6fGZ4uB6fFR6ux2eHh+vxOeHhenxueLgenxcersfnh4fr8QXh4Xp8YXi4Hl8UHq7HF4eH6/El4eF6fGl4uB5fFh6ux5eHh+vxFeHhenxleLgeXxUersdXh4fr8TXh4Xp8bXi4Hl8XHn5At9eHh+vxDeHhenxjeLge3xQersc3h4fr8S3h4Xp8a3i4Ht8WHq7Ht4eH6/Ed4eF6fGd4uB7fFR6u23eHp9N6fG+39wTX4/vCw/X4/vBwPX4gPFyPHwwP1+OHwsP1+OHwcD1+JDxcjx8ND9fjx8LD9fjx8HA9fiI8XI+fDA/X46fCw/X46fBwPX4mPFyPnw0P1+PnwsMv6Pb58HA9fiE8XI9fDA/X45fCw/X45fBwPX4lPFyPXw0P1+PXwsP1+PXwcD1+Izxcj98MD9fjt8LD9fjt8HA9fic8XI/fDQ/X4/fCw/X4/fBwPf4gPFyPPwwP1+OPwsP1+OPwcD3+JDxcjz8ND9fjz8LD9fjz8HA9/iI8XI+/DA/X7a/C02k9/qbbr4Pr8bfh4Xr8XXj4A91+Hx6uxz+Eh+vxj+HhevxTeLge/xwerse/hIfr8a/h4Xr8W3i4Hv8eHq7Hf4SH6/Gf4eF6/Fd4uB7/HR6ux/+Eh+vxv+HhevxfeLgeDw4P12MHLoOD63HTVA/X415TPVyP+031cD1um+rhejxEUz1cj4dsqofr8VBN9XA9HrqpHq7HwzTVw/V42KZ6uB4P11QP1+Phm+rhejxCUz1cj0dsqod/0O1ITfVwPR65qR6ux6M01cP1eNSmergej9ZUD9fj0Zvq4Xo8RlM9XI/HbKqH6/FYTfVwPR67qR6u2+M01dNpPR6v4+M2levx+E31cD2eoKkerscTNtXD9Xiipnq4Hk/cVA/X40ma6uF6PGlTPVyPJ2uqh+vx5E31cD2eoqkersdTNtXD9Xiqpnq4Hk/dVA/X42ma6uF6PG1TPVyPp2uqh+vx9E31cD2eoakersczNtXD9Ximpnq4Hs8cHq7Hs4SH6/Gs4eF6PFt4uB7PHh6ux3OEh+vxnOHhejxXeLgezx0ersfzhIfr8bzh4Xo8X3i4Hs8fHq7HC4SH6/GC4eF6vFB4uB4PCA/X44XDw/V4kfBwPV40PFyPB4aH6/Gg8HA9Xiw8XI8XDw/X7SXC02k9XqrbJYPr8dLh4Xq8THi4Hi8bHq7Hy4WH6/Hy4eF6vEJ4uB6vGB6uxyuFh+vxyuHherxKeLgerxoerserhYfr8erh4Xq8Rni4Hq8ZHq7Ha4WH6/Ha4eF6vE54uB6vGx6ux+uFh+vx+uHherxBeLgebxgerscbhYfr8cbh4Xq8SXi4Hm8aHq7Hm4WH6/Hm4eF6vEV4uB5vGR6ux1uFh+vx1uHherxNeLgebxsersfbhYfr8fbh4Xq8Q3i4Hu8YHq7HO4WH6/HO4eF6vEt4uB7vGh6ux7uFh+v27uHptB7v2e0ewfV4r/BwPd47PFyP9wkP1+N9w8P1eL/wcD3ePzxcjw8ID9fjA8PD9fig8HA9Pjg8XI8PCQ/X40PDw/X4sPBwPT48PFyPjwgP1+Mjw8P1+KjwcD0+Ojxcj48JD9fjY8PD9fi48HA9Pj48XI9PCA/X4xPDw/X4pPBwPT45PFyPTwkP1+NTw8P1+LTwcD0+PTxcj88ID9fjM8PD9fis8HA9Pjs8XI/PCQ/X43PDw/X4vPBwPT4/PFyPLwgP1+MLw8P1+KLwcD2+ODxcjy8JD9fjS8PDdfuy8HRaj6/o9vLgenxleLgeXxUersdXh4fr8TXh4Xp8bXi4Hl8XHq7H14eH6/EN4eF6fGN4uB7fFB6uxzeHh+vxLeHhenxreLge3xYerse3h4fr8R3h4Xp8Z3i4Ht8VHq7Hd4eH6/E94eF6fG94uB7fFx6ux/eHh+vxA+HhevxgeLgePxQerscPh4fr8SPh4Xr8aHi4Hj8WHq7Hj4eH6/ET4eF6/GR4uB4/FR6ux0+Hh+vxM+HhevxseLgePxcersfPh4fr8Qvh4Xr8Yni4Hr8UHq7HL4eH6/Er4eG6/Wp4Oq3Hr3f7WnA9fiM8XI/fDA/X47fCw/X47fBwPX4nPFyP3w0P1+P3wsP1+P3wcD3+IDxcjz8MD9fjj8LD9fjj8HA9/iQ8XI8/DQ/X48/Cw/X48/BwPf4iPFyPvwwP1+OvwsP1+OvwcD3+Jjxcj78ND9fj78LD9fj78HA9/iE8XI9/DA/X45/Cw/X45/BwPf4lPFyPfw0P1+PfwsP1+PfwcD3+Izxcj/8MD9fjv8LD9fjv8HA9/ic8XI//DQ/X4//Cw/V4cHi4HvthcXBwPW561cP1uNerHq7H/V71cN1ue9XTaT0esuND9CrX46F61cP1eOhe9XA9HqZXPVyPh+1VD9fj4XrVw/V4+F71cD0eoVc9XI9H7FUP1+ORetXD9XjkXvVwPR6lVz1cj0ftVQ/X49F61cP1ePRe9XA9HqNXPVyPx+xVD9fjsXrVw/V47F71cD0ep1c9XI/H7VUP1+PxetXD9Xj8XvVwPZ6gVz1cjyfsVQ/X44l61cP1eOJe9XA9nqRXPVyPJ+1VD9fjyXrVw/V48l71cD2eolc9XI+n7FUP1+OpetXD9XjqXvVwPZ6mVz1cj6ftVQ/X4+l61cP1ePpe9XA9nqFXPVyPZ+xVD9fjmXrVw/V45vBwPZ4lPFyPZw0P1+3ZwtNpPZ6j29mD6/Gc4eF6PFd4uB7PHR6ux/OEh+vxvOHhejxfeLgezx8erscLhIfr8YLh4Xq8UHi4Hg8ID9fjhcPD9XiR8HA9XjQ8XI8Hhofr8aDwcD1eLDxcjxcPD9fjJcLD9XjJ8HA9Xio8XI+XDg/X42XCw/V42fBwPV4uPFyPlw8P1+MVwsP1eMXwcD1eKTxcj1cOD9fjVcLD9XjV8HA9Xi08XI9XDw/X4zXCw/V4zfBwPV4rPFyP1w4P1+N1wsP1eN3wcD1eLzxcj9cPD9fjDcLD9XjD8HDd3ig8ndbjTbrdOLgebxoersebhYfr8ebh4Xq8RXi4Hm8ZHq7HW4WH6/HW4eF6vE14uB5vGx6ux9uFh+vx9uHherxDeLge7xgersc7hYfr8c7h4Xq8S3i4Hu8aHq7Hu4WH6/Hu4eF6vEd4uB7vGR6ux3uFh+vx3uHherxPeLge7xsersf7hYfr8f7h4Xp8QHi4Hh8YHq7HB4WH6/HB4eF6fEh4uB4fGh6ux4eFh+vx4eHhenxEeLgeHxkersdHhYfr8dHh4Xp8THi4Hh8bHq7Hx4WH6/Hx4eF6fEJ4uG6fGJ5O6/HJ3Z4UXI9PCQ/X41PDw/X4tPBwPT49PFyPzwgP1+Mzw8P1+KzwcD0+Ozxcj88JD9fjc8PD9fi88HA9Pj88XI8vCA/X4wvDw/X4ovBwPb44PFyPLwkP1+NLw8P1+LLwcD2+PDxcj68ID9fjK8PD9fiq8HA9vjo8XI+vCQ/X42vDw/X4uvBwPb4+PFyPbwgP1+Mbw8P1+KbwcD2+OTxcj28JD9fjW8PD9fi28HA9vj08XI/vCA/X4zvDw/X4rvBwPb47PFyP7wkP1+N7w8P1+L7wcD2+Pzxctx8IT6f1+KFuHwyuxw+Hh+vxI+HhevxoeLgePxYersePh4fr8RPh4Xr8ZHi4Hj8VHq7HT4eH6/Ez4eF6/Gx4uB4/Fx6ux8+Hh+vxC+HhevxieLgevxQerscvh4fr8Svh4Xr8ani4Hr8WHq7Hr4eH6/Eb4eF6/GZ4uB6/FR6ux2+Hh+vxO+HhevxueLgevxcersfvh4fr8Qfh4Xr8YXi4Hn8UHq7HH4eH6/En4eF6/Gl4uB5/Fh6ux5+Hh+vxF+HhevxleLgefxUersdfh4fr8Tfh4Xr8bXi4Hn8XHq7b34en03r8Y7c/BNfjn8LD9fjn8HA9/iU8XI9/DQ/X49/Cw/X49/BwPf4jPFyP/wwP1+O/wsP1+O/wcD3+Jzxcj/8ND9fj/8LD9XhweLgeu9B3cHA9bvrVw/W4168ersf9fvVwPW771cP1eIh+9XA9HrJfPVyPh+pXD9fjofvVw/V4mH71cD0etl89XI+H61cP1+Ph+9XD9XiEfvVwPR6xXz1cj0fqVw/X45H71cP1eJR+9XA9HrVfPVyPR+tXD9fj0fvVw/V4jH71cD0es189XI/H6lcP1+Ox+9XD9XicfvVwPR63Xz1cj8frVw/X4/H71cP1eIJ+9XDdnrBfPZ3W44k7PlG/cj2epF89XI8n7VcP1+PJ+tXD9XjyfvVwPZ6iXz1cj6fsVw/X46n61cP1eOp+9XA9nqZfPVyPp+1XD9fj6frVw/V4+n71cD2eoV89XI9n7FcP1+OZ+tXD9Xjm8HA9niU8XI9nDQ/X49nCw/V49vBwPZ4jPFyP5wwP1+O5wsP1eO7wcD2eJzxcj+cND9fj+cLD9Xj+8HA9XiA8XI8XDA/X44XCw/V4QHi4Hi8cHq7Hi4SH6/Gi4eF6PDA8XI8HhYfr8WLh4Xq8eHi4Hi8RHq7HS4aH6/FS4eF6vHR4uB4vEx6u28uGp9N6vHy3ywXX4xXCw/V4xfBwPV4pPFyPVw4P1+NVwsP1eNXwcD1eLTxcj1cPD9fjNcLD9XjN8HA9Xis8XI/XDg/X43XCw/V43fBwPV4vPFyP1w8P1+MNwsP1eMPwcD3eKDxcjzcOD9fjTcLD9XjT8HA93iw8XI83Dw/X4y3Cw/V4y/BwPd4qPFyPtw4P1+NtwsP1eNvwcD3eLjxcj7cPD9fjHcLD9XjH8HA93ik8XI93Dg/X413Cw/V41/BwPd4tPFyPdw8P1+M9wsP1eM/wcD3eKzxcj/cOD9ftfcLTaT3er9t9g+vx/uHhenxAeLgeHxgerscHhYfr8cHh4Xp8SHi4Hh8aHq7Hh4WH6/Hh4eF6fER4uB4fGR6ux0eFh+vx0eHhenxMeLgeHxsersfHhYfr8fHh4Xp8Qni4Hp8YHq7HJ4WH6/HJ4eF6fEp4uB6fGh6ux6eFh+vx6eHhenxGeLgenxkersdnhYfr8dnh4Xp8Tni4Hp8bHq7H54WH6/H54eF6fEF4uB5fGB6uxxeFh+vxxeHhenxJeLgeXxoerseXhYfr8eXh4Xp8RXi4Hl8ZHq7HV4WH6/bV4em0Hl/b7TXB9fi68HA9vj48XI9vCA/X4xvDw/X4pvBwPb45PFyPbwkP1+Nbw8P1+LbwcD2+PTxcj+8ID9fjO8PD9fiu8HA9vjs8XI/vCQ/X43vDw/X4vvBwPb4/PFyPHwgP1+MHw8P1+KHwcD1+ODxcjx8JD9fjR8PD9fix8HA9fjw8XI+fCA/X4yfDw/X4qfBwPX46PFyPnwkP1+Nnw8P1+LnwcD1+Pjxcj18ID9fjF8PD9fil8HA9fjk8XI9fCQ/X41fDw/X4tfBwPX49PFyP3wgP1+M3w8N1+63wdFqP3+n27eB6/G54uB6/Fx6ux++Hh+vxB+HhevxheLgefxQerscfh4fr8Sfh4Xr8aXi4Hn8WHq7Hn4eH6/EX4eF6/GV4uB5/FR6ux1+Hh+vxN+HhevxteLgefxcersffh4fr8Q/h4Xr8Y3i4Hv8UHq7HP4eH6/Ev4eF6/Gt4uB7/Fh6ux7+Hh+vxH+HhevxneLge/xUersd/h4fr8T/h4Xr8b3i4Hv8XHq7Hg8PD9diDuIOD63HTVg/X415bPVyP+231cD1u2+rhejxEWz1cj4dsq4fr8VBt9XA9HrqtHq7bw7TV02k9Hq7jw7aV6/HwbfVwPR6hrR6uxyO21cP1eKS2ergej9xWD9fjUdrq4Xo8als9XI9Ha6uH6/HobfVwPR6jrR6ux2O21cP1eKy2ergej91WD9fjcdrq4Xo8bls9XI/Ha6uH6/H4bfVwPZ6grR6uxxO21cP1eKK2ergeT9xWD9fjSdrq4Xo8aVs9XI8na6uH6/HkbfVwPZ6irR6ux1O21cP1eKq2ergeT91WD9fjadrq4Xo8bVs9XI+na6uH6/H0bfVwPZ6hrR6uxzO21cP1eKa2ergezxwersezhIfr8azh4Xo8W3i4Hs8eHq7Hc4SH6/Gc4eF6PFd4uG7PHZ5O6/G83c4TXI/nCw/X4/nDw/V4gfBwPV4wPFyPFwoP1+MB4eF6vHB4uB4vEh6ux4uGh+vxwPBwPR4U3v8BqYP02nicXdRDDDDIAgTh1cza9r+2bdu2bdu2bdu2bdu27Ze8zHeY7ksnlTrXaIMN9P+N3n7R9osEH6P9YuHhY7ZfPDx8rPZLhIeP3X7J8PBx2i8VHj5u+6XDw8drv0x4+Pjtlw0PH9B+ufDwCdovHx4+YfsVwsMnar9iePjE7VcKD5+k/crh4ZO2XyU8fLL2q4aHT95+tfDwKdqvHh4+Zfs1wsOnar9mePjU7dcKD5+m/drh4dO2Xyc8fLr264aHT99+vfDwGdqvHx4+Y/sNwsNnar9hePjM7TcKD5+l/cbh4bO23yQ8fLb2m4aHz95+s/DmaD9n+y3abx58rvZbhofP3X6r8PB52m8dHj5v+23Cw+drv214+PzttwsPX6D99uHhC7bfITx8ofY7hocv3H6n8HA93jk8XI93CQ/X413Dw/V4t/BwPd49PFyP9wgP1+M9w8P1eK/wcD3eOzxcj/cJD9fjfcPD9Xi/8HA93j88XI8PCA/X4wPDw/X4oPBwPT44PFyPDwkP1+NDw8P1+LDwcD0+PDxcj48ID9fjI8PD9fio8HA9Pjo8XI+PCQ/X42PDw/X4uPBwPT4+PFyPTwgP1+MTw8P1+KTwcD0+OTxcj08JD9ftU8PTaT0+vf1pwfX4jPBwPT4zPFyPzwoP1+Ozw8P1+JzwcD0+Nzxcj88LD9fj88PD9fiC8HA9vjA8XI8vCg/X44vDw/X4kvBwPb40PFyPLwsP1+PLw8P1+IrwcD2+Mjxcj68KD9fjq8PD9fia8HA9vjY8XI+vCw/X4+vDw/X4hvBwPb4xPFyPbwoP1+Obw8P1+JbwcD2+NTxcj28LD9fj28PD9fiO8HA9vjM8XI/vCg/X47vDw/X4nvBwPb43PFyP7wsP1+P7w8P1+IHwcD1+MDxcjx8KD9fjh8PDdfuR8HRajx9r/2hwPX48PFyPnwgP1+Mnw8P1+KnwcD1+Ojxcj58JD9fjZ8PD9fi58HA9fj48XI9fCA/X4xfDw/X4pfBwPX45PFyPXwkP1+NXw8P1+LXwcD1+PTxcj98ID9fjN8PD9fit8HA9fjs8XI/fCQ/X43fDw/X4vfBwPX4/PFyPPwgP1+MPw8P1+KPwcD3+ODxcjz8JD9fjT8PD9fiz8HA9/jw8XI+/CA/X4y/Dw/X4q/BwPf46PFyPvwkP1+Nvw8P1+LvwcD3+Pjxcj38ID9fjH8PD9fin8HDd/jk8ndbjX9v/ElyPfwsP1+Pfw8P1+I/wcD3+Mzxcj/8KD9fjv8PD9fif8HA9/jc8XI//Cw/X44FK7+F6PHDpPVyPBym9h+vxoKX3cD0erPQersel9B6ux7X0Hq7Hg5few/V4iNJ7uB4PWXoP1+OhSu/hejx06T1cj4cpvYfr8bCl93A9Hq70Hq7Hw5few/V4hNJ7uB6PWHoP1+ORSu/hejxy6T1cj0cpvYfr8ail93A9Hq30Hq7Ho5few/V4jNJ7uB6PWXoP1+OxSu/hejx26T1cj8cpvYfr8bil93A9Hq/0Hq7H45few/V4QOk9XI8nKL2H6/GEpfdw3Z6o9J5O6/EkjU9ceq7Hk5bew/V4stJ7uB5PXnoP1+MpSu/hejxl6T1cj6cqvYfr8dSl93A9nqb0Hq7H05bew/V4utJ7uB5PHx6uxzOEh+vxjOHhejxTeLgezxwersezhIfr8azh4Xo8W3i4Hs8eHq7Hc4SH6/Gc4eF6PFd4uB7PHR6ux/OEh+vxvOHhejxfeLgezx8erscLhIfr8YLh4Xq8UHi4Hi8cHq7Hi4SH6/Gi4eF6vFh4uB4vHh6ux0uEh+vxkuHherxUeLgeLx0ersfLhIfr8bLh4Xq8XHi4Hi8fHq7HK4SH6/aK4em0Hq/cfqXgerxKeLgerxoerserhYfr8erh4Xq8Rni4Hq8ZHq7Ha4WH6/Ha4eF6vE54uB6vGx6ux+uFh+vx+uHherxBeLgebxgerscbhYfr8cbh4Xq8SXi4Hm8aHq7Hm4WH6/Hm4eF6vEV4uB5vGR6ux1uFh+vx1uHherxNeLgebxsersfbhYfr8fbh4Xq8Q3i4Hu8YHq7HO4WH6/HO4eF6vEt4uB7vGh6ux7uFh+vx7uHherxHeLge7xkersd7hYfr8d7h4Xq8T3i4Hu8bHq7H+4WH6/H+4eG6fUB4Oq3HB7U/MLgeHxwerseHhIfr8aHh4Xp8WHi4Hh8eHq7HR4SH6/GR4eF6fFR4uB4fHR6ux8eEh+vxseHhenxceLgeHx8erscnhIfr8Ynh4Xp8Uni4Hp8cHq7Hp4SH6/Gp4eF6fFp4uB6fHh6ux2eEh+vxmeHhenxWeLgenx0ersfnhIfr8bnh4Xp8Xni4Hp8fHq7HF4SH6/GF4eF6fFF4uB5fHB6ux5eEh+vxpeHhenxZeLgeXx4ersdXhIfr8ZXh4Xp8VXi4Hl8dHq7H14SH6/G14eF6fF14uG5fH55O6/GN7W8Irsc3hYfr8c3h4Xp8S3i4Ht8aHq7Ht4WH6/Ht4eF6fEd4uB7fGR6ux3eFh+vx3eHhenxPeLge3xsersf3hYfr8f3h4Xr8QHi4Hj8YHq7HD4WH6/HD4eF6/Eh4uB4/Gh6ux4+Fh+vx4+HhevxEeLgePxkersdPhYfr8dPh4Xr8THi4Hj8bHq7Hz4WH6/Hz4eF6/EJ4uB6/GB6uxy+Fh+vxy+HhevxKeLgevxoersevhYfr8evh4Xr8Rni4Hr8ZHq7Hb4WH6/Hb4eF6/E54uB6/Gx6u2++Fp9N6/EH794Pr8Yfh4Xr8UXi4Hn8cHq7Hn4SH6/Gn4eF6/Fl4uB5/Hh6ux1+Eh+vxl+HhevxVeLgefx0ersffhIfr8bfh4Xr8XXi4Hn8fHq7HP4SH6/GP4eF6/FN4uB7/HB6ux7+Eh+vxr+HhevxbeLge/x4ersd/hIfr8Z/h4Xr8V3i4Hv8dHq7H/4SH6/G/4eF6/F94uB4PVHsP1+OBa+/hejxI7T1cjwetvYfr8WC193A9LrX3cD2utfdwPR689h6ux0PU3sP1eMjae7geD1V7D9fjoWvv4Xo8TO09XI+Hrb2H6/Zwtfd0Wo9HaHz42nM9HrH2Hq7HI9Xew/V45Np7uB6PUnsP1+NRa+/hejxa7T1cj0evvYfr8Ri193A9HrP2Hq7HY9Xew/V47Np7uB6PU3sP1+Nxa+/hejxe7T1cj8evvYfr8YDae7geT1B7D9fjCWvv4Xo8Ue09XI8nrr2H6/EktfdwPZ609h6ux5PV3sP1ePLae7geT1F7D9fjKWvv4Xo8Ve09XI+nrr2H6/E0tfdwPZ629h6ux9PV3sP1ePrwcD2eITxcj2cMD9fjmcLD9Xjm8HA9niU8XI9nDQ/X49nCw/V49vBwPZ4jPFyP5wwP1+O5wsP1eO7wcN2eJ7z/Ab3zBXk=AQAAAACAAABwLwAA+wcAAA==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eJzj5BwFo2AUjIJRMPwBAGORNV8=
26
+ </AppendedData>
27
+ </VTKFile>
CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/Surf.pvd ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ <?xml version="1.0"?>
2
+ <VTKFile type="Collection" version="0.1"
3
+ byte_order="LittleEndian"
4
+ compressor="vtkZLibDataCompressor">
5
+ <Collection>
6
+ <DataSet timestep="300000" group="" part="0"
7
+ file="Surf/Surf_300000.vtu"/>
8
+ </Collection>
9
+ </VTKFile>
CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/config.txt ADDED
@@ -0,0 +1,78 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ variable BZ equal 1.380649E-23
2
+ variable PI equal 3.1415926536
3
+ variable molecular_mass equal 6.63E-26
4
+ variable molecular_diameter equal 4.17E-10
5
+ variable gamma equal 1.666666667
6
+ variable R equal ${BZ}/${molecular_mass}
7
+ variable L equal 1.0
8
+ variable xmin equal -5.0
9
+ variable xmax equal 6.0
10
+ variable ymin equal -5.0
11
+ variable ymax equal 5.0
12
+ variable Kn equal 0.3
13
+ variable Ma equal 2.6
14
+ variable To equal 273.0
15
+ variable Tb equal 273.0
16
+ variable theta equal 0.0
17
+ variable mfp equal ${Kn}*${L}
18
+ variable cpmfp equal 4
19
+ variable nden equal 1.0/sqrt(2.0)/${PI}/${molecular_diameter}/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
20
+ variable sos equal sqrt(${gamma}*${R}*${To})
21
+ variable vo equal ${Ma}*${sos}
22
+ variable vx equal ${vo}*cos(${theta}*2*PI/360)
23
+ variable vy equal ${vo}*sin(${theta}*2*PI/360)
24
+ variable ppc equal 30
25
+ variable xncells equal (${xmax}-${xmin})/${mfp}*${cpmfp}
26
+ variable yncells equal (${ymax}-${ymin})/${mfp}*${cpmfp}
27
+ variable Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
28
+ variable tstep equal (-${xmin}+${xmax})/${vx}/${xncells}/10/4
29
+ variable nave equal 10000
30
+ variable noutput equal 300000
31
+ clear
32
+ shell mkdir output
33
+ shell mkdir grid
34
+ shell mkdir surf
35
+ seed 7
36
+ dimension 2
37
+ global nrho ${nden}
38
+ global fnum ${Fnum}
39
+ timestep ${tstep}
40
+ global gridcut 1.0 particle/reorder 100 comm/sort yes
41
+ region 1 cylinder z 0.0 0.0 3.50 -0.5 0.5
42
+ region 2 cylinder z 0.0 0.0 2.00 -0.5 0.5
43
+ region 3 cylinder z 0.0 0.0 0.80 -0.5 0.5
44
+ boundary o o p
45
+ create_box ${xmin} ${xmax} ${ymin} ${ymax} -0.5 0.5
46
+ create_grid ${xncells} ${yncells} 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
47
+ balance_grid rcb cell
48
+ species gas.species Ar
49
+ mixture air Ar frac 1.0
50
+ mixture air Ar vstream ${vx} ${vy} 0.0 temp ${To}
51
+ collide vss air gas.vhs
52
+ collide_modify vremax 100 yes remain no nearcp yes 10
53
+ read_surf cylinder.surf
54
+ surf_collide 1 diffuse 273.0 1.0
55
+ surf_modify all collide 1
56
+ fix in emit/face air xlo ylo yhi
57
+ balance_grid rcb cell
58
+ create_particles air n 0
59
+ stats 10000
60
+ stats_style step cpu np nattempt ncoll nscoll npave nscollave
61
+ run 200000
62
+ compute 1 grid all air n nrho massrho u v w
63
+ compute 2 grid all air trot
64
+ compute 3 tvib/grid all air
65
+ compute 4 thermal/grid all air press temp
66
+ fix 1 ave/grid all 1 ${nave} ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
67
+ dump 1 grid all ${noutput} output/grid.*.dat id xc yc f_1[*]
68
+ dump_modify 1 format float %12.5g
69
+ compute 5 surf all air n press px py shx shy fx fy etot erot evib
70
+ fix 2 ave/surf all 1 ${nave} ${nave} c_5[*] ave running
71
+ dump 2 surf all ${noutput} output/surf.*.dat id v1x v1y v2x v2y f_2[*]
72
+ dump_modify 2 format float %12.5g
73
+ compute 6 lambda/grid f_1[2] f_1[8] Ar kx
74
+ dump 3 grid all ${noutput} output/lambdakn.*.dat id xc yc c_6[*]
75
+ dump_modify 3 format float %12.5g
76
+ run 100000
77
+ write_grid grid/final-grid.dat
78
+ write_surf surf/geom.surf
CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/cylinder.surf ADDED
@@ -0,0 +1,410 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ surf file from Pointwise
2
+
3
+ 200 points
4
+ 200 lines
5
+
6
+ Points
7
+
8
+ 1 0.5 0.0
9
+ 2 0.499753280182866E+000 -0.157053795390643E-001
10
+ 3 0.499013364214136E+000 -0.313952597646568E-001
11
+ 4 0.497780982301540E+000 -0.470541566592573E-001
12
+ 5 0.496057350657239E+000 -0.626666167821523E-001
13
+ 6 0.493844170297569E+000 -0.782172325201156E-001
14
+ 7 0.491143625364344E+000 -0.936906572928624E-001
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+ # molecular mass (kg)
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CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/grid/Grid_0_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/grid/Grid_1_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/grid/Grid_2_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/grid/Grid_300000.pvtu ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ <?xml version="1.0"?>
2
+ <VTKFile type="PUnstructuredGrid" version="0.1"
3
+ byte_order="LittleEndian"
4
+ compressor="vtkZLibDataCompressor">
5
+ <PUnstructuredGrid GhostLevel="0">
6
+ <PCellData>
7
+ <PDataArray type="Float64" Name="id"/>
8
+ <PDataArray type="Float64" Name="xc"/>
9
+ <PDataArray type="Float64" Name="yc"/>
10
+ <PDataArray type="Float64" Name="f_1[1]"/>
11
+ <PDataArray type="Float64" Name="f_1[2]"/>
12
+ <PDataArray type="Float64" Name="f_1[3]"/>
13
+ <PDataArray type="Float64" Name="f_1[4]"/>
14
+ <PDataArray type="Float64" Name="f_1[5]"/>
15
+ <PDataArray type="Float64" Name="f_1[6]"/>
16
+ <PDataArray type="Float64" Name="f_1[7]"/>
17
+ <PDataArray type="Float64" Name="f_1[8]"/>
18
+ <PDataArray type="Float64" Name="f_1[9]"/>
19
+ <PDataArray type="Float64" Name="f_1[10]"/>
20
+ </PCellData>
21
+ <PPoints>
22
+ <PDataArray type="Float32" Name="Points" NumberOfComponents="3"/>
23
+ </PPoints>
24
+ <Piece Source="Grid_0_300000.vtu"/>
25
+ <Piece Source="Grid_1_300000.vtu"/>
26
+ <Piece Source="Grid_2_300000.vtu"/>
27
+ <Piece Source="Grid_3_300000.vtu"/>
28
+ </PUnstructuredGrid>
29
+ </VTKFile>
CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/grid/Grid_3_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/grid/final-grid.dat ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/log.sparta ADDED
@@ -0,0 +1,318 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ SPARTA (4 Sep 2024)
2
+ Running on 128 MPI task(s)
3
+ variable BZ equal 1.380649E-23
4
+ variable PI equal 3.1415926536
5
+ variable molecular_mass equal 6.63E-26
6
+ variable molecular_diameter equal 4.17E-10
7
+ variable gamma equal 1.666666667
8
+ variable R equal ${BZ}/${molecular_mass}
9
+ variable R equal 1.380649e-23/${molecular_mass}
10
+ variable R equal 1.380649e-23/6.63e-26
11
+ variable L equal 1.0
12
+ variable xmin equal -5.0
13
+ variable xmax equal 6.0
14
+ variable ymin equal -5.0
15
+ variable ymax equal 5.0
16
+ variable Kn equal 0.3
17
+ variable Ma equal 2.6
18
+ variable To equal 273.0
19
+ variable Tb equal 273.0
20
+ variable theta equal 0.0
21
+ variable mfp equal ${Kn}*${L}
22
+ variable mfp equal 0.3*${L}
23
+ variable mfp equal 0.3*1
24
+ variable cpmfp equal 4
25
+ variable nden equal 1.0/sqrt(2.0)/${PI}/${molecular_diameter}/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
26
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/${molecular_diameter}/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
27
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
28
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(${mfp}/${cpmfp}*${Kn})
29
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.3/${cpmfp}*${Kn})
30
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.3/4*${Kn})
31
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.3/4*0.3)
32
+ variable sos equal sqrt(${gamma}*${R}*${To})
33
+ variable sos equal sqrt(1.666666667*${R}*${To})
34
+ variable sos equal sqrt(1.666666667*208.242684766214*${To})
35
+ variable sos equal sqrt(1.666666667*208.242684766214*273)
36
+ variable vo equal ${Ma}*${sos}
37
+ variable vo equal 2.6*${sos}
38
+ variable vo equal 2.6*307.815564238681
39
+ variable vx equal ${vo}*cos(${theta}*2*PI/360)
40
+ variable vx equal 800.320467020571*cos(${theta}*2*PI/360)
41
+ variable vx equal 800.320467020571*cos(0*2*PI/360)
42
+ variable vy equal ${vo}*sin(${theta}*2*PI/360)
43
+ variable vy equal 800.320467020571*sin(${theta}*2*PI/360)
44
+ variable vy equal 800.320467020571*sin(0*2*PI/360)
45
+ variable ppc equal 30
46
+ variable xncells equal (${xmax}-${xmin})/${mfp}*${cpmfp}
47
+ variable xncells equal (6-${xmin})/${mfp}*${cpmfp}
48
+ variable xncells equal (6--5)/${mfp}*${cpmfp}
49
+ variable xncells equal (6--5)/0.3*${cpmfp}
50
+ variable xncells equal (6--5)/0.3*4
51
+ variable yncells equal (${ymax}-${ymin})/${mfp}*${cpmfp}
52
+ variable yncells equal (5-${ymin})/${mfp}*${cpmfp}
53
+ variable yncells equal (5--5)/${mfp}*${cpmfp}
54
+ variable yncells equal (5--5)/0.3*${cpmfp}
55
+ variable yncells equal (5--5)/0.3*4
56
+ variable Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
57
+ variable Fnum equal 5.7528162356074e+19*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
58
+ variable Fnum equal 5.7528162356074e+19*(6-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
59
+ variable Fnum equal 5.7528162356074e+19*(6--5)*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
60
+ variable Fnum equal 5.7528162356074e+19*(6--5)*(5-${ymin})/${ppc}/${xncells}/${yncells}
61
+ variable Fnum equal 5.7528162356074e+19*(6--5)*(5--5)/${ppc}/${xncells}/${yncells}
62
+ variable Fnum equal 5.7528162356074e+19*(6--5)*(5--5)/30/${xncells}/${yncells}
63
+ variable Fnum equal 5.7528162356074e+19*(6--5)*(5--5)/30/146.666666666667/${yncells}
64
+ variable Fnum equal 5.7528162356074e+19*(6--5)*(5--5)/30/146.666666666667/133.333333333333
65
+ variable tstep equal (-${xmin}+${xmax})/${vx}/${xncells}/10/4
66
+ variable tstep equal (--5+${xmax})/${vx}/${xncells}/10/4
67
+ variable tstep equal (--5+6)/${vx}/${xncells}/10/4
68
+ variable tstep equal (--5+6)/800.320467020571/${xncells}/10/4
69
+ variable tstep equal (--5+6)/800.320467020571/146.666666666667/10/4
70
+ variable nave equal 10000
71
+ variable noutput equal 300000
72
+ clear
73
+ Running on 128 MPI task(s)
74
+ shell mkdir output
75
+ shell mkdir grid
76
+ shell mkdir surf
77
+ seed 7
78
+ dimension 2
79
+ global nrho ${nden}
80
+ global nrho 5.7528162356074e+19
81
+ global fnum ${Fnum}
82
+ global fnum 1.07865304417639e+16
83
+ timestep ${tstep}
84
+ timestep 2.34281150772045e-06
85
+ global gridcut 1.0 particle/reorder 100 comm/sort yes
86
+ region 1 cylinder z 0.0 0.0 3.50 -0.5 0.5
87
+ region 2 cylinder z 0.0 0.0 2.00 -0.5 0.5
88
+ region 3 cylinder z 0.0 0.0 0.80 -0.5 0.5
89
+ boundary o o p
90
+ create_box ${xmin} ${xmax} ${ymin} ${ymax} -0.5 0.5
91
+ create_box -5 ${xmax} ${ymin} ${ymax} -0.5 0.5
92
+ create_box -5 6 ${ymin} ${ymax} -0.5 0.5
93
+ create_box -5 6 -5 ${ymax} -0.5 0.5
94
+ create_box -5 6 -5 5 -0.5 0.5
95
+ Created orthogonal box = (-5 -5 -0.5) to (6 5 0.5)
96
+ create_grid ${xncells} ${yncells} 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
97
+ create_grid 146.666666666667 ${yncells} 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
98
+ create_grid 146.666666666667 133.333333333333 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
99
+ Created 85160 child grid cells
100
+ CPU time = 0.123684 secs
101
+ create/ghost percent = 0.978128 99.0219
102
+ balance_grid rcb cell
103
+ Balance grid migrated 85003 cells
104
+ CPU time = 0.0983299 secs
105
+ reassign/sort/migrate/ghost percent = 53.8936 0.0310791 8.38241 37.6929
106
+ species gas.species Ar
107
+ mixture air Ar frac 1.0
108
+ mixture air Ar vstream ${vx} ${vy} 0.0 temp ${To}
109
+ mixture air Ar vstream 800.320467020571 ${vy} 0.0 temp ${To}
110
+ mixture air Ar vstream 800.320467020571 0 0.0 temp ${To}
111
+ mixture air Ar vstream 800.320467020571 0 0.0 temp 273
112
+ collide vss air gas.vhs
113
+ collide_modify vremax 100 yes remain no nearcp yes 10
114
+ read_surf cylinder.surf
115
+ 200 lines
116
+ -0.5 0.5 xlo xhi
117
+ -0.5 0.5 ylo yhi
118
+ 0 0 zlo zhi
119
+ 0.0157073 min line length
120
+ 428 0 = cells overlapping surfs, overlap cells with unmarked corner pts
121
+ 76068 8664 428 = cells outside/inside/overlapping surfs
122
+ 428 = surf cells with 1,2,etc splits
123
+ 109.215 109.215 = cell-wise and global flow volume
124
+ CPU time = 0.107451 secs
125
+ read/check/sort/surf2grid/ghost/inout/particle percent = 19.9184 20.4396 3.21451 22.6877 33.7398 6.21383 0.144491
126
+ surf2grid time = 0.0243783 secs
127
+ map/comm1/comm2/comm3/comm4/split percent = 14.2902 23.9214 5.03996 4.57659 11.4375 6.34754
128
+ surf_collide 1 diffuse 273.0 1.0
129
+ surf_modify all collide 1
130
+ fix in emit/face air xlo ylo yhi
131
+ balance_grid rcb cell
132
+ Balance grid migrated 1177 cells
133
+ CPU time = 0.046942 secs
134
+ reassign/sort/migrate/ghost percent = 5.63318 0.0723659 20.4425 73.8519
135
+ create_particles air n 0
136
+ Created 582478 particles
137
+ CPU time = 0.0173516 secs
138
+ stats 10000
139
+ stats_style step cpu np nattempt ncoll nscoll npave nscollave
140
+ run 200000
141
+ Memory usage per proc in Mbytes:
142
+ particles (ave,min,max) = 1.7666 0 3.375
143
+ grid (ave,min,max) = 3.76965 1.51379 6.20129
144
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
145
+ total (ave,min,max) = 5.55685 3.22189 7.90939
146
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
147
+ 0 0 582478 0 0 0 0 0
148
+ 10000 15.393879 628321 18887 15758 16 602461.93 11.6255
149
+ 20000 35.342102 637241 19457 16385 13 618417.73 11.72655
150
+ 30000 53.367247 636867 19537 16430 12 624780.48 11.757267
151
+ 40000 73.569697 638273 19722 16510 10 627963.16 11.776675
152
+ 50000 92.939776 637238 19422 16216 13 629940.82 11.77162
153
+ 60000 111.75259 636682 19587 16477 12 631196.9 11.77595
154
+ 70000 130.31753 636752 19528 16362 11 632078.14 11.779029
155
+ 80000 148.61165 637674 19428 16220 12 632773.43 11.782025
156
+ 90000 168.42008 637404 19468 16282 12 633338.59 11.790711
157
+ 100000 187.58431 637170 19405 16221 11 633727.47 11.79313
158
+ 110000 205.83665 636287 19455 16351 13 634007.53 11.792891
159
+ 120000 225.49434 636926 19237 16001 20 634269.86 11.793492
160
+ 130000 244.11476 637720 19502 16383 11 634512.83 11.791723
161
+ 140000 262.51272 638014 19647 16553 7 634774.45 11.79465
162
+ 150000 282.2062 637226 19420 16302 12 634978.18 11.79672
163
+ 160000 300.34369 637093 19535 16349 11 635112.09 11.796681
164
+ 170000 319.30485 637802 19495 16461 19 635254.08 11.796865
165
+ 180000 338.60675 637450 19572 16363 15 635376.74 11.797583
166
+ 190000 357.37738 637943 19492 16292 9 635500.64 11.7966
167
+ 200000 375.89462 637721 19452 16295 13 635600.54 11.794465
168
+ Loop time of 375.895 on 128 procs for 200000 steps with 637721 particles
169
+
170
+ MPI task timing breakdown:
171
+ Section | min time | avg time | max time |%varavg| %total
172
+ ---------------------------------------------------------------
173
+ Move | 0.023641 | 15.888 | 92.591 | 502.7 | 4.23
174
+ Coll | 0.43238 | 20.171 | 152.42 | 604.4 | 5.37
175
+ Sort | 0.14639 | 2.9145 | 21.32 | 232.4 | 0.78
176
+ Comm | 63.829 | 96.183 | 106.91 | 90.2 | 25.59
177
+ Modify | 0.020503 | 0.14897 | 2.6566 | 102.7 | 0.04
178
+ Output | 0.0037781 | 0.016785 | 0.018625 | 1.9 | 0.00
179
+ Other | | 240.6 | | | 64.00
180
+
181
+ Particle moves = 127120107840 (127B)
182
+ Cells touched = 133318931534 (133B)
183
+ Particle comms = 245978216 (246M)
184
+ Boundary collides = 0 (0K)
185
+ Boundary exits = 25170819 (25.2M)
186
+ SurfColl checks = 98500012 (98.5M)
187
+ SurfColl occurs = 2358893 (2.36M)
188
+ Surf reactions = 0 (0K)
189
+ Collide attempts = 4277674208 (4.28B)
190
+ Collide occurs = 3285838692 (3.29B)
191
+ Reactions = 0 (0K)
192
+ Particles stuck = 0
193
+ Axisymm bad moves = 0
194
+
195
+ Particle-moves/CPUsec/proc: 2.64203e+06
196
+ Particle-moves/step: 635601
197
+ Cell-touches/particle/step: 1.04876
198
+ Particle comm iterations/step: 1
199
+ Particle fraction communicated: 0.00193501
200
+ Particle fraction colliding with boundary: 0
201
+ Particle fraction exiting boundary: 0.000198008
202
+ Surface-checks/particle/step: 0.000774858
203
+ Surface-collisions/particle/step: 1.85564e-05
204
+ Surf-reactions/particle/step: 0
205
+ Collision-attempts/particle/step: 0.0336506
206
+ Collisions/particle/step: 0.0258483
207
+ Reactions/particle/step: 0
208
+
209
+ Particles: 4982.2 ave 30504 max 0 min
210
+ Histogram: 82 14 8 4 7 5 4 0 2 2
211
+ Cells: 665.312 ave 666 max 665 min
212
+ Histogram: 88 0 0 0 0 0 0 0 0 40
213
+ GhostCell: 17265 ave 31629 max 955 min
214
+ Histogram: 22 8 12 10 17 3 6 4 16 30
215
+ EmptyCell: 0 ave 0 max 0 min
216
+ Histogram: 128 0 0 0 0 0 0 0 0 0
217
+ Surfs: 200 ave 200 max 200 min
218
+ Histogram: 128 0 0 0 0 0 0 0 0 0
219
+ GhostSurf: 0 ave 0 max 0 min
220
+ Histogram: 128 0 0 0 0 0 0 0 0 0
221
+ compute 1 grid all air n nrho massrho u v w
222
+ compute 2 grid all air trot
223
+ compute 3 tvib/grid all air
224
+ compute 4 thermal/grid all air press temp
225
+ fix 1 ave/grid all 1 ${nave} ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
226
+ fix 1 ave/grid all 1 10000 ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
227
+ fix 1 ave/grid all 1 10000 10000 c_1[*] c_4[*] c_2[*] c_3[*] ave running
228
+ dump 1 grid all ${noutput} output/grid.*.dat id xc yc f_1[*]
229
+ dump 1 grid all 300000 output/grid.*.dat id xc yc f_1[*]
230
+ dump_modify 1 format float %12.5g
231
+ compute 5 surf all air n press px py shx shy fx fy etot erot evib
232
+ fix 2 ave/surf all 1 ${nave} ${nave} c_5[*] ave running
233
+ fix 2 ave/surf all 1 10000 ${nave} c_5[*] ave running
234
+ fix 2 ave/surf all 1 10000 10000 c_5[*] ave running
235
+ dump 2 surf all ${noutput} output/surf.*.dat id v1x v1y v2x v2y f_2[*]
236
+ dump 2 surf all 300000 output/surf.*.dat id v1x v1y v2x v2y f_2[*]
237
+ dump_modify 2 format float %12.5g
238
+ compute 6 lambda/grid f_1[2] f_1[8] Ar kx
239
+ dump 3 grid all ${noutput} output/lambdakn.*.dat id xc yc c_6[*]
240
+ dump 3 grid all 300000 output/lambdakn.*.dat id xc yc c_6[*]
241
+ dump_modify 3 format float %12.5g
242
+ run 100000
243
+ Memory usage per proc in Mbytes:
244
+ particles (ave,min,max) = 1.79297 0 3.375
245
+ grid (ave,min,max) = 3.76965 1.51379 6.20129
246
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
247
+ total (ave,min,max) = 5.80682 3.4453 8.1333
248
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
249
+ 200000 0 637721 19452 16295 0 0 0
250
+ 210000 32.598899 637302 19508 16387 11 637853.22 11.8329
251
+ 220000 64.074295 637424 19495 16365 7 637844.06 11.8507
252
+ 230000 95.836529 638211 19541 16366 12 637857.73 11.8371
253
+ 240000 127.39805 637197 19372 16261 10 637761.74 11.8244
254
+ 250000 159.80265 637624 19648 16452 11 637679.61 11.8165
255
+ 260000 191.181 638164 19550 16403 14 637756.96 11.806833
256
+ 270000 223.14354 637405 19509 16247 18 637801.51 11.798857
257
+ 280000 254.72164 637710 19524 16373 10 637744.65 11.798288
258
+ 290000 287.55743 637672 19539 16415 8 637778.56 11.802656
259
+ 300000 319.45093 637426 19508 16323 7 637787.07 11.80447
260
+ Loop time of 319.451 on 128 procs for 100000 steps with 637426 particles
261
+
262
+ MPI task timing breakdown:
263
+ Section | min time | avg time | max time |%varavg| %total
264
+ ---------------------------------------------------------------
265
+ Move | 0.012758 | 8.0199 | 46.494 | 355.5 | 2.51
266
+ Coll | 0.21713 | 10.239 | 79.099 | 434.2 | 3.21
267
+ Sort | 0.085899 | 1.4928 | 9.8866 | 164.3 | 0.47
268
+ Comm | 36.129 | 52.997 | 59.202 | 64.6 | 16.59
269
+ Modify | 3.0307 | 22.026 | 120.68 | 546.9 | 6.89
270
+ Output | 0.036926 | 0.038546 | 0.042688 | 0.6 | 0.01
271
+ Other | | 224.6 | | | 70.32
272
+
273
+ Particle moves = 63778706665 (63.8B)
274
+ Cells touched = 66885833958 (66.9B)
275
+ Particle comms = 123289403 (123M)
276
+ Boundary collides = 0 (0K)
277
+ Boundary exits = 12617207 (12.6M)
278
+ SurfColl checks = 49222256 (49.2M)
279
+ SurfColl occurs = 1180447 (1.18M)
280
+ Surf reactions = 0 (0K)
281
+ Collide attempts = 2156285543 (2.16B)
282
+ Collide occurs = 1656159380 (1.66B)
283
+ Reactions = 0 (0K)
284
+ Particles stuck = 0
285
+ Axisymm bad moves = 0
286
+
287
+ Particle-moves/CPUsec/proc: 1.55977e+06
288
+ Particle-moves/step: 637787
289
+ Cell-touches/particle/step: 1.04872
290
+ Particle comm iterations/step: 1
291
+ Particle fraction communicated: 0.00193308
292
+ Particle fraction colliding with boundary: 0
293
+ Particle fraction exiting boundary: 0.000197828
294
+ Surface-checks/particle/step: 0.000771766
295
+ Surface-collisions/particle/step: 1.85085e-05
296
+ Surf-reactions/particle/step: 0
297
+ Collision-attempts/particle/step: 0.0338089
298
+ Collisions/particle/step: 0.0259673
299
+ Reactions/particle/step: 0
300
+
301
+ Particles: 4979.89 ave 30389 max 0 min
302
+ Histogram: 82 14 7 5 6 5 5 0 2 2
303
+ Cells: 665.312 ave 666 max 665 min
304
+ Histogram: 88 0 0 0 0 0 0 0 0 40
305
+ GhostCell: 17265 ave 31629 max 955 min
306
+ Histogram: 22 8 12 10 17 3 6 4 16 30
307
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CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/mir.txt ADDED
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+ read_grid grid/final-grid.dat
CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/output/lambdakn.300000.dat ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/output/surf.300000.dat ADDED
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CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/runmpirun128.sh ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #!/bin/bash
2
+ #SBATCH -J Cylinder——Kn
3
+ #SBATCH -p wzhcnormal
4
+ #SBATCH -N 2
5
+ #SBATCH --ntasks-per-node=64
6
+
7
+
8
+ module purge
9
+ module load compiler/devtoolset/7.3.1
10
+ module load mpi/hpcx/2.11.0/gcc-7.3.1
11
+ export UCX_WARN_UNUSED_ENV_VARS=n
12
+ /public/software/mpi/hpcx/v2.11.0/gcc-7.3.1/bin/mpirun -n 128 ../../../sep2024-sparta/src/spa_mpi <config.txt
13
+
14
+ /work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/grid2paraview.py mir.txt Grid -r ./output/grid.*.dat
15
+
16
+ /work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/grid2paraview.py mir.txt Lambda -r ./output/lambdakn.*.dat
17
+
18
+ /work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/surf2paraview.py ./surf/geom.surf Surf -r ./output/surf.*.dat
CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/runmpirun64.sh ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #!/bin/bash
2
+ #SBATCH -J Cylinder——Kn
3
+ #SBATCH -p wzhcnormal
4
+ #SBATCH -N 1
5
+ #SBATCH --ntasks-per-node=64
6
+
7
+
8
+ module purge
9
+ module load compiler/devtoolset/7.3.1
10
+ module load mpi/hpcx/2.11.0/gcc-7.3.1
11
+ export UCX_WARN_UNUSED_ENV_VARS=n
12
+ /public/software/mpi/hpcx/v2.11.0/gcc-7.3.1/bin/mpirun -n 64 ../../../sep2024-sparta/src/spa_mpi <config.txt
13
+
14
+ /work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/grid2paraview.py mir.txt Grid -r ./output/grid.*.dat
15
+
16
+ /work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/grid2paraview.py mir.txt Lambda -r ./output/lambdakn.*.dat
17
+
18
+ /work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/surf2paraview.py ./surf/geom.surf Surf -r ./output/surf.*.dat
CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/slurm-28429356.out ADDED
@@ -0,0 +1,204 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ SPARTA (4 Sep 2024)
2
+ Running on 128 MPI task(s)
3
+ Running on 128 MPI task(s)
4
+ Created orthogonal box = (-5 -5 -0.5) to (6 5 0.5)
5
+ Created 85160 child grid cells
6
+ CPU time = 0.123684 secs
7
+ create/ghost percent = 0.978128 99.0219
8
+ Balance grid migrated 85003 cells
9
+ CPU time = 0.0983299 secs
10
+ reassign/sort/migrate/ghost percent = 53.8936 0.0310791 8.38241 37.6929
11
+ Reading surface file ...
12
+ 200 lines
13
+ -0.5 0.5 xlo xhi
14
+ -0.5 0.5 ylo yhi
15
+ 0 0 zlo zhi
16
+ 0.0157073 min line length
17
+ 428 0 = cells overlapping surfs, overlap cells with unmarked corner pts
18
+ 76068 8664 428 = cells outside/inside/overlapping surfs
19
+ 428 = surf cells with 1,2,etc splits
20
+ 109.214731023047 109.214731023047 = cell-wise and global flow volume
21
+ CPU time = 0.107451 secs
22
+ read/check/sort/surf2grid/ghost/inout/particle percent = 19.9184 20.4396 3.21451 22.6877 33.7398 6.21383 0.144491
23
+ surf2grid time = 0.0243783 secs
24
+ map/comm1/comm2/comm3/comm4/split percent = 14.2902 23.9214 5.03996 4.57659 11.4375 6.34754
25
+ Balance grid migrated 1177 cells
26
+ CPU time = 0.046942 secs
27
+ reassign/sort/migrate/ghost percent = 5.63318 0.0723659 20.4425 73.8519
28
+ Creating particles ...
29
+ Created 582478 particles
30
+ CPU time = 0.0173516 secs
31
+ Memory usage per proc in Mbytes:
32
+ particles (ave,min,max) = 1.7666 0 3.375
33
+ grid (ave,min,max) = 3.76965 1.51379 6.20129
34
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
35
+ total (ave,min,max) = 5.55685 3.22189 7.90939
36
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
37
+ 0 0 582478 0 0 0 0 0
38
+ 10000 15.393879 628321 18887 15758 16 602461.93 11.6255
39
+ 20000 35.342102 637241 19457 16385 13 618417.73 11.72655
40
+ 30000 53.367247 636867 19537 16430 12 624780.48 11.757267
41
+ 40000 73.569697 638273 19722 16510 10 627963.16 11.776675
42
+ 50000 92.939776 637238 19422 16216 13 629940.82 11.77162
43
+ 60000 111.75259 636682 19587 16477 12 631196.9 11.77595
44
+ 70000 130.31753 636752 19528 16362 11 632078.14 11.779029
45
+ 80000 148.61165 637674 19428 16220 12 632773.43 11.782025
46
+ 90000 168.42008 637404 19468 16282 12 633338.59 11.790711
47
+ 100000 187.58431 637170 19405 16221 11 633727.47 11.79313
48
+ 110000 205.83665 636287 19455 16351 13 634007.53 11.792891
49
+ 120000 225.49434 636926 19237 16001 20 634269.86 11.793492
50
+ 130000 244.11476 637720 19502 16383 11 634512.83 11.791723
51
+ 140000 262.51272 638014 19647 16553 7 634774.45 11.79465
52
+ 150000 282.2062 637226 19420 16302 12 634978.18 11.79672
53
+ 160000 300.34369 637093 19535 16349 11 635112.09 11.796681
54
+ 170000 319.30485 637802 19495 16461 19 635254.08 11.796865
55
+ 180000 338.60675 637450 19572 16363 15 635376.74 11.797583
56
+ 190000 357.37738 637943 19492 16292 9 635500.64 11.7966
57
+ 200000 375.89462 637721 19452 16295 13 635600.54 11.794465
58
+ Loop time of 375.895 on 128 procs for 200000 steps with 637721 particles
59
+
60
+ MPI task timing breakdown:
61
+ Section | min time | avg time | max time |%varavg| %total
62
+ ---------------------------------------------------------------
63
+ Move | 0.023641 | 15.888 | 92.591 | 502.7 | 4.23
64
+ Coll | 0.43238 | 20.171 | 152.42 | 604.4 | 5.37
65
+ Sort | 0.14639 | 2.9145 | 21.32 | 232.4 | 0.78
66
+ Comm | 63.829 | 96.183 | 106.91 | 90.2 | 25.59
67
+ Modify | 0.020503 | 0.14897 | 2.6566 | 102.7 | 0.04
68
+ Output | 0.0037781 | 0.016785 | 0.018625 | 1.9 | 0.00
69
+ Other | | 240.6 | | | 64.00
70
+
71
+ Particle moves = 127120107840 (127B)
72
+ Cells touched = 133318931534 (133B)
73
+ Particle comms = 245978216 (246M)
74
+ Boundary collides = 0 (0K)
75
+ Boundary exits = 25170819 (25.2M)
76
+ SurfColl checks = 98500012 (98.5M)
77
+ SurfColl occurs = 2358893 (2.36M)
78
+ Surf reactions = 0 (0K)
79
+ Collide attempts = 4277674208 (4.28B)
80
+ Collide occurs = 3285838692 (3.29B)
81
+ Gas reactions = 0 (0K)
82
+ Particles stuck = 0
83
+ Axisymm bad moves = 0
84
+
85
+ Particle-moves/CPUsec/proc: 2.64203e+06
86
+ Particle-moves/step: 635601
87
+ Cell-touches/particle/step: 1.04876
88
+ Particle comm iterations/step: 1
89
+ Particle fraction communicated: 0.00193501
90
+ Particle fraction colliding with boundary: 0
91
+ Particle fraction exiting boundary: 0.000198008
92
+ Surface-checks/particle/step: 0.000774858
93
+ Surface-collisions/particle/step: 1.85564e-05
94
+ Surface-reactions/particle/step: 0
95
+ Collision-attempts/particle/step: 0.0336506
96
+ Collisions/particle/step: 0.0258483
97
+ Gas-reactions/particle/step: 0
98
+
99
+ Particles: 4982.2 ave 30504 max 0 min
100
+ Histogram: 82 14 8 4 7 5 4 0 2 2
101
+ Cells: 665.312 ave 666 max 665 min
102
+ Histogram: 88 0 0 0 0 0 0 0 0 40
103
+ GhostCell: 17265 ave 31629 max 955 min
104
+ Histogram: 22 8 12 10 17 3 6 4 16 30
105
+ EmptyCell: 0 ave 0 max 0 min
106
+ Histogram: 128 0 0 0 0 0 0 0 0 0
107
+ Surfs: 200 ave 200 max 200 min
108
+ Histogram: 128 0 0 0 0 0 0 0 0 0
109
+ GhostSurf: 0 ave 0 max 0 min
110
+ Histogram: 128 0 0 0 0 0 0 0 0 0
111
+ Memory usage per proc in Mbytes:
112
+ particles (ave,min,max) = 1.79297 0 3.375
113
+ grid (ave,min,max) = 3.76965 1.51379 6.20129
114
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
115
+ total (ave,min,max) = 5.80682 3.4453 8.1333
116
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
117
+ 200000 0 637721 19452 16295 0 0 0
118
+ 210000 32.598899 637302 19508 16387 11 637853.22 11.8329
119
+ 220000 64.074295 637424 19495 16365 7 637844.06 11.8507
120
+ 230000 95.836529 638211 19541 16366 12 637857.73 11.8371
121
+ 240000 127.39805 637197 19372 16261 10 637761.74 11.8244
122
+ 250000 159.80265 637624 19648 16452 11 637679.61 11.8165
123
+ 260000 191.181 638164 19550 16403 14 637756.96 11.806833
124
+ 270000 223.14354 637405 19509 16247 18 637801.51 11.798857
125
+ 280000 254.72164 637710 19524 16373 10 637744.65 11.798288
126
+ 290000 287.55743 637672 19539 16415 8 637778.56 11.802656
127
+ 300000 319.45093 637426 19508 16323 7 637787.07 11.80447
128
+ Loop time of 319.451 on 128 procs for 100000 steps with 637426 particles
129
+
130
+ MPI task timing breakdown:
131
+ Section | min time | avg time | max time |%varavg| %total
132
+ ---------------------------------------------------------------
133
+ Move | 0.012758 | 8.0199 | 46.494 | 355.5 | 2.51
134
+ Coll | 0.21713 | 10.239 | 79.099 | 434.2 | 3.21
135
+ Sort | 0.085899 | 1.4928 | 9.8866 | 164.3 | 0.47
136
+ Comm | 36.129 | 52.997 | 59.202 | 64.6 | 16.59
137
+ Modify | 3.0307 | 22.026 | 120.68 | 546.9 | 6.89
138
+ Output | 0.036926 | 0.038546 | 0.042688 | 0.6 | 0.01
139
+ Other | | 224.6 | | | 70.32
140
+
141
+ Particle moves = 63778706665 (63.8B)
142
+ Cells touched = 66885833958 (66.9B)
143
+ Particle comms = 123289403 (123M)
144
+ Boundary collides = 0 (0K)
145
+ Boundary exits = 12617207 (12.6M)
146
+ SurfColl checks = 49222256 (49.2M)
147
+ SurfColl occurs = 1180447 (1.18M)
148
+ Surf reactions = 0 (0K)
149
+ Collide attempts = 2156285543 (2.16B)
150
+ Collide occurs = 1656159380 (1.66B)
151
+ Gas reactions = 0 (0K)
152
+ Particles stuck = 0
153
+ Axisymm bad moves = 0
154
+
155
+ Particle-moves/CPUsec/proc: 1.55977e+06
156
+ Particle-moves/step: 637787
157
+ Cell-touches/particle/step: 1.04872
158
+ Particle comm iterations/step: 1
159
+ Particle fraction communicated: 0.00193308
160
+ Particle fraction colliding with boundary: 0
161
+ Particle fraction exiting boundary: 0.000197828
162
+ Surface-checks/particle/step: 0.000771766
163
+ Surface-collisions/particle/step: 1.85085e-05
164
+ Surface-reactions/particle/step: 0
165
+ Collision-attempts/particle/step: 0.0338089
166
+ Collisions/particle/step: 0.0259673
167
+ Gas-reactions/particle/step: 0
168
+
169
+ Particles: 4979.89 ave 30389 max 0 min
170
+ Histogram: 82 14 7 5 6 5 5 0 2 2
171
+ Cells: 665.312 ave 666 max 665 min
172
+ Histogram: 88 0 0 0 0 0 0 0 0 40
173
+ GhostCell: 17265 ave 31629 max 955 min
174
+ Histogram: 22 8 12 10 17 3 6 4 16 30
175
+ EmptyCell: 0 ave 0 max 0 min
176
+ Histogram: 128 0 0 0 0 0 0 0 0 0
177
+ Surfs: 200 ave 200 max 200 min
178
+ Histogram: 128 0 0 0 0 0 0 0 0 0
179
+ GhostSurf: 0 ave 0 max 0 min
180
+ Histogram: 128 0 0 0 0 0 0 0 0 0
181
+ Writing grid file ...
182
+ grid cells = 85160
183
+ CPU time = 0.0120469 secs
184
+ Writing surface file ...
185
+ surf elements = 200
186
+ CPU time = 0.00158038 secs
187
+ Processing 4 grid chunk(s).
188
+ Completed grid chunk number: 3
189
+ Completed grid chunk number: 2
190
+ Completed grid chunk number: 1
191
+ Completed grid chunk number: 0
192
+
193
+ Done in 0:00:12 (wall clock time)
194
+
195
+ Processing 4 grid chunk(s).
196
+ Completed grid chunk number: 3
197
+ Completed grid chunk number: 2
198
+ Completed grid chunk number: 1
199
+ Completed grid chunk number: 0
200
+
201
+ Done in 0:00:11 (wall clock time)
202
+
203
+ Processing SPARTA surface information.
204
+ Processing dump result file: ['./output/surf.300000.dat']
CylinderKnMa/Kn0p30/simulation0607_Kn0p30Ma2p6/surf/Surf_300000.vtu ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ <?xml version="1.0"?>
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+ <VTKFile type="UnstructuredGrid" version="0.1" byte_order="LittleEndian" header_type="UInt32" compressor="vtkZLibDataCompressor">
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+ <UnstructuredGrid>
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+ <Piece NumberOfPoints="400" NumberOfCells="200" >
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+ <PointData>
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+ </PointData>
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+ <CellData>
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+ <DataArray type="Float64" Name="id" format="appended" RangeMin="1" RangeMax="200" offset="0" />
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+ <DataArray type="Float64" Name="v1x" format="appended" RangeMin="-0.5" RangeMax="0.5" offset="432" />
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+ <DataArray type="Float64" Name="v1y" format="appended" RangeMin="-0.5" RangeMax="0.5" offset="1468" />
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+ <DataArray type="Float64" Name="v2x" format="appended" RangeMin="-0.5" RangeMax="0.5" offset="2476" />
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+ <DataArray type="Float64" Name="v2y" format="appended" RangeMin="-0.5" RangeMax="0.5" offset="3508" />
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+ <DataArray type="Float64" Name="f_2[1]" format="appended" RangeMin="0.00318" RangeMax="0.17911" offset="4512" />
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+ <DataArray type="Float64" Name="f_2[2]" format="appended" RangeMin="0.034527" RangeMax="2.3285" offset="6536" />
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+ <DataArray type="Float64" Name="f_2[3]" format="appended" RangeMin="-0.066011" RangeMax="2.3259" offset="8612" />
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+ <DataArray type="Float64" Name="f_2[4]" format="appended" RangeMin="-1.0409" RangeMax="1.0422" offset="10720" />
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+ <DataArray type="Float64" Name="f_2[5]" format="appended" RangeMin="-0.00050054" RangeMax="0.19565" offset="12784" />
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+ <DataArray type="Float64" Name="f_2[6]" format="appended" RangeMin="-0.16854" RangeMax="0.17218" offset="14884" />
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+ <DataArray type="Float64" Name="f_2[7]" format="appended" RangeMin="-0.0010372" RangeMax="0.036545" offset="17032" />
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+ <DataArray type="Float64" Name="f_2[8]" format="appended" RangeMin="-0.013999" RangeMax="0.013976" offset="19180" />
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+ <DataArray type="Float64" Name="f_2[9]" format="appended" RangeMin="1.6517" RangeMax="209.93" offset="21324" />
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+ <DataArray type="Float64" Name="f_2[11]" format="appended" RangeMin="0" RangeMax="0" offset="23000" />
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+ <Points>
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+ <DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="0.49999998503" RangeMax="0.50000001255" offset="23052" />
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+ </Points>
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+ <Cells>
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+ <DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="24380" />
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+ <DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="25284" />
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+ <DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="25776" />
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+ </Cells>
33
+ </Piece>
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+ </UnstructuredGrid>
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+ <AppendedData encoding="base64">
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AQAAAACAAABABgAAAwYAAA==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AQAAAACAAABABgAA+AUAAA==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AQAAAACAAABABgAAFQYAAA==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AQAAAACAAABABgAANwYAAA==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AQAAAACAAABABgAANQYAAA==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AQAAAACAAABABgAAsAQAAA==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eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAABABgAAFQAAAA==eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAADAEgAA0gMAAA==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AQAAAACAAABABgAAXwEAAA==eJwtxVFEHAAAANBKkpzkJEmSJMlJkiRJkiRJkiQnSXKSJEmSJEmSJEmSZGYmmUmSJEmSJEkyMzOTzCRJkmT20Xs/LybqXazjHO8EB5zoJAed7BSnOs3pznCms5ztHOc6zyHnu8CFLnKxS1zqMpe7wpWucrVrXOs617vBjW5ys1vc6rDb3O4Od7rLEXe7x73uc78HPOghD3vEox7zuCc86SlPe8aznvO8F7zoJS97xate8wd/9Cd/9ro3/MVfvektb3vHu97zvg986CMf+8SnPvO5L3zpK1/7m7/7h3/6l3/7xrf+47++870f/OgnP/vFr37zP0dFvxfjWMc53gkOONFJDjrZKU51mtOd4UxnOds5znWeQ853gQtd5GKXuNRlLneFK13late41nWud4Mb3eRmt7jVYbe53R3udJcj7naPe93nfg940EMe9ohHPeZxT3jSU572jGc95/9sSVRSAQAAAACAAADIAAAADAAAAA==eJxjZh4eAADsVAJZ
37
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38
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_AQAAAACAAABwLwAAnwcAAA==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AQAAAACAAABwLwAA0QEAAA==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eJzt1k0rAwAAxvHUMGZmxomDw9LchaYxpB28Hb0kMlZrJbF5mzGr0awxbDUJpSwTNlGUpEwj5eBkzfKyD4ASRy/zJZ7Tc/p9g39/x2c8ajMK1A4K0aNMabKLUynI9eni8Ow2RRm4aiifq0mjIM1lu1WtcYpyxnJ31D6cTkG6w1+KTomQglwVFmx07VCU/ma1rKcug4IMeXWO3keK8vTB+a0bzaQgI0UHQ3qpiIL0LUqSa0hRbt6XvlfUZ1GQe4UdfZXPFOWJ1hpTjYspyIvAVvIMsynI27eby9p9ijL6n3GNhIJMmPOCmgRFOfKyJvWrcijI7pXGfJeTokxOYct8lKI0PA06F+RSCnLAJoi4BylKk9z3u3hOUZqvS5TLolwK0mo4M3naKEq7uCXk9VOU/ZGfw4kPitKoX3q1VMsoyDGRXDHloigng8daa4yi/AOXsFq+AQAAAACAAABwLwAALSkAAA==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AQAAAACAAABwLwAA4yEAAA==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AQAAAACAAADoSgAAcA8AAA==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AgAAAACAAADAPQAATRQAAO4JAAA=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AQAAAACAAABwLwAA+wcAAA==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eJzj5BwFo2AUjIJRMPwBAGORNV8=
26
+ </AppendedData>
27
+ </VTKFile>
CylinderKnMa/Kn0p30/simulation0608_Kn0p30Ma2p7/Surf.pvd ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ <?xml version="1.0"?>
2
+ <VTKFile type="Collection" version="0.1"
3
+ byte_order="LittleEndian"
4
+ compressor="vtkZLibDataCompressor">
5
+ <Collection>
6
+ <DataSet timestep="300000" group="" part="0"
7
+ file="Surf/Surf_300000.vtu"/>
8
+ </Collection>
9
+ </VTKFile>
CylinderKnMa/Kn0p30/simulation0608_Kn0p30Ma2p7/config.txt ADDED
@@ -0,0 +1,78 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ variable BZ equal 1.380649E-23
2
+ variable PI equal 3.1415926536
3
+ variable molecular_mass equal 6.63E-26
4
+ variable molecular_diameter equal 4.17E-10
5
+ variable gamma equal 1.666666667
6
+ variable R equal ${BZ}/${molecular_mass}
7
+ variable L equal 1.0
8
+ variable xmin equal -5.0
9
+ variable xmax equal 6.0
10
+ variable ymin equal -5.0
11
+ variable ymax equal 5.0
12
+ variable Kn equal 0.3
13
+ variable Ma equal 2.7
14
+ variable To equal 273.0
15
+ variable Tb equal 273.0
16
+ variable theta equal 0.0
17
+ variable mfp equal ${Kn}*${L}
18
+ variable cpmfp equal 4
19
+ variable nden equal 1.0/sqrt(2.0)/${PI}/${molecular_diameter}/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
20
+ variable sos equal sqrt(${gamma}*${R}*${To})
21
+ variable vo equal ${Ma}*${sos}
22
+ variable vx equal ${vo}*cos(${theta}*2*PI/360)
23
+ variable vy equal ${vo}*sin(${theta}*2*PI/360)
24
+ variable ppc equal 30
25
+ variable xncells equal (${xmax}-${xmin})/${mfp}*${cpmfp}
26
+ variable yncells equal (${ymax}-${ymin})/${mfp}*${cpmfp}
27
+ variable Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
28
+ variable tstep equal (-${xmin}+${xmax})/${vx}/${xncells}/10/4
29
+ variable nave equal 10000
30
+ variable noutput equal 300000
31
+ clear
32
+ shell mkdir output
33
+ shell mkdir grid
34
+ shell mkdir surf
35
+ seed 7
36
+ dimension 2
37
+ global nrho ${nden}
38
+ global fnum ${Fnum}
39
+ timestep ${tstep}
40
+ global gridcut 1.0 particle/reorder 100 comm/sort yes
41
+ region 1 cylinder z 0.0 0.0 3.50 -0.5 0.5
42
+ region 2 cylinder z 0.0 0.0 2.00 -0.5 0.5
43
+ region 3 cylinder z 0.0 0.0 0.80 -0.5 0.5
44
+ boundary o o p
45
+ create_box ${xmin} ${xmax} ${ymin} ${ymax} -0.5 0.5
46
+ create_grid ${xncells} ${yncells} 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
47
+ balance_grid rcb cell
48
+ species gas.species Ar
49
+ mixture air Ar frac 1.0
50
+ mixture air Ar vstream ${vx} ${vy} 0.0 temp ${To}
51
+ collide vss air gas.vhs
52
+ collide_modify vremax 100 yes remain no nearcp yes 10
53
+ read_surf cylinder.surf
54
+ surf_collide 1 diffuse 273.0 1.0
55
+ surf_modify all collide 1
56
+ fix in emit/face air xlo ylo yhi
57
+ balance_grid rcb cell
58
+ create_particles air n 0
59
+ stats 10000
60
+ stats_style step cpu np nattempt ncoll nscoll npave nscollave
61
+ run 200000
62
+ compute 1 grid all air n nrho massrho u v w
63
+ compute 2 grid all air trot
64
+ compute 3 tvib/grid all air
65
+ compute 4 thermal/grid all air press temp
66
+ fix 1 ave/grid all 1 ${nave} ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
67
+ dump 1 grid all ${noutput} output/grid.*.dat id xc yc f_1[*]
68
+ dump_modify 1 format float %12.5g
69
+ compute 5 surf all air n press px py shx shy fx fy etot erot evib
70
+ fix 2 ave/surf all 1 ${nave} ${nave} c_5[*] ave running
71
+ dump 2 surf all ${noutput} output/surf.*.dat id v1x v1y v2x v2y f_2[*]
72
+ dump_modify 2 format float %12.5g
73
+ compute 6 lambda/grid f_1[2] f_1[8] Ar kx
74
+ dump 3 grid all ${noutput} output/lambdakn.*.dat id xc yc c_6[*]
75
+ dump_modify 3 format float %12.5g
76
+ run 100000
77
+ write_grid grid/final-grid.dat
78
+ write_surf surf/geom.surf
CylinderKnMa/Kn0p30/simulation0608_Kn0p30Ma2p7/cylinder.surf ADDED
@@ -0,0 +1,410 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ surf file from Pointwise
2
+
3
+ 200 points
4
+ 200 lines
5
+
6
+ Points
7
+
8
+ 1 0.5 0.0
9
+ 2 0.499753280182866E+000 -0.157053795390643E-001
10
+ 3 0.499013364214136E+000 -0.313952597646568E-001
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