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  1. .gitattributes +3 -0
  2. CylinderKnMa/Kn0p26/simulation0515_Kn0p26Ma3p4/output/grid.300000.dat +3 -0
  3. CylinderKnMa/Kn0p26/simulation0516_Kn0p26Ma3p5/output/grid.300000.dat +3 -0
  4. CylinderKnMa/Kn0p26/simulation0517_Kn0p26Ma3p6/output/grid.300000.dat +3 -0
  5. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/Grid.pvd +9 -0
  6. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/Lambda.pvd +9 -0
  7. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/Lambda/Lambda_0_300000.vtu +0 -0
  8. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/Lambda/Lambda_1_300000.vtu +0 -0
  9. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/Lambda/Lambda_2_300000.vtu +0 -0
  10. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/Lambda/Lambda_300000.pvtu +21 -0
  11. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/Lambda/Lambda_3_300000.vtu +27 -0
  12. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/Surf.pvd +9 -0
  13. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/config.txt +78 -0
  14. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/cylinder.surf +410 -0
  15. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/gas.species +14 -0
  16. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/gas.vhs +9 -0
  17. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/grid/Grid_0_300000.vtu +0 -0
  18. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/grid/Grid_1_300000.vtu +0 -0
  19. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/grid/Grid_2_300000.vtu +0 -0
  20. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/grid/Grid_300000.pvtu +29 -0
  21. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/grid/Grid_3_300000.vtu +0 -0
  22. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/grid/final-grid.dat +0 -0
  23. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/log.sparta +319 -0
  24. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/mir.txt +3 -0
  25. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/output/lambdakn.300000.dat +0 -0
  26. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/output/surf.300000.dat +209 -0
  27. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/runmpirun128.sh +18 -0
  28. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/runmpirun64.sh +18 -0
  29. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/slurm-28429282.out +205 -0
  30. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/surf/Surf_300000.vtu +38 -0
  31. CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/surf/geom.surf +610 -0
  32. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/Grid.pvd +9 -0
  33. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/Lambda.pvd +9 -0
  34. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/Lambda/Lambda_0_300000.vtu +0 -0
  35. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/Lambda/Lambda_1_300000.vtu +0 -0
  36. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/Lambda/Lambda_2_300000.vtu +0 -0
  37. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/Lambda/Lambda_300000.pvtu +21 -0
  38. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/Lambda/Lambda_3_300000.vtu +27 -0
  39. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/Surf.pvd +9 -0
  40. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/config.txt +78 -0
  41. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/cylinder.surf +410 -0
  42. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/gas.species +14 -0
  43. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/gas.vhs +9 -0
  44. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/grid/Grid_0_300000.vtu +0 -0
  45. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/grid/Grid_1_300000.vtu +0 -0
  46. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/grid/Grid_2_300000.vtu +0 -0
  47. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/grid/Grid_300000.pvtu +29 -0
  48. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/grid/Grid_3_300000.vtu +0 -0
  49. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/grid/final-grid.dat +0 -0
  50. CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/log.sparta +319 -0
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AQAAAACAAAAoUwAAWwIAAA==eJzt3N1LU3Ecx3E9x7knt9kSqbQWMkMYBRkI3ZStsMBKTYgeLsJQepqZDCFmBF5IYEWjsQZZIdkDwipbQoliYRSMIEgEUTMn60nEspGm6ezpF+d3Vxdy3PnW59y8Lt5/wfmdz+/Y173v9bvicu2/nX72Ifi4k2tHl7VbakeKHlyBctuye7y1TxcvWf5uuunTDi66vN3dMLn67Soot5lVwkVNPfeVoK2zhLnoc+tCu8qc8hDOlz63yZVjEyQLlqUe3ubkov+5O3vMkQ0FcL7V+NP3lLZxp0zD9++IouT/3pcG36y/NijAGBm4/PHm03xR8ohtwjfg4f7r/dzriKWrAsZaa+vMqc/93Jd54nG9NUGSeo/79UCl6O3WHsxwcLfvT961toWr9F6ZZgitdEOlqR5L3VI4w50sDl+v36SSjHUP5yx5tHc5VKp3h4a9gTPcQxVjtcFurtz9bNaooaMZKt2M6ERVKD1Rsr8uWvallDvXPrvx6+hILqSiZ1HCTuMt7tYburzMce7f+rF96ueLX0BqDrlSbm8uUUPinnb8/EAGqRv98fbfU6OBxD3aGN+uMmshcUMdxktrrkLqFvWlnSjJ1kHisr0bpC7bc+khcdmeCVKX7XySIHHZLsYAicv2JZC6bL9hhMRluwlIXbZjMEHisr0BpG75k9lAdXYyJO6KYlXjeRek7mBI72nqhNRl92cXQOKyc1ZIXXYPGFKXnZdD6t6rjjQX2syQuA7tVMMBJ6Su1ffNfbINUnfAmljjFRdC4l4IJFX68yF12XdISF32XwBI3e9CyOnSAQAAAACAAAAoUwAAFUIAAA==eJxdXHdcje//RlklK6KEEJWsUlnlaiFkplJkhKRERihRRmd09jnPWc1TdsgqI8kW2aPskTRoiZSR/O7nfDqd3+v7j+fljM459/0e13W9r/u5+HXP9yMrpLiCAzOoS1LUBZewsn9SYJQ+PNd+phRb+lhanWwjQ8WcfoWfnWXYH9bELmBIEdul/6TDN6QYkVoaGb5VhhuD+nn0SZRB1admcd/PUkzuYD0720iGQf7Wr0zLZfiX+TDph5UcCfqLB4ROlSFaaen6ZYsMV4vb9ziyRo63ZzIfb1TJUXZCeMH2sAxZTlHXd3ySgVc1467HJTkOFgrP5z+RY/XSSGHKYDm8f47N9dsjx8Ax3ZTfBikwsd15v9yFCpRzLvVZmiVH/4K5vb0+y+GcljK5XYwCzvNenjx4WgH3xmOhWaYK+L06cuHNMgWm+ew05vZQwrTDd9/bi5WYYnBw+U+WAkEzfaacv6NAxrIF8y1USny1vT7V77ISMau31zP+KFB48r1h5QIl2Nk/e7UpUWLoINHZOosEOLnvm8RKVqKcJ7mWm69EzqzzvmXHExB6Yaxhl/IEJNmOe8+qUWJISlXQVCTAfKXZw1HvE9C7zOmB3fJEtG3yynB/mQiKfvewJFSwouXz5UkoHDTuusHPJCR/9zLtuCQZm4oOmUpuJqN38bB9BWNScKvpzSMqOQWCeSmRE6pS4PP1dfcS+1Ss+jSiag0zFc1Kl+hl+an4U9nb6E03FXRNXaUJTiq4mrvxj69WYUlD5eytKSocu3moTd+HKkzxePsg7xt5/suWBmnHNFy88PN1ilkaVr3LqJw7Kw0d9oTWVMSkIbNOWZV6KA3bZGZDVNfSsOGf6POjz2mYkT0nf0WHdIxJ231df3A6Yr9/vOE7KR1teE8OxExPx6PkZf8i1qXjdocnNw9K0xFZPpeRoUjHTq+FR1Tp6TjaOb1GR5iO0XbP1+w/kA7m4WupxffTMeWb1HlGVTr+1qfaozkd43PNBttXp+NH4/xtj8jjBTeO7+5bkY5UUSfespJ01AUZvPMtTcfKzC4ZBrMphOlsVc2OpGC6rGzST7YE78SmJ4/ekeDXq7Ez2z2jMHSz/IZfDynubU9ac61Bgnk2D97vdaXg3nRdNmCWFC+mPNYZuEeK04WlVKyCwouY5ESHEgqGX0PNO1+TIibX97jnTymqRl+06KYvBe/Z9uGHnKS4dfXAigdjZZjh/rOPywoZcoesyP4VI4XeTEfV2gIp5hnl5RUdkCHG9hbz5V0ZmO8+Fjt1lKH3BPc3STNk0Hu+L9xJT46mw4y/KQvl6Dn2j+PUSBmSn78YmnFOBsfLli4xaXJIODYn+SVy6GT3dfT8o827WmFgrLuhAsmG24MHWisgz1zWr26lHD7WhjuPpMpR0vfOgLQgBU4dPG1Zla7Ag/mnk/aSfOuxPjnmYpUcRf05YfMfK1B9Vv9+hIkSc+cva+tprAAJyqYxrgoczj/bZfxMJb63H2m+bLMSh+d52B7dqsC9KdEWQZcU+HHxpP2iSCUc2ttO4rxTwstJGVM/KwENUY352wsTMLBrz/Rol0TEjI7reD8zEc49G6rNBydhaIddUjdOEtZOzjToXZKEBx9vXus+IRnblkr1pTHJSPt2olRamQyILKY/90xB906bh4VlpGB9Q8eCsD8pkD5NEW8KTAW3B9v1bk4qTrS/NI7RRoXs/ftM7w1TYdyGjZfd5qmwslR+ta9IBc44W0HTVRWOrHaxrC1RYUbWp7qsJhV4ltUGeWPScOKzi4uVfxqal3240BiehpIN80YOjk8Dc85E0bKMNJhwDp6RXE3D5IepDhlP06BOH5IPq2NUb87WpkFH0m9KkUk66psxWzEmHfK2q638ZqfD5fuErReXpKO2v/2wG4vTse5N4M51wem49KfkUsiqdGzL2nDDPzodW23ubz4hScd59DEwFqRj2Lj4Y/ZUOi6YvJTKROT1G+YrGsdLkPSr0NRMIcEVapeOf44YVI8+sVM/i1G1z8t38l0JvrlOdNxbJ4FxvkdDJ3sJJrb/9fJ2hAS7zJwZ/P4UAkkR7DmdQvTjAaP3X5dgsq73Pl8dCouqGvxWHaTgn2Rzr/MrCkKbrSMHDaRw9vUokqkUCiMXNL0n+bMr8jbVzUUKelWU2RTkd8IdU9tKcXun0UxRtBSHfZYG9D4sxda0C7OHjJRifaDH7GHrpFj2adWsEV+l+PzksrnUSobVXxs5L8VSVG6c4exJ8sti7DufqDAZLkZXXo/aJ0PSu5t/NvyRolQpv14zSQbpKtaKgDcyrJs9VMe5txwdXkw7lBktwzB1gMuwtWjdxUeL5WgcqOyanCKHmYVn3/sFMqz52P/DdH05Tq8Y0v1EpRznYlYdmG6lwHObzPPjh8sRl3VLZehK8o5EqX5nBSr2PnKRhyvgck5uN7VSgU4+hXdr7ZQYRKpRYIISO3nmLufbJSC6Wjm0bUgCJqzU+Rz4NAGdFh7dMssjEWc6+u8adDQRuqVndwh+JyLvQNLohiVJ2J6a4apzKgmuNYM9541KRlBvB53FwmS4h7y6afc0GU7Wa26O65UCustYbU7BnEqHw3+LUiAbQjeSVLx/Z18xc30qIqkZ21xPpOK1ofnZix1VGF7yfvXi8SpsaerTqd1KFUb9G/S3IUIFOsuaOCp4z8steHVQhXNTlAa2d1QI7bY9LbZahYlmnf9s6ZmGJ/nRzqqxadjYy0wvyDMNH1ac/LggNA1Baw6VbdyThpVl7eT5CWlwvNpc+SYrDQ2R3G/37qZhh/+UmOCyNHS9WNt3wJ80/JE+YK7unA7XyuK77j3SUfhgTPaBrunYtGpuWDjpEwlL77fdPSEd1MySPkuma65i0FEzVCjGK98B+w/dFqFq3vkBcZUiTLq25ionT4zjvxeH3WwWI1c6dOLdEWKYzHvVL3q5GD9DT091cpdAPCi/aOxeCXr2XNMvJl0M/aeNJrtLxPC7orvu7X0J5u+ShH3oSqEoI8DwiYkEdkE9f+yeI4Hcq11gz1EUTq236FG8lMJSdUJIUNI85GnaUwl+D//1IkBFYfQabtG8Qgq55Vc27u1C4cfr57s2TaVw6Xr1o5N9pfBrOnhyPsmHYcWuA67yKFQYRoo336cwgE73+VLkvSy7Vb9Xiq55Y5TDyevFzntmJU+T4lxCxK3Gm1KE1np5B5vJ0NxlfdGHHVLs++I7cWCKFGHePV929JOhZlDx9pg95Plall7hfSnadbmbul5fBqM5Tk8+nJXBg8kcs9NEjhPyg53Co+S41tjcobpQjog746eenqbAkNGhgbtOKFDyronB7qDE9aBY/dOrlFiTYfFdkKeEec2p+jT9BPT5vsnNa4sWt4zlzF3bflYiVhj0uXCIxHOjj/mww8WJiO7ikxQyMgnDJizzlRxKQqL/2aI+nUn8Zv/+kuGcDJJkfaoYydjopXO//E0yyJsWLRyXgj++PgnU7hT8c74Q9n5fCmINWN19H6Sgr/PPuelDSTwfMGAe2JWKnJEi/QcfUnHacMlur4Eq1Dgnf6uYqkJw5Ydl6wNVUMNEpgrvBK9Hpx5T4XaXBbcuE1yDtr2GzCxTYSf3QmjnXyps/THcdiLBNWvv+yz5hjQcSd8mzSb4ZmDuljXXl6dhsUihYqxPw3OjFHk8jzwfJ75zJDkNcfekLtmkzvcl2VTxIg3zPN+1Gfs+DbakKn76mgbdiIJ9/ZaLcGyS0ev96SJEmp32MKwV4uCF3tdCRohQ/WzxujHPRFj/TI9EohjBVTMdBqwVYR3Htt9KMbnOC9rjaSvG01EHlTURYtz0nRS/iby+wSp/JcFY8B61oDk7V4zRfeqSFT/EmDf6p53FaDEW3JZGGe0VQ8LfOCaxDYn3F0l7VrtKMPW+7538GjEW5te5HeghQaeSQxvW75SgQ/fJVDDBP70WuTztaS1Bdfd/Jw9Mk2DRsOt10R0o6FR3tergQYGXffmMU5QEESckv09nSTDw8rnPD3dSiLpRcSEuk4JolyMpyRIEcHdFmILC1rxUk9FvKUin3qv6TuJZ7mAq60Beb3B43L6yoxTU6WkrhVFD1vWlEi1uerXheu3BRTK8ZuaWfsmXYeHdZOWy8XKcLIgruCyT4+qhCZEiUn+x7nL06UCC3zfRnVsBwVFRwBpjJR5cHZs2PVAJT9aF/SEXlcgc8dgvqEcCjI80Lpi9PQHzZk0vKq5IwOoVQ8v8pifixyXGh/PcRBg1OdzYdj8RT3+4P48bmAR1mQ5NAp0Fv3KSkPm8XqXqlQwzt/yuwzckQ5ypjD5zPxlnqqYv29Q1BfEDV9T4u6ZADaO3pYCuTvPOp0BBp1ufVDideyTttCAVs0bdujKRnwq9H/U9fl5PhVT55PeidipcId2uzEzVko/a+hyd2Fw1LV6FVF2H8g9KFaznNcg25qnw4YfyzORSFdq+GbFkRJc00M8+Mk9D2OG+5etd0zDs6OA3KxekgXfmc6cPQSQ+exySrI1IA7/sdsFoUq//iRccVOwR4lHR1avvbgjhN+d4Xs5wIUbec510yE+IXsO4Qav+CNFxu6HbRltSZ3lZC97xhTjkp3o76KYQN1xcqdHBIjxul3U8KFmE6CJ7/671QtT/fbbt8zAR4szPRDFfi0CCq2TNLxGeFdIAUgS3hbyhx3gkfkkxu28qxnZ1gIpxwjwys/a6CDtOB56f2EYMt0/1P6Lvi1GZ4TyyQzcJTM3df+02EmN8Q9UFz1niVpzT/rd7inkAwS2n8nbd4RF887v9xeWvxci2LZb/jpQgsuLiIr90Es87IrxVRhKU1myKziLvO6dI7ZdwWoIbnT0PRfSjcHGag+/9TRTO1VkM71dE4XSi8d/g8aRek27ieorg/R6s5z9IPQ19EsZeHC7D1JrPX/g3ZZimW/LhiY0ciQXpJznpcuiKpiRs66jAXPsoe+c1Cjw+tWfG4nwFfvW4HGjQR4lifcmR3fOUmJ7q83ggwQlPrwhCXtQqMfZju0eWAQm48PfbnfjiBFxtp7ANd04EzbIjSHzaP7M0VxYm4mufM0OPElw87dNFKmdlEio3vA9JPp+EHNvDDuN7JGMar7ONfEEykvbx+UdFybhw2KjHzU/JYDq06dd9UAocBj5nxG/Q1tUtfSXNS/RSEbeYRrypoLvtt8Wp6H7q6rXpCamIGWsTwCpMRYdpd45u6qJCka9v+xAbVUucqDC/u2PepVBVC95XIbI06rVnHKnHQ84NeytT4caQum+bM1WIouFgoaolTlR43UvACemRhii7QsmvaQJsWx569ptYAJfhN/m30vhgvp91rqq7oCU/hDAcGek4EkLMteu2TLRUANEO4aqrNwRY7UYzWyEM6PJ+Xog9czZ9G2woBAEtPZqnCEGSwPjWWyHGh8R93m4gwoDQqR0ucMjreh/y1z8jxMM1RsFbPUQ4X8ZvloeKsH2fjyLvuRAElLt+1hchJSDvx/JLIjwpvV/sXy2Cmr6R+NaXe7/oEi6C3asM89PdxKhTvYxYP0WMoXTYp4lQHHnkheK5qAW/i/GDpqtPtHgkcYsayLfihasOH++sCyK4oe7R1nOnKVwb/eP7wcFS7HnP6HsiUgqznc3bv76SotPRU3uzbWTok9pumSPp9/u2XNb7+laGgTmqvFWz5dh2gVV745gcNIh4Rupk2QPPMUmhClz4Yzpw5AMF+vucLx1ipUTbPivvfotQwtD9bUezbCWO/6qTG/1QQl2+FyTAfruqd9/TCXhIw7NvCdBRE4dEWBie0wtUJUK8uNntd3UiJvlYOT2dmYSbGS6K15eSUFZRtz2xOQnyBWHjro5LRk217FNsQDIqbArGjmYmw7T6fPFWgmP765x+fhEpEJt38nVOS4FZzJp5qZ9S8PVa0dpS0udvYO3nx6ReWn2552QenQpdn64jTyen4uHIzUPbkXj0demyuVpfheLTeoltR6nwryNdsVWYms2yHLZeBd9ot+IzpH76G7C3j9ihQuDoXif7c1V4UjyIm3qLh7zGccEnJvOxZOTWoN3FXDja+iT+8+VBTW+y+BDu3TGJ3UkAZfKU2gVXeFC3C2s+XIe8ON8cIMCVzwG5A88JUDd69y3PdD660G2iiwCxytoPFl2F2DD++9EJzkJs+XPM1stfgIygovnOrwR4p/vebscWISbodW8/9qAQg68uGBtqRXCB26HytwtJ/TS56P6jSIjTK/mlAT+EcLf99CKKIUQTV7+j62khLIuOfHMaIoLJ61CXWlJHc0avPmtdL0KHZ4nzvnuLYfplK8kkMV4brXK4bS7Bg34WcZECCdRt95MEj+TvmhfbUQhz8AlMkVLA8XTYfacwx3friLPTpXh+bUTWpgQpKta2TftBeJjxxrVObuNlmFTy5+N8qQxqOeYb4UuEhUxeJMeq9VblnEvavhypLpwKcN738hl+WAEmu4PVNj0lnJazO1KzlJjLb+d+latEw+Mj1qmlSnQNHc65NioBJSapd5ojE9Db67NF0tsEZG1u/5plQXDl8L97zyxKBCd+fPJKgi/J5jTL2iShyTu21mF9EsaoBYokZNP0rGMy9p0wu7/QLhkfxSWzPy9Lxoqlp+uWcZJb9jEZvTKnFUcR/rQk6WfINFIH2zY6xrw6nALWaMMpHm9TMJCwXbe+qeD8EXgyZ6eCkJ41XhGpuHx25++HpB7SVerfnVS8u3Mo/yyph7F1XUx+W6hQ9S7+hq49F7sWbf2+gMlFZuL8JdZpHEw6WFMwqi+3Rb/g4sjsjqdT/HnYuif4ePAmLgzaeL85f5OL+xEma47k8lrwBB839M5Fmw/loTr5sc9QEQ8dz3QeMyKGD0/7M7J2T/j49TrF7NRbHiQ3xBsbJ/Bx61r3CTucBHBQCyMCFFeGBoTs5UMtA5XxUTXn4yaLFwIcJ9EYM1OIgSlDb3c6LEQOw9hkjq4IRZy0pGBfEe4IV1QaXxOhrX322uMETza9O4g/IjF6H+2wfF2jGLW3dl9TeUow7t+JiRsJD/I4stei/jfhTyuPpz1bQuHBIb73jIcUHjuPSJxgLsXXP+NGzyZ8f1DbfXcTr0sx7aj/k3ldZehC9VrYxkuG4HvmX9qnylBAywM/ZLjATTQJnizH67/Dr2xNlGPOwF1oapJjRF3saStfBRyOHRmhd1GBmxO+VJw3UWLaBMWs2OVKnLi3KKJ/hhKx3elfoMT6EZZdCuwS0Hwh+PY2KgFxQwfMdShNwL3hazucN0vEtuEfUsrnJOLJsbUDv8kS8eacv8Wo/ESE9MwdxNNLgs2pX+cdFiSh3qhb7YSTSTg8vmuuf00SYkItZrgOTgbdfQZO0da1vcmBhWb3kjHk8k6WgVEKzIc6dTk+OwXWje3OuIpSUOhMCzwpeH7w1CWj+hTkqeJ0uYSvFy9/Na7RNxVnp60/L3gTj2txjrv7WXHQy7/o74pB8ZD57Q20Do7H1dJTQSuFHGz7atjxUS0HlskeYwrvxeNewMzbHZ04uDBB2qWNNxcf750oa3OViwjfLVc/JHDwZds951VNHNzZQgNyHkz1Uo/v2cPDMppmR3GxxeiSV9tGLmyqE/8czeeBSYfDBj56DAgzPWWk7bNfTvguDCf9V7a0wwr3dCE22nQo2tAkRPZfa+tZM0QQP7ROidovAvnxs580icAMUxMZuIza8GnXbTHOKN3m6w+VoK868CUQPW47/cU5Uo9W/nM06EthuzoxKQTMz36r+56CkWGiINRNisC9X4NLWFK8pb75d34rxeurrB3tLGVQ06ONMiQusCtqfiDDyXE25haGWn20bOE7724KOV4Mv/oxvEyORQGzO7Oma/XNS59ivm2tVWCbpV4921EJ+9rxU6ZtVLboF0qce9zmXbvOCaDV6C++CTj4KJIXkJ6AW5y4QRt/J2CGWvhJxKeGuxbWjER0fXVUwMxLhOBglO2/CvJ47j+B4bAkXHff08sxLgmn3jo5N5YmQb0cJH5qwyfZjZhKeMTdGI/LO5KxLkT1K+liMk5fCEkZ8i0ZdwZ2cWwckNLSdwgvNt/6wj0oBe5j52RaCdl4P3vwtcud4hGmHnywoG5f/dmo5NZyZnrHw87jqtdtaTwOba3b+WYnG9NoGlbKbplDxCM5L+WE3ygORrqZVn50iMfk6q/PV/LisUZNlDiQTlneZ0o3LmaeHJ/0q5CL99yEE2IBD8lJaedLZvExoOlG2/o/fJiwH3VyyBTgya0eoXWkj2XpGrftTXhC3HZ6UkB4ROeDCX4zCf4/P+7ycsKDazo6jon9KsLY+FKZj5sYJQcSb5idFCMs/1nAy/YSHH+7Je3CbAmuXdlUWyyWYP33W9OXvyPXog87vEdR+E8eITgpTf/LojIK0QZXNxiPkyL666sDBkwp8nLb/Kl4JkW3hIBGH3MZAtTASquTv62OWhPfRo5IP0P96Cly3CwI/vQ9Xg7n1yFFxu/lEJ3Pf8IcpcC5wJiXTpEKtHv27HR2ngJJ7M+ux5oVsMv129PorcSOrdYzN8uUqDkxoPF4kRJqWjcwAUf9VkcvXZwAg+adNosIfnq0glq9pGsiltAwcl4ikunl25mIP7RcdToR3u9/Ten8OxHXCAlL8kyCfcJiAsGSMGMHPaFKQnPKwkMFjUnYUbH7t2xCMh7cfN+gy04GAW/GzQRH2ctOOtyazYJj8Ja3i0QsJES9HTymiImMuiezAruzkDOq6UP0Fxb27rnEHjSBjaZ5z5TbPVh4tHM/q8tRFrpZJm6M28rGtse+wqAR8SAgI7YzqUO1A1R/NgZxWnR4Lsb+fhxe8IaLrr9Wd6jbxYPn+phRJrZ8HOrY/kBwKR/3qaL3PWMFeL9/DYHoQtzsp5zWvEyIfqv+BgXmCMF79PBZpZEI91bcv222VYTTr5ouf7ktwgyDsDYOZmIYBo468mqdGEX5bu/fFohRMCdjx8QBEizM0N+mXK7Fy7ddN3cy7Uyhp81QccUqCq5nKknnpZBkr258uP3g9YsqDyl0j3lfHLZfipw9L5Su5VKMyL07JdpCBlY9LczJ8PjE8dTmMzJcXNr+57rvMgz5fptknBx2ycld+GJt3dDMSzTzRY1O1vGrkcfcJgW6b1vWpthNiVKLwsn9Bcr/xhB5SqRW5Hzd812JR9VDeY8nJuCN9XefAGYCPH6+e6+6lIDYC0YjnV8n4Nj8qIPyvokw7XSn3bDwRHyf+FFosD8R5dc8Roc0kvi4Zhj1d3oSfgQ9i5ZGJ8H7wMjMOmUS8NH3WPFgJoTpD964XWPimC9dUVkwnrhlLruShfnuDO9cERvhSzs+MJ4Xj8iCkJyUiniYD18wrk8MpxWvTHW3idS5x8Ue5pr3b5by8HXN7CUr2/FxL/F69qvrfNj1TOuxdrEAwSePfD/8UwBro8tWxxYIMYs5++HFUwS/0mNJ0gcEDvyFnDkiHPAMCdY5KQL9b9seYsy2OiF9FCDG3oRB3r1OiBF1YASpOGIwSn51OTyO7OutBv9H2yWwGrTQe/RlCb7TYW1AgXOYPXkg2V/zJSkPeh+gsOhhd75fA4WoeNPB62ZLsYRue4lS/F37KceqVIonpn6/Vo2RYdxvRbdOm2V4+Xj8s9prZJ/F+U+/6cjxOKK4Y7mXHNY/w1h1CXLsFsntT12Rw/3G/SMr2yiQHrOb09tegcqJC7zEEYQ30e2W4Iydn4r2v+6pxKSj7RsUHkqY1XpbG+5UQjU+duf7y0p0/jeYQJiElnlNAnyKHG6WkD7hWexCIjMBa6t6Fi7SSUQAx0gVZp+Ip6NpwJqI+rCr8wOuJEI9Tp3OwMLx07/nZzFa6hIT+o/OJkTcYmK+WkhioabDY//HZSw82LDOsEbKRm+1IBePfQVjyFPx+Dov5tK13RyMC7u1hjVcu6+qI89HtlvBwytaXh7KxxZ7OhL4iLh9P1xnsgBW98s29L0nwNNfX0e4TCV8edfE0sc8IULeJL4f81iI31WxlfHGIlTlrdhWtVoEUzVBF6Gj+XLSgsS440Mr5GKol/GwGMIXNaRyiHFh/PBx82ZKkD+CVngkaE6uftyvRoL3h3sfrLWn8K/sJvvEFgrnN9+LvJVH4fnoFwavjaS4IT2zdeoiKf4bcEtb9ew7+TXthraXIfLkzXWp3jLYTr635GyyDM0ePYx96mSQNw894mkjx1A/5r6jm+W4P/DpK7uzchiLLLOO/ZHjUzD/WJOtAsub7Grur1fgiZ1lQseTCqSQbPctV2DP3Hf5j02VyE89vHahlxIdz84gnU+JDLd1jH5flXComEkqXgKKuF029lmegN+xzqufHExAG68OXYM/J7T4Hxhw3MNo7jyKgU/Tn9hL1jPQMIzxaeVHBoJdaaTORENM1++l7Vl4u7gpbI6QBdHy3utXDmBj/4bD7+OOs/HFr3vBn/HxaE7a3bT2UzwK4ou/tGFxcPOTwZjv/bmYfXbXpLmHuBh3a/a2zrN5GFjUL/taPQ9qGhXPR8dIJ0WvgQJ0xIY2f/ME0NenO64QtXeV1Xo7hNjrwTBd9FCIBdzv49K6i8AQLXlWQ3D/d6HVwN0ZIhh8GClU/RRBRo9p/p/+bKd6RyMAMMdeTtDRlWDKyPvHu/tIIKFlRJUEhimPKud8lMC3OkFYRPCcvSu8Tiyi8DqubCIvi/qvXDVSuLTJ0s3bUwq1bMCVol/PxoW/H0mhhnNGMhS2z713cp4MWf7LBGxKBtfsq+yK5zLo6+2x5Q2T44acPXj/OjnWLin0G3lSjodx9A+Qg2WomF3poNXdLrUNytuTqkD7+IU3Tl5XgOFjsdqyRoE5ZNV2mCmh/vorlJCX9GalUEr02pp7Z/1jJeisvNuFg5WOM4Y6pjHh+Xu7lWMwA3H6kbrj5jPQLnXg1E4CBhppmaCZgUFmS13bM5no/Nfz0roeLKztOKShs4oFMxq+jWJjsak08fABdgsfiW/F7TAuuV61ioO2o8eupX5wQILHR28XF4vVggUPA8IDbIYQPmjx+kr/w158dDCM6RVBeFxTm/0OGzYK8GL3u35ubYS4Zuuw+QzB5Z4L1huslQqx+2YxYQCE39lErUuzFmGHerAuavFniDDwVb7ezn5i8BePO5DrI4Zy9dDjPxliBOaWeScXihEw9ldQYj8JqP2hw96vlWDyoEnrV5yRYGvv+TvnV0tg7nHgxePx2vzttuRiVvFJCu7GGYHD/1J4eIk5kz+J4K9nVoJ1e6W4/sNyseCaFHGWSx+5tpNhA3/ixMypJG+zczdeCpNh+/QVWfwMra6wXU3E5DBUAxM52lkzjV4+kOOLOY3gFRBXHqSez1Dgxdf6GX4MBQq/HD3aLluBXV8Gutt+UmAje0g3dyMlwr/o3JnEFLf4AvioS12nujKJjfyc87wOXxlQy3cujJZ4Y6B5VeOn5WkM7LpLAxQmkmOHXWMcYqIi7azBPjMWqlQ9n9tkshCxkfGRP46NczVlR7peYLfi5yE2Lgbvr8XDeGDQ6NcEPzfR8sFDDvxH9Uv+7sWF6+SKl8d+c7Hke8aDEIKfCqMuP+b34yMteMCVwZf5eLVx1E3vVQJE8Nu+rHwrQEqNY13SSCFco5flx+wSYuxstwXFJG9/xNKDdRHeRs3qpkd4V/aHKUtdEkTwW7fG3rxGhID4owV51iRfL91YeHCpGHdzvZ+nJWh1cfX4or8EXVM3D766QIKzq674zZBJMH7VurwebyVoy5x7IKgbBWOzx7rxCymM0qGdIBROtos+F1lCwcT406hrvaTYM9rzoN5UKVJ2zu1jRZF87uLb0fmN1vf1dM74i9meMjgGqWybd8hgvmxz5KbzMljb0hNlGeYe6blqvZUcYZkJ5axoORYcXjeqmdTrbheM110plyO4E905FNi3+fNScQGFRL+Zbdf8k2D34T8kA0Rw7wve9u8clNif+HLMiIVj4wv9FXEM/Gu/u43xRAauX1x8Y2sgA5kpknfj8hjg7ttomG3HxCw18GC2+FdYED+4cvtuAgsxfc4GWY9mg3vRJcsni43motnUXndtfz21LneSrQ+pC860Y4WDP4PTRpbP50I9pvnARdTHCYucg3lI1NHdVP+TB52o4gdxIj7O0bIRqceCPrTyKADNqlPbCdFl8v07HE8hDh9ZFbpDRPZ5adSfTaTfUpe3T+N1FmHXUN9TP2eJ0P2MPOzQcRGGyqiLD+tEmBO5eciI4WIsVQM1MdQ0PVW7v+eehJ451VOC7H9tizICCN+2yHs1j/TfAb/27ConPIpW4y2HUthy+KB5ZTiF4QUH6vRPUFD/2Y8Uum/OyhjaXwo1TPKVYkxgapt4kRTmtJx/W4qQ3M2SvroyjKjN6HjPTYaZW5+/FMbIEK4mQjKYhNIOORkMR3RdvdNeDstu+tkHIwn+Krh05dhcCm1MDsz8J6bQ67/CixvLmvWU1hLYvXgWuaBJgIvVrpuSp8ajLILuqEy8nPxppC8YuOqd4vzCioGJJ00H6UQyoIaRpK9GmFUeKfRl4nljsdmgAiYu2H8+6z6KhdHxA372PcZC4I9pfTuM0OZrmVlFsPfMeOhvf1V84k48BqsBBwdq2pPDgdm5pZP9bLj4OWfc3A/JXGxSLwgPy/zWzNfL4SEnr1vHzvP4UI9DbvPRQFidtacA6nbxXAAapVeNEuJDTuDUbduF2Jrz/cams0L0XZqVr/9ZiFeiL5MuW4qwnbDQQ4QHrZQ5dV77QIQyaWXY2N4EP/W8ePbcIjFyfiQM6EWJsShh0aBjt8QYNyH6CZv03ZCrnLzddqQuqwuzBE41i44byiXIEvtEuxVLMPZN7MNuQyjcF0mXdlhB4dZ886Wd91PocSNy/K7PFHKdp+9qP0YK09O7Np9aI8W2c6fdVyulaHuwi+mjJ1p9zoF6xQmepOVLB6M7ZUw9IUPS5c5xnUj9V9NfPwoVY5Yuid1BYUXX3XyfbArpS+jApPDkdnnvOU5i7ItYYO/yjIfIbQ93lXZiw2l6TtC3+wzErBUPrLNmwKWWN6jNeAam19vGl8oYLT4cJnSbv35/v4cJq6G6R7+Ukno81X/4+mks9Hl27t7n0yz0U9k9szRnQ7qMVtrZ+BUyjbSWeJztJWzAlXgo4rbMPuPMwbWZdCfgIMCO7uhchKsNoNwWnZgH36wJD8Ku8aDH2GQw1o7sZyJN9PlQyz4TBfg1cqJfyCUB2o59f3WOqRDZC97xw/2FuBBuZq6vEKK0M638CeF2c3yMoZ4IiteX3lhMEyGBtlvGaOdHh0s7Zn7TFWPw9eHvbjuKoR7/RYqhluGzxHB+d9RnWJMYv2t8ZBUjJLAtCTvwPEiCYeN/7PqULEFp1qFPSS8kWFu9I0OP8KMwL8dRGVMotPe6f+xALIWZC/utsMilMD6v4Z64jRS06+aOvRSVgjFdFm6U4g1tzyJ8+OTRO14+T6WoXf9oyQ5H7Xz/+8KxtrcDKJxK7/B0TDQFD1qOTCD13qHg933Cr710x1/iNEpg8nOewR8nEco37knras1Fm4X9JzwhdVSTlyMRLrXozgA9lbhqy8BmC9ohyQDV+3ph2+5MqMd7O5lwTHeN2FTHRNu817kb5rOgHi+cZYH+Ve42JE/9s9qEkX39u289gerxmBcyOr1aEQ//QjF/4xgO1tJjtH0clGH/+7yuXFjk6h6aLORC+bwHc60ZD/+NJ3lIciixc+/NR4Dxgn5JLD44femJJx8EHBIGJ4DrZ/1B5X8FaNCjgbIQNxT1jfO3CXE7y4FXnS3EY8fYKTv/ClHwt+uUXZNFsLxwfZjtJhFKafnwsAgetLusXIRBwpmmkWZiHOhJA2ExHv7YMd6DJcbGudc8X18WI8P95aKCX2KUjP8acmGsBOnZ6fc3rJNg+vRubkclhAcf6S64cVeCj5lLpkztSOHgygmdD4ymsCzik8fqZRQ+5HVNGptO8qvOvXt5MYWnDSeO2VlJW1/vkvMia34nCqUrP/q4dKFa6wCNTvu4k/d3pQEZwWkOwlEOxylkJl0a+yqDQt5+G/9p3pLWucDiiP4ZVqQuVrzefSAnlvCVZfOjo10ZoFHhU0MGvNfeq2S5MaDzpLnjwqMMCN8kbF40mIn/bHxMjF9j0uu+DguHB6wJX7SIBb2GpeUH77OQNTgk/eE0Nj7S47dLbMxKOZ2QaRHf4meMx4qoaz27WXLAM3hb1Y3iYPO5ygNW7bh4/fszQndy0fm3vlNgPRdqOL6F16KT8rCKs/9txQo+Pn/tfmtOCR/3ljf2v75CgKAZles7XxFgRNDecx0HETx8UZ/qtVCIR8Nop6YQZ0Oe7826JcSen1f4/9qJoGdDTyxFMDnMjUndQHjR5m2dSg6JYD88/LTBGxEu9S1gbyH1eYWV+ITufDHUsGivGCNP2Zr8yhXD0nKKdWM7CWiR22uSBOoxQZgEarvDKQk6utGTVwnKTYKCHXtQEK30qQ2fRCFpPV2QKISEvPRfak61+hEKH3VYpjOY8ONMRY93AyjcifAqCCV9++gjerBCYXL5uuczvbR+Zk0fv/RXPfBAu5mZgXWJYqy7btlpwHt+i3+djTEpLm7/dJl4od+eUBUGHoxtGNqvGwNqW6UDAz9/1V4NlTNa/MZMHPy2Ze/T3UxEDqSdNkwYb3atUM1ktfhQWBjVf1PKKYKbOKzAbx0UbHiGPn2xRD8eryLWTwncHd+il8ej2GDNgg8rOS3+dg4yLJesCvPSzr+CbE0frnbm4XGma8GcDB78Zj03DOjDh5VLTNo0Lh/XrTZ951XwMawtvVICsF4sKza/L0DMf8ZAqGFIkBDqtnZAiFg1MRGil1+oZXYfESY8cgvrN1WEa3nJ7ntjtLgqXpiTvKNUhPqDg3vfMhIjpO/kwQfdxfA/51J9bgvZV3pbz4iRcnaqbskHMcxrTQvm9iY8lx6XTpFgBKlyDpslqAzfLK3JlOB+5nbrnoYUes7WX1Lfm/Dfy6ef7O9FYd2+trnte1Lopxb4KCwMx4ddbbX52ienJ6EwFPiZT95GOGjxWcTCYpmA9O/Ffuln7pF40PjGrCoaxLcI3gyxu9BXp5LgnO4LJ2TdZqDc1NEwwZyBI2sXevn1YqDEiDbsMaC261/Q5qteyE+jIh4T4VF9avOrmeg9yYT5O0C7r+OupQ+ebcHG5WXj1i6i2Mjut+NeR914FHYOHrx2WzxIEdI9+DQe38w/J9wZx0H+XsXMjLMkb78UrI4cwMU29UCLi0+29GSDC9r9PC+Gh39Rce0bdfgQ5k1/qgrmo2vcw6KrV/moYmfqY7wANhhnt+qQAGq7s54QvUuaZlm6CxHya9dRR8KD1HLcBdJvxX6XrlcLQbvyIvuLMNjkrUuVpxZX0ej6yglRiy9PhN0DQl6P0RPjo4AWTMUw6ns6p3CTGIMIK+6xXwyf5WOvtH8pRviOheuf6UkwyyO0y8RBBD9dfng+3IxCimvmszPkWkK78kldNQ6XiUtJvpoOM9n/wYrkMXf49fMkbzXzLI2PersNZVg9nODecZw++m7k/TdoIx8Fu2+RN70EFNR2/7OSFj+MqMV/xoXi1fyOkU4s0Ks+UUL4y4wvunY9GLB8GrzRpgMD+fV7hw6Yy0ComhAxYFzxqs8jgptct9MOEiZWF5aHWDcw4U7bCuaykP9ys274GRaCRoVHHjNmY5u+ueVOLhs5zL21fw3iYabYl18bFo96glZjH8VDYrze+pIDB3zn3MylJznwWuzdENCD2zJ35yIwKDXf8iEXL3KedfrryQPtqhv+VoujzJLm9D9K8aEeMzbxMebltpM31wkwakIN1bVIgIlbLy5JGCyEl+QDqQxC6P5bdIfPE6KcSxvttbrytkdVOecGi5CzhmbAZH3iFv7twRCBijtxIuIIyYOHuaZbyP6evmRU/66vGKRJvHH1JTy3LT0pFGOmuPz3ZFPS/6xpRE1BfczHWFtn1bZzkqecm+v1rHtr6zBZrG2nxlCtOCm43E4/i9Rr2aOAnqsJ7lLLfD5avKS2352iMLXK0NnmNAW9IM+rJqslWFwxQzcjhsTrwBEr3EieDJz1Y2XzYyZe708/1bBV21fH9Yl5bUjydiVtq17OwE61wMJA1+73Hpc0MrB3ZVvD8xFMFBjHT3r3iQm1Ld+NhYYproseHGDBQXCdMCl2y7kcNrbvvxoWVszGDMWaP74+8aihxxAZ8UhrvNW9jSkHvY37C/fu4ED/WeDXMdWclvkTF9NnRPX1J7znNj2G6ckDrSamCnnYf3hso/ArD8Gi6mjY87E2IGTvzoN8qMdB/QV4Qo9L4wVw2kEjdwEu3Ro175K9EKoFfzY7krrc3O2kT3WCludq+u63qDFWkwmu+rFC0sRaKoLhhQ9dmneKEGV8c+PMoyIEHBLJCl6L8JOmd32o1v10EOsW61lSmNSsr9vWVrs/cZ33+b2cTCE1gifTcaLgefNWLp/wFXXbIteEznSAaq+D1MZwwmfUxiyCh2bFNAwh+zuA+8IiNpDgp6E0ciBxMes732szwVVzjf9NLhG38r1yr/zhB1bHI8OaPgjHbNWVbiwqfz/qTxz2EBQlN2Yg9sncfcKVDNCup3cENzF0uaPWd2Xi1iwDu9RNTJR1Mr595i4T3nmrzV2HkPrbtC5nFZMFmyG5Tp3asuEz42F9zxVsXL31o/b3PTZCrph9fjpci4uZr9OW23zR+gEONAx+xT/CgcPE8kPjCT6e8HRvtcUKLjLrX609doML5hWR855ZPHxeeeTHzn080G795Y08bEp6vXf7Kj763yklyJqPQdLAaSVzBVCPPY4I0Oj/aPuKTsKW82NCxPxaeTM8QojQEcvDuMlCdHeykpi8EracGxC16jVqW9xyEaKzxq9QkP7I2/693zATCvSUOsqIwqzedIWjUOnFv/OxWYKazj1fv9XR9snsm/aTJX8leJZskXKmvdZn7xa+mCyh9nr3Z6Nxn65Ua7yEmQWs9bfS7quFTadjpv4URjM2pgfEUUj7aVOWSXBVGG13WiVuxZFOFpfWR1ez0UzbG1yYOJI6rveRMQykUtMNwtow8PGk3dd9JgzkzfFO27VQO7/5yXUP1u2n5Tm9D9/8sPwVE2rbkxULc9QHx1itfdu7D43M2KgPrTz07xgbu7Ywe+mYxyO7mP4ALX7SzOXVNvFTHEyZOWDO3W5c2K3eUWDjxwU9Bbd/xAUJmp/MkTw0uNIFkIfSJct8LJ9o63JnOszO8aG2bfURoP3BpzkGIYIWX5MAuZI5gjBjIQpPbJ7sSPiAU3e//eytWlwlv3mjrITsr/qYo5X2/M8Gv7j7bch6n6WPQ5L6ujrLe/pK8ngvXcH6WhPt80MIytpN8nfEfwIHPN6s+OxGHn8X4fAplbxPEx+a+qzBT3ojYq10CM85EkJHFAXVTVrYoLBte/d238j+RUTkByYuoBAzq+gwM5jUA91+zy9XSlr7wzju7g911Tz83GA3zWcnG9FLF2c8MWK24iX9nf0Cc8viWvFw/NZYi5GLGbhS8a0s/DgDswiYMO/ERKDaKMVs0aWZ6OuyYti80SyYTe0kcOCzQKvkT+tYqA6aCpPZbBw3erFi8AE21DbbbvE4QcPbHfGYbp2X9vVlPNS2KXcOxJGfunVI4WBMYpvr38o5UMuJTlyEHOh+eyifC/oUx9mvXJDFrl/rw0M2lz5YyINYdObkof587CG/LmAPH30D3plmFvKR+bJgZrOFAGrb1kYB6FOQrqUC3Bn0sWyBLemvGwQHugUIW/NG1+nZ2eVknc+4imrKe2n3SfP//8W1Bh91SOmlWvnMZRpWk6v9fwWzNT8fl+/jnif7pdEtLq40HfJyiLb+avrruJsl6f6Ep55b8nTP7vkUAv4Dnq3nyjbQ9rAgUidsNxo1ZEnQ51undfvXilrnJRr/y9G7Vm1tOjPRc25xp/lWDIzoInr6/Htcy/kZBgbTx4BWaPtrTZb94L4dmVDTukAm1DTwKhPiSWsHj+3Dwr5S527ZYayW848s0O6KcWPYGHzgpWPXPWxU0D/zExs3aRve5Hi4cZ/nZpyJRxsdl9gu/Tlw9qQdXRx8+2Kqc/o5B5nLGbcMXbj4abqQL9zFBSEFvXCLi6IFRnEBvXhYrQZ+PKjT8T3J37qspivefPQZ/s9/yQU+pF/3LonpKcBLzNHpMF0AuiuZywWt5zU0662GG38ID81Jqcj5qr3GDWMPLa2RoIvacC+Bm7phS2C7hVbKJLAbMTUglDzeddXh+CP1ktZ6vGffp8IJ5O+f235hDr8dBXXZJ5/z0MZs+yXyOY6zH4sWk9ftHPf2tFuTBDk2ascnYtSCMYXud4O6Th9JgWs9il8wi+Dq9M9VKwm/saPHiQQPNyg81jgIJKCrrnKoCDvVB1y48Hwf2ol/lwX61+iUMkCrUZsHMWCzTdFw/28cRm2knasMqO0UIdp83cictbKsHanbPy8PGb6AiRtRtLGb2XL+mYUbzs/zYpewoCAssMdVFtT02ZwNj7Vbuz3aoe2z1JUyUiHi4TrMeIL+9viW88fxrXiu33mdiIJ9HNzp7yBS6nMhocPAn9vi3+G2+FJ5SHR6pNfFj4e2s2s//j3Pw1r1gRg+QhqPtnkfxkdW6eL4owX81vUsK2ccrCLr3/7Ktg4GpO9tfGPV/9g/Cf49uicJ1dPiVk0f1dRhjW6g0X80+abhI5o6POBI3ncO4aNNJtN3h5N+qvHViLJookfBSpeepFGtcTX2SJrBFXLVxEGR19ETmeR7HPMq3T6VfJ5ziKFFI8FfTisLmKoQCiusg/0DV1ForDBoFC2SwHMc22VZqRAHcn1ct07nts5JF/wzIwiMAReaZvRjoMup30O66DBQxXJzEI7S4mENbvpvTsiAlzhifM4MJhgFl2W+mUwciLs7fG0HFro/7LlSdwELf05N33njBAv1B86hjwEbanlyCxu5/jX3dK+zUbOUFvTjEbjrREVRKOmvXhGCtZnxeJaUe1u3KR4D6HRfyIEaHidyMCLwxXLP3xycoOgDptr5gNq+pU/2N5x2oPKwnOvRy7+I1zpnUY8hCT71DmlwtiZ8YrwH61t7kgd7i67L2YO1vEOzv5rrUbMOOQ3ttbqrJh4053ZfFM355/ddgk82OtI6kq9qWzTJu+u0fZ6832J2zVZLsj/p2+kDF9o83NSt8/s/pK9uucn92mCm7Z+u1ee2pBPeQ58OaR5GQX/p0sr5JG6uMQ75FpDvX1Nl3e2JF4VuHrSCQsHsbH1whoUE4Ypg4e5DhKcf2+DQvy0Xpxu2EubPat0vtT1CjwFprTH7UScGThCWnzqRAbU9MYqBoOmxCf5nGThJqu/zBrL/agLHBD0tnipnYsaZSNMO37W60855u5tdBSzMm7nJem8hC31Wd9m024ENB1LF5Xw2+IPajG+oYiNwNq30xbf4ceKxQG0c5kB53ru7TgAHS9K6yU6lcVr8vlwEqx1TXBz2rmcGpXBR/Ty5xrGOi6jmrHnJZP3WqI1FFAjoWlzaWdsvqxi00VXLL//p0MYzbf4NvTvdcscgCvTp85gRZD+zNo4eY036Gi2PO1A4zrjhJCN8hXaznJ2qxalWWcf+5LtqdWCNDqHBtepjSSRuMpKXh8wkeX3JhB6IkLx+k5z9epRWlzhsQj9DoTm2I33Ur1WH0Pi194lo4y6Fk44ec0TkccXvSC+RngS/h83akx4pxLQBrBFPbnCwgz5u7cNq8d1o+c36H0n1eXVxeJr616OHsXbuqvHDyPt1iVhYzMCpkO5lW0YzMa28qVf+Lib8aFdGPROr7APmbA5ggS9VrB56nNXiqyP13tLilbcHG29oGVrOxrVfz07N+MyG5fNet6tGxCO2qOnnTI7WrxibNGa5nTUH9fGHBqwJJ3n6gC6kHPTYNL1wiyG3Va/R8EYNv1+xfWTFJRttnGv+r+GVb76JqPox2tf/KdhT32sChW9DF4Rvc6HQt7qOZCThE/sWrltjT0Et5xNc00U8+Xg6KIQmnzc94UzBRD0I067zwG60g5TC6W93l3E9tLxVs9+a/dTofpp81ehSmvqvwWca3ULDgx1tKm/Ona3lN3PVDVGMt4//bRzpT3B8aaVt0yEOMImeVLIQZJT2Qi+B0XLfCS1usurgYbdrMAOGZ1O5dcu1Pon/7uvCQG15r0+rhzBbfFdMSLsW/Ztwj4m6qWUi9GVhsXDk3eerWC33gdDqFBUjB7zbtEw7v8tf9eaZ83c2eizgLTGYG4/GAtq4EI+ysn6PnSoJH6LHX26c1rzT1LNl4oJem7pr8aXmqskPp10nvY6ZaHGrxl+oObfwivu0u/dP7TmGwTQ8JrhGU0/3N9OCpaT1fiDhww7qnyKv0/CQvJBV10b/kMAn5+IDRpP2/Rp8rPl+4wl7PEuurG5VP0f/v6vGb6Hpu5q6//WytOpFJy3/sdx1f8K2Ydo4lVW7vdtIPvfCxoYHwUfFrfMrK9kigog58FFvAAsmrFVjmfsJ3p1wJiCN8JpaPrew7F8caPUu15SBFTvoO1KQ/Nz/ZgdfwAA9vbj+jAG1jbQvE07dah68CmOCvgvByLskbxsFcRXdtX3W5dmONvMTWbiNseQnaeuxcZuM8xs4bNAuEEYJu8U/p9WPNXU0Qnx81CHC+9//pG/AouX/Gr7/OVnvfPkvbd/TUR+clWCUU8KXO2S9NbqBBo9o/t9LbfCVtOJhzd/VPK+Zl2niRRMfGpxjrggJGkn2QZ12ulr/iUaP0Pw9zfc+yVUPrlrjTsOLNPisq1rIpvB0Fq3UkzrLKB4SOEM7xyEkz7G7n/b7WP/J7NR8Tgz5P+HOPxOFoO+aciSWg3lxuJ5oz0Jv0yXdRSRfp/wouuLTmYG/qdejI9sycG6H4HdlbwZiUzcUO3sQXus+p2A/g4FR4/dcXnqPgZw3yw5f12Pi66ynqzsuZuInfducHCbyDV2SmIas1jrvlOidevS4dl8TJ5hnz7VlQ328LpaN0GVHdTkER2l4RrxY6PGa7ItalvqtxSFqWfm39qpZf028Zxax79bpafNBg1s06/h3lqX7lUHavqoeDwzU5vUBenxJeOkP6+RuD3tq+7RmHTX4J+DNVJ1t+tp5i0Z/0NRPtY2vjxaPaeJBoydpvq8mHjT7z/CjK662Tmv8re33iSe2JTxHTNuMfbU44ePgxs0R+WKE/SuYIZkvhF3a9MDpFzhwuCP42TuUBYMMg9nulxnIfLF0y5wBDAj39Ax61azVJTR+mMG/s388jWGA5/Z31Nr7DNz3S93oacTEuc505WS2+hfpuxzpVDAx8eEL+VpHFlgNp3a/Z7DgRqfTUxYq27AuRvVmY4FagNbyBA0u1Ohnv2hZh+CIaX6XlYpR2jmIRrdZ1fx43Jr/p/P8r66n4TWBtN31lzZeaPeg3Vct39TEiUbfmTrsw3OPntp80uyLBj9r/q+JAw1e0+Sxpi6o7Y89tHVYw280PEizv5p40bxO8/frD9NEkkJZgerVB3dt3mruG+LJNo8yvimG3kXLqA8rhFjXt/3VktccyDp+ttrIYoGtV3j/5nsG7o6kER8DJtds7qboMlr14SU9mtYPnaT1Df/nl2OgfWjSrGlttPvqv3LS+zk8JrhrDm5Pfqb1ndKntAcuZ6FhCX2DEm2+aPC+Rp/R3MdnzPf+TTfaavU0zbpp4lvD8zR9UPM6DT/5X76veV7zeP8t720cSb8MUN9ISQL67iQNXySoLrI15pdLcG0fb0jRRwnaPe899tprCbi97UlJlOAXDVc+SRCbs6tdLbleaA5InVApadXzTnc7PUJB4kZTjzX9QfM9NX4II7VRWatHafqspi5ofq8GNw1rtvxyz4lCwWFb7kWC0+hqspKsg9oWfEfcqnOb9KUd+lzMPMadOpnwy5XqA3Ran9pbd9pZzEDuZ1n/jwMZeKTMOpIzTZuvMyx6etqfYaA/TUd/MWClJjpMfEr3d+8lYWLzGcxd95oJZ+avb+2qtOun6X8aHJLm0bhJ75uEvolUgrRagj/la0jpleBBM33jFNKX6NsilUrQV+9F16lVWt2n0Oxe9RJyfevqO3juX+06an6vZh9Xqg8YSVr76Gq1MK3FJZo6qtH5/jeuNK/X4BlNXGn6ZVg4vSISDOvX7ewL8v1NriwycyG/z1J9YENbF9Qya6MWh2lwmub7aeq9RifRfO7/1neNHv00hFacyTodOJ9RdVEM3HqTvTdaiEBV6FLn0VyoZeHnLBhGP61/SfbV1PLr7MkkX8Mto8927crA16uhcgeCm9Tlw50BAmr7FrAZUPFoQzXZZ55e0lodZqt/UaNj++0bkP64vxa/q8dYJO4059omZwl6Nzlo9VCNz1qDFzS8QsMbL8r/fLIkvIL7c/a9KMJXlnQbdjPfgmrVHU50XsNzsdDyHc3/NfVAo7Nr6puGV9oM+3up1wDtfFvDOzTf/4nJntmd/t9VoxvctX7+OojUx4pZU4ZzR2o/T/N9NPVasw/KIvogrNYPIWiWhz5up+3Tmjz98uhz5Dgjbf/U8On8b5lRVxy1fFnTvy6750Y0V4tbz50N2fNmiiKd26oPu/Wj73zBbJ232u8slpo/jGvxqcdhW8K9bYs+x7XqUO+2dhH8HcHA/wG2XvifAQAAAACAAAAoUwAAqjQAAA==eJxdXGV4G1fXDDM0abhhapiZJg03zNgwMzNDw4wNNszMDBXLkq1dsWSQKdQwU5Pvnqsj632+/lHt2PJq74GZOXP2U53/vBvyJOLg5bqf/hmWiJ9bxGQsfiUBaQc1Wrr8ewLqLatQe+7+RKiJH8VPJqLjnLhPvpqJeDZ6xb2yYxOhPM4xZGSWJJT91hUTKyThUvles3asSUT1f3WdO15OxKMTOW4UnJCEna/a/Xf7RBKKfl66+FFsIprr6i38Wfxegczj6+9ISMI4+Y1ktHuarlauOkn4t/6T+YljkzDzwI2OpSono8eD44c7Nk1Gp4bfavc5lISrbc/X2/M5Ce/qHvgp9YpktJ7yOeeTa8mo1v5ollZlknHPEbV7dfdkvu5k5Bi5oHbGTA/R5U7t8z2WJGPqokHri95LxtYON/659cdDFGm8YKL974dYdeVTnlSJyciwb27OHYUfomm11hvi/A9RcUU+b+THh6Cf+q/NQ+w21fVH//UQrh/1LTvyP8LHzfpRRXo8Qov7Jbqf8D5E6mr7fmv+4yFK1TidsM7yCBu6TSu948cjBFwxjZwlHmHe851lUo95hFaR/+yb8cmNUp/i2s4Y50FOcTf3uj38972Ib9omX7XFXlT0Xsi10u3FhC4jlrav4UPDdZe7x673IW3m1cWGvvDBWLrUyMGd/PjwYsPHk9v82HfFX6WW24/6ez47CxePxrXLhXJ/7B2NHJUv7n15LBo77cOrX/gcjeUbVpbf1CIGI99Y69Q9GoP092dlyP5fDPpduPdsX6NYTFj+y6vPg2NxZnTs5NXrY/GoAf3hWDjmp+q6u14ces4/e3XIwjicenT447pzcfhznu1Sn/dx6Lgn+mXnPAGc39Cx/+dKAeT7efeGsc0DMLxbVqZo5wB0U9qdKjE5gBqNB6/KuDWAJQmGv25tD2Dqwf5/bv07gKL5xnR4uz4ATWvt1jYHA/DO++OXCnrxe2nNR/+ID+B7m1wFe74W/26vOLxgQgB1xKnqxPcfj6n4YUdMALvE3R3jDaDMk13ipMR11KMbkYAvuzuvXNQ8geMyHrd+zZn1ytF4HHrybNikrQkos/nx8DwRCTitO5aqQFQ8NJ5mG5fmTsDk02v8o1Il4sTfdfOeqJYIeve+AxNQu/SLC+8OJCC7/IFEDPEftGTYmYgDd4d33KFLQC336MNH3iTAPG7j760iE/m8E3Fu4PlfrlZOROFMpjRlJyWiRtptr1/WTEJu35Qquh4irvMeLrjmaCLnRyLS/ehnWr8uCQ8KU6AmYXapt8Zi2ZJAWehonoTq8sKTOQ6SUd+lG19rUTjv1BMV/06enYzkX51NimxI5nNMwvipQ+f8kzsZY6plF7c6Gb9+bJgn/ZdknCq78mZOkW+uNQf2jOqVjMMrs52aVeoh7lVc8uPMsId87uL7kxpncR9KxuRfsgcqb3yI0SduF4m//BDiQ89YZk+GNlO8os/1EHTKHW64kC82ueTdn9249abPvowz3ShS/K9DhpdujgsPjvcy19Be8GBPfIZ5Cwp48fepM56BM7w4+CLtRp/Wi0IT7j9akcuH9Rle5WvT2Yd6Igv3nffBdXzFqGkZ/SgrD8aPI/v97Qod8qPoscdtqvzw49HXE6/VDtHot9VbfMvaaNRd9dugZFs051kMzIFys6evj8EHhW5UDLosHV2gSclYpG3e89qcjrEYcHDO2EGnYnHgbaFbLd7HonElx66HReJga+F59a5tHA5tbpC6w7I4FC+d9a/7Z8SrOnFgxsg45E2VWLDWuzikkv8FsLTL73sXlQ0ga7Y+MU/rByCK7slB3QOITUOJHEA3UUW7Dg6gdLkFa2+MDcCxJP/89KMDSH/8xPCx8wNYnWZ+yU6bA2h0p+v2EiI/vp7N9P2a+Lrw1coixAJYJqqrpkw8nr9yD1s3Jx4Hd3SpdO1yAL0fFdh4JzaAGwZ1RZXj8WheXznbzBzPnzMeF98dyPq0Xzwmvt/z7u7reFzvTf+SgEIxvz1rfyAe4sMU7OKL5+tKAF3F2Z0JOLL0/cIcb+Px4bJm4JbaCejfOa7GMZE/VfO/3vvX+wTs+reW2nV2ApqUPNoi950EKNunlj9bIRHxWbecWNJFxH3xuXe+Jiag+JVVW74WScS32KP4uikR7VeVnlNQl4hNOefUOdUkke9DIo43SBpxPXUSChYucy6yehKoKnzeLfrWm9+iRjgTOT6TcHM/JWASej2rKlI8CUl3xgz/p6r4fqWydYq5k3Bs03azP1cyOnw6siC2exKfv8i7GquTt/dM5nxLRos140ToiL71y+JZ/e8loW6n6UbrJCeazO59vLbViebmTifnN3DhwsEM9mrzXHhH4eFyIe/atqKTibhe9Oz9iw1ubP7je/Mvz90QTTVzlZ4eFHs3TqSQh+PJg2kv4zcndvRCluu/vGjdgzqxj+uMD5fPHyvyfZcP/prt0jgcPmT5M5NozX7EBehG+pFQakjb0ooflydr+87LEs11Lhovv88613dnNNZbSi2s9ioajXz1hlRuEoNHXf/o8aF/DH7OWW73lD9j4OvR5vPvV0Tcd7x8auObGMRYuxWZUjMWP1+fLj5yLCabJh+bdj4WJVcNaHUhOpbzOA69SlBFicMebfHzU0bFodL8x0u+bI9DD+/Mlq/uxWHDtwf3p76Mw68dX8wslyWAW9fXicwNcP4E0L/m5xG7fwmgyaXSTTtUFnX8aQkRcgEkjo2qlFn0iSJ9hzWM6xSA6fzqujU2BPBiHmoPuBnHdTQOQ28ccW68HkDXBV2f20U/+LtYq0wb6og8yN7p3NbhAaSufWXcmarxKP/4g+jQ8Ti98c2WMaK/yPIl+sNAtcCZQyfj0WHkr0sPJcWj2bZdjW1Z4jk/47nuJ4DQSFSlBL5f8egpuo3lXDyWxpwf32WEiPeY0hkWbxP1ftG1pksS4uEdOKNT0XwJqNPnUNGDSgJk+xb5UFUCkARsostYnwAJE9IlYrWRPqCI79rWhh3Fz2eSCZGA2f3vDao7LhFbV/zZ1347EaX35Lv9uGIiXlNZb5PI9zcRHzMM/Kt93iTE9rn1vNnURLwos05pcDIR42bNOVKpuYPzxAGKjkWvHegsAYoTjhwLO7iOO3GgrbXoqPQufC15oPKjri7GCS5Ql2n00YXtUW8aXW/ohu3XN6Wf7HKDqv1+gVvmjvh90a6+In5FVn8V8ZxmSf0532I9+Kfq+7dHS3rRoD91flHHG9GBCxwj0GTeAj78bT0Z5ezpQ8wAOgAfPq38K/fv73wYnpoizo9qi/vNfNvdjwF7hzb9MMePVjuz1zAZ/SgzPc2uTL9E41S/xr/emRgNcVOzztBEQzQh0Yli8NuuC6MaNIzBk0H//a2ZFwPjlQND9tyLQaOOyqY/vsdw/Y3FDQrDNrGI+Mlw8/q6WCyl8qKP5euPRZcjI3JeTiPqe85Sy1r/Eoe1ri7OdF3icO7f/M+Wj4/Do9ozVj0VdT6Is+L43MXPvSVAGsCE9p16J6SOQ+WopbcuzYiDJ7s/3/A6sYxfxd+RgDIOI3zft20T/eDnBYQs4nB1GQGoODyjstkwAFf9DMPOzQxgI8GoKPF3JzYrkSZHAB762FcFzpl3ybruSYDxWABjZOMNoOaxiCFD3oo+IQtOPEQwixAOYHzhC/n+ThMPkeydDEPjGWfEY7AEUvGI++/1gCs14rGlNiViPN6KLr4kfwLkrw2KZ7wWD1EE1DFtRLzf25U23dQE/DnzxsqX2ngYBYrbmDMBs4YQckiAdt7s1B9EPFeUACMB3fX3oq5PEnhp1VxRKlQkt7iVpTzsaDmst+6XnXbuP3YcfT6wz+iuDsgyedWBgdnoJ52MG52oV4Mi38lx70KNem1FqLiw3NRdMAUX5GW9c2FSph5jPjR1Y0PB42sX/u3GJAm8Paj0etHF8r08+LJgzO1pWzzo++rgueJWD0RytamZz4v52x89iOnjRbcI15eSB8Tr2VdV8r/2cl31Yf+q8/FPtgkcUvTetSdRPmy+RAXah2m/zY/YU8WPSuJdOoz0Y3ZT79aKt/3QVIg1Nnrjx/vKU0ULiob4owXS9YxGEtGTDdEcf9HINHPk86tZY3B2mKFV8QExzFdisHl2Us4M+2IwVaDD4XEx+LTuXONLpWMhikf+imNiMXL3L/aft8eiWeaa43+YY/F8cc9BxqexiFypxgayxqHdlq6252XikPbZoW69RL0ecaeAedWMGOwoPLNtxn9j4JqqftW7o0GndaJiDP6o99Pm9O1jIYJ4eLezsaCuuXx1DMqIKt1P/PzZxWdyV8oRh8fe01/+EPmQ5nb63HkQi6ytKENjUfrGtxXv/HHIXjfwVpMpgGFB4peSR4QOhpQT+Lx34chvYwIomK6nKDlxMBn7eOwivqskNBQUMoCTu4o/bZJKxCXBgpIiruN3fJndLYxzllYlwhcPS9Ph376uDaDL/k5Jv6sBbFjX9PbZgfFY2W59wyNL40H/mjWjwCn9c32bKH4vMJI+oYKestApeDitT/txTVRUObNc23i7irP2Nu2Sn6scB3buE3ZUj4xb1iydg/GnAz+etRal2wHfhjybBud1osG5C+26T3RixP4a3+frnVDwQLe6kAvxQ1pmPzrYxXHjggDjk2YKnJB/eB0B2d2ct24MFMm344sbybvHixLiwTgJWD1YQbDB4cG1cpd+K1vQi47liGl6MY2ObZ8XEW3pgL1Q9bnGvi7vw+SHvQTF9aFZv8gj108KnEzHGfChwtrK6eqXE3VUoKfic/1YT7fpvB8yLCL8oCrZ/IsfdTXZP32rFs19NBqiuNyIOyDqrWxD4TiZLdDFq3YxOCHY+c+DYzCYyu7sGFxvSowuBp0L/miS+E8MnLOelK2eKTYlTh4kTBJXGIubSz07mz3y43n2u9V2VojGkTsP8pft5keupP3Ldl71p+SHNTUV5mhcIBjwzc/9Ixotqx7qPWG0wC9pz9zf6IwBVeXFZ6I57mKQ80Wkb3z+WObXsfjz3y7Xiwq8M2DR/GlPzTFYto/eKJb5UxysvWvt3ZstFi9NmmaC86KKuFuDj8YhqjoB1Tjm/bG4KLpMwcJxKJVXn29J4QC2fqBCFMBBgaIfTovD3dupvj52xDFuteFy8h+rT5ltjEMVnK5PyoKCCbJRKKg9VJk2o4aKthLYqGguWOcInwpiZznL2ZGmzfiEpAV2/FH8t9dDLXaMTlx55VMeB7xET0c48Os/y4/1MjvQWwobThSicifqZLBvOkFoYFdxF7T0qSa7INv2VRfMhd7/tO6FC66eBJTdkLB+nhv66CuiE7nR8r3rfs/Moj6KrFzYwYMO/nsX1cMeqPR2Tz2QMKqxFzW1F6pMOORFXwlcvTgp2NaQn3yQMKG6j+utD/Lj7Pbh4k2nqDg+5JcEwY9eEnD7IYIrTxGTH6Q2JIl6mbtj1gHv8kYzP47GxyezRKpHI6Fou2I390eDotoVE41Rl55OvZI3BrV/o04Yg75Vl085KPBtM8EKHo0R8SFY3x5x7j0dgwot3+CDbTCdkA9HKGw1Xlgz7ByWVMmHw0lO0XH9EOBfZIYfkpas9uHq2/8cs56I65cERcTrrZIioqK5HvlRi2D5RT/fn2hQN2v9PZp1Iz/rPdEQJEx02BjWx2JwZ+0QgWCjMW9wjR7VKoh6LFhJx6yxmOi5KjI9FpfUw3mmzY3BS6K/phhQdW+7JRLHBRs43SUKY2QjsWHHmfctm/WzoZsE6DbG5wo610nO8nKKgjMTqLEq+CDYWnJ6lXUvFYlHdgvkrkKm8X8qRj3+OzCkpR0T1tT4ZdhmO+gUiql2tNe8ylW9jAPOzKNKjpvl4LxxMG4P9+W/1xuydRd1T9KF707kOul4trini3mri/PAhZ2LzZ8+FnRD/no/N/qs6SQQqRtuag8f3RCgs2iV+h64ErqlWjvSg4fpPa2PCXzZrAl1HA+2FCFC5kX8i9MxM0R/PrhnlKAiXsjLz+7DwYVL1uStLerfLGJEvpRzrDqaOpAPe+nHf/Xj5ZRccav6+NG6cYtDDVf6GWf7MTMvMQo/et7eJDpvNHQPE32dq0dDwvF+0QjczbGn5sFodJ5EzC8agwuRkuaFpK1TvPjQkiqvB9S15+YM6xcNSrWdu7SqD3WkUOPlvuJFZdlgfTBmI4TkQ/0XW3O4fnjRUwogPkTvJaDpx1nRdUcu8EPS1sM+eBZPbbX1gw+N9o8z5431Q8p2laLxSns6f/P6fpzwUmH0Y1iGColxIy04OpiQthVS/rxmZd4fCULBGV5FctxH8f23Qd+ZCKENv13bUavVvza4Sb6sq3A+KTgq2JdBVZiXqKwDqaybqsxT7fiV5KQxdswimHjaDlLNsj61Y4b8BQfKxo2bOnSOA9Stnt1yMG934v0N3+r/hjvRVq29ZeJVJ+NLF0brDz55NsyF6lt/fl5B4L2PqalAunD6+INa2Yq5sa4/CTZuSDh5xQ0pf/znxiqiGTU8KDl5w5Gc/T240Hnsrpl7BB4k2cDgQU3Rtf9M6+U88LKO4GW87mV91AuqRlUKh+ualM+2+jDiY9LgAy4fdovimj+zH/fmF6k3soWfP7+IL5Kf9vix7kXxGUdtfuaFfuzXEFB2I0v0zd3HGnggaVAnN9JG3VnRbr2b9VEPtj/zZNL+64HTvGzg00duULfp096DtvKAvIznvUilryk+ggfDj/wuqK8Hkp5lEnxr7vWk6918jE+9CLYBL5+zmftABIhtLL0VwflrgbzN3yywvKDGaGU9LRILRRT+44lEOZJRZ0dByqFZbRxvNtRJ8/rmggc2xLzsnOexqEfytndWMGLs/E227QokPHmmoFqFEz/bWqholCf9lxb7VLT5Pihw46MKCedq29G9yJSa0YvsGDvoVLo1GjuqTjiU+nZ6BypsaiEQgAPtu0/MPm6bA7FbKIEdkDQ+mxMTgwkPUrs6nXRCkN9shb44UXzoi77NmrjQed2OCbmXuiDL5SUX6+ku0OmNr++GhCEL3fiWSI3bje9l85QM/ORh3c7DOpEHUzr/095/zwNv34GlLyd7GB94IT/GJC/aSMLlRYmMZSyXRfw0+WNKdPkiPpiJrnT0YZlgif4/fcx3fDjTnjI83HfSNsHan4r68fjn2ZunWV0oTzCwfuh6XFwnXYi4kafXtvluDC+Y0Dv/NTemn/8eNfiuC9RFD4t6S3/19A83jNZJ4i09ILVuyBA36/du/JtQp9D9fka8ofDOZMK1Fw9P5LhhQrFc1FnMkPA+UwS+kEx1KALy+JtZOO4teHVM367uKivW96aCHokB7qqC+kZi2TCK6Cj80pqUdRuIta1ta0Np2RBsEMX0ct1PNq5bCnJLYq9gAdHaGwr/ngoZVqJvBfusCvSiSYXK9dHOcWjHSZL379vxFSs+v0njgKT/zR3wdyYE70CBfpnEkTlY33GiDJXtdk4cm20o32CzE59Obst8z+FE528Fprpzu7C9LCnKLrSoRYjVxXHmwtOoBYdXZnND0uIObnSSiePm/HYzbxH9i8JrgAeCRAtK7sFdggFXPMgjBWQPzP/laLm4iRdfZ3fblGWoqPsVSRHwsr7gZb3Sx/HuQ6aHj1/PFTiK0NXDs07MkwXBmaLrLE6n21B9phODJ9d7e6q+Cz06/DS92CIXXvagN3YyD3Zhr9tT5uQ1PQZLYcKA9kSX3huQ8GTbxWyTjSifnhQaExpsjljY5p6JebkZ9XcknLz40sw4NgLlaKxQ0IK/z2vTmo9aWI+wonVxigArSkjBMxKSxpePwuX1J8uuvBkFSc8rijpB9HKyDZ2kcGNjnUPBi3/v1y/VVsFUghcCLwf5r4JjdFsFXh6RJ6LymeUq80WV65SKzXS7OtqRVTZ4O2KpbYm6se/pxt3xGQRvo7Rt6sA1gq+zHZhPY6sbDuSUhDhcN4LzEifPF8M6WQtJNF34VRJpF6wW+k/wui2xde9+EK/GLYfHlnWj6vGJO+3DRV2XN9oNurrDPjc+9v5iS//ejf4CDd2t6OH5jAd7SF447sF43feLc994IMehjbxYQG1ktBcP6hOAEDijPAWCFnVEV7xRXcc6tQ6C5Auor4cI2je/Rek5HwyoKxPSCCmrrTAyXjHBUIUUBhPu0xiplpl1dzOoapkmR+BlvZbio0fg4JA99zL/aWFdz8q8woqNIyrtiuwYCVLNmydEcr+KwuZNJIjYUPuv5fGlhtiYh9owRRYsGzq8Xd9tWmmFcZCCGVLAUUB351iigrWfOlrmVFehlPR/XjBG5fqsIp5k+tR27nd2xm125q92vC1GgxcH9ycHXARPVjh4nudAGlnQnKCsaFrNiWtZrdMLjXay7u5kvdYJUiVyiLqajsaN/V3YXJIGuS6I4M9y846L65ULcuzd1c16rsAXNOYSfWLh7V6ihLuRff3mXo8KeJB76X3zgZYe5CS5dYWH+6IHa/PSHdKg0KHp3Wv/puW6pIUIyt7Ha+uwJrCwoveCjnVtPaT8rurhvHjlbptRBjSl8vbMgCxy4G1EIpXv4uFzrdy8sCjpZkhYkWTmOIrgOXwEBLlfObS/hfmyFUOWvRqVuNLK9SESE6SwGQmZxtmjmJdHoW+Fia3rVbYx/7QxHrWhqCQcNoyUBUVBQ/lBFe5/Cp+Pyp9XxVpRfScuVllHU5E+PymFdhStScqBnfVsOw41pYyyY+vtBoZFz+zIIIU0BypJIcXB8wkHLtT8M3LsMwfeUdss68TyxjQJE/ixtBJRbruT5/FOxg8u3BxBg28XbtHtGeHCvvLTBgzd4QKdzgSPqPMzyIDg5rmiG4uCg3jmOW6s0ewcaE3twaCnjzq0rKCFSIYMrU0aiJsa3SqtFlepfI/Wouykfyfse6pFuhJ97qeboGPdVoeKBbY5Mo/SQ46vHumZfxoYZxp4zm/EcpJd8pi4DppAqkft0qIfy8QyY7ps6BGQt08TAZqa7+hi4bm4BZlpDDvWir4SUFshbQRTIjGpDJ1QJOtPUeyTsKEMjZEb2kAsUTtT8MuNNIizIZcUVG1oIImwAlm+lijMmxSQKj/vuYLyf2z45305lfmiCgknRf72HB6X98EPFeQG0NWzc5+347Dh5fgvl+yQLo3HdlSf10KUIgfqSaDl4L7iwE9Prp1L+8iBbpcy9l1cwsn8zQkJC3eGdbefmo75+dePTrSJHvqkeX4XZn4ae7FVYxfrpS5UlYN5FyRMUlyoSPJsRjcSaOxcwsh4VcfnoIF9DL2TBkVkI9UilsY+S7Xcb7S4vpkIqY75qw6kqhSfoYeE4QE98xEDKkhgbmAd3AhCvZ5XRtZRTZB0M4OZcYIZW2isnD0CiQT/N4p8JXkxuwVShl1jYd5ugWgSd7put2Ifyaq/RuKobbb4k+I1J01ko5BMYXUuCtRlv5e1Me+zMe+0sf5twxyCH1kVSNmim4JVJB9vUSDHQXoF0haUWYX8MZG/f279u/vXaSocZCe5rkLKxa9U7kt2rjd20NSj6EE7ThemgZ4dXek2pXZAyl71HJDy9SwH63cODJBv7IClfztjxsZOxtFO/Fax2rDpp5xIFOhjdcDJc0UX9y8XpOwySOT179kEZbNxP4/gOqbHbZJtZmh5nq1BS9nYNZAwpJqWdU4t5Pi+oI55ro51Fj16S2CuR0Ep5OjRNSc5oAz8uQyMT40odlApoo00Mo80Iau6tqXda0JB86oZeQV+evYl/a3BfjNKGH/LXHN8BN8PCyTMH2+BtK1Ei35LctkUK/uxrJgy/niBRxMjuT5F4ubYzJ/3j4zClsSOAjlF8RzexvMdG7JLwi/6sARyNq6vCs/VFWQzDnj5fZaCHBKgK/ALtv0xScFtxJ7qWVZlX4LKeoeKtP1IsVfxItOx9FW/qBCkw2aDHVPkYNHOupYdy3tQJNtZB3RgTAFyADgg4eVCB1rS2OeEA/nkoM/BvNPJ+q+TfQNOjnOVeaoCKbNdiUSyYBu1Xhp5zqfjPNeiE8l5dg3rbhpkFVGao60WRz7SwESL51ep4etgojHDQh0KDCq29+YbHfcRPaYnX2qU84U45567ti6ZEO6vq62GKweGGJGDxnhGI/N6EzTvy4lKZ4K0AzQ04ynZiG6bkefSAAF1I1hfjIAc45e2gNTwxRst+CR9d1au51ZI2Vz02ztfiWhGQtLkuEioqegEorjP2DjObdw3bKxf2DBBCqni3HNSgVQg6VorBY9SkWNIgZRPBI8Kzs0VyPLYUGUdXsWJald/Stqvsh6p4iqNTTPbIYrsqX6N7Xw/7Mz77Jj1orFgsHbmJQ7uFw7sJHlmjgMrOtMA1cH9xYFezUmxVXFFdLNJfVVIm9QwlXmpAppOd15pwUmCwZMMPE/UYncPEsA0GC1QQjqdhn1PWsaFWhDrvqhqMYTCoZ6O5zo6kAtweho9BDjcW36aHscubXnQ5Y0eHaRRyMB6oYF9gkaUore7bYSUXcua8JMc9AocReOUVGbIMFxmhqTdWSMwWjaCCJ6HRTD/toDcQnPiLMghiYKV5/lWSBm6YiQsO/KLiItEOSkcRaGjbLBR0vUzroSN5zY2FCjbLf2hzTacakIE14ZK0sBnY/+gAnExV/e0U3jeouBiFQI0Ct59utNh4QeFfQ8qykkjj4rFmQkBqnhPZf+hyvqrnePYDmlrmBnW54LzizBf2kZlvpEDC6QxQ+U+o8JdixiCilfULmer/DlV3BVXUaqlDdsz0x024+cshBz0EKBxltJLy3hQw/qyBr8PJUaoZZ+hln1oWvYJ6bBQAmId61h6pO9Cip+o5ySbPNRj1PZ0x08MN8AqbS4GTLnXXDA0wV9L0uTViMzfr4kObcIAaie7TawTm5FRChFm9hOaMdM14ZbtjwhkkoJOBM/5LKyjWNgHYmUfhJXxUiRGyP8ikX9J4a3V7JHIPm7boMn1othXGYX8ssDaWOcSfIjCaK4NGyZR57Vhqgx48f1n7Q+8LaTgTAwBT4X1JwWyfFxW2J+qQI5v86pc31Qk2yghVGy7VmpPvtviHHzjRUVQOV7sKCaFTDskbJ9l58+vsn9VxVwppKrYf3T7mfctVfahqYwPVJwiOSRKwZdLxcQtjcRkCRhMfH26lLxsNPZa/1FnNeyP0vBcT4s4wYotm7XwxZ8zFXqvRSZZWHQ899WxbqjnONKjihQ29Lh7uHrf1j0MoK4euGHAuoV/T45vakQbKQgZ8fufF/4sntHE80wTz2dMHB9mnlOYgQZU2SNAqCbxSARet3q4CQUsGNy966/7V1k4vywgl9raIVbQlKWrzQppk+sUiXxfI16YxOcO3s8o/Lfind+9OArEtn57HYXts2jQb8MHkRW+HjbIcF5pw1XB0iJuCHy1L+PMkc9tkPKyyN8/RfZO7qGwP0RB9v9+/uP0cQXn5tHAWeF6rzLPUllPVXnupfI8V4Ugw95/xc8H/X0Kjgm2WiVBgWyvog5I+PqzCnI3OeurPP9TQarqlokq8ywlZS6Qh+TFJAPfDy3ngQbayDwNzl3Q8Fxf4CY5SNam6BDSFphZh2Ah07FPS4cpMsH1aCINiXq0lYYePft7DOw7M7BOZWT/gBGz5UDfyLxF8B2iiw4T3szd/f1ZazPPL834t2fU7y9/icDjFbn+ObRO5GspqsQWyDFZVwvkuFlvwXXBGtaWs/Kc0Yo+RJ9eWCHH530ikfNymuY9r0ViqjQIRuEUwcuFUUCqEx32RIvz7kADdxsWl6VBq411RBt+lwZLG/sdbTxXUng+r+A7yXqbFGwgunhPYR+Uwvki6vIsmiipjFcU9sMqrMMpPAdV2G+lsL9P4GtpAFXZjxLu49K2JL4O+jNtkHb+VRHI8ZNFSfyox/UnJFhqkfpwnclT7mmwJRU1Cg3PezUYfnKQyAgtZoqq2mCdFvJYP2uh19IATAdyQ4nMY11Uz/xQ9FWSFx16ZJJA2MB5ZoC0+ecysl/LyP72MH4K6vIm7M1FyM+MpbWIEZjZj2Jm338E67IRuHHy2a2SnyLQ+8ejagMHWLBpwdcGkyLFeRMsbmblOawVZz1kwIuEhNsLIqGTsnIkFrWhvxyVgquCvswojDfnjU0uaUMUhXk7G/MRGzbZyLBqY9+oDd5M2n+/pFewrhxVNgV/xZAQrLBfXYEcKzxWYMtCBkLRn6WwobDPQWEflsK4JpyvK6Kz1Q28Vdj3qSIj0dBGKvNVFSOprYp8Ds6hovjfzSBxr3wDPfv2tKx7a9D1zdPCaS9qWBfWoP1kcmSG8/WI71hi9bQ6ZC/05dfrvXUgFezEbR373fXMM/R83/SQY7zaBjyhdY+9BojDLtvxhQF7W1GFMiK7JLRG9rGZkIVo/xwTgusMJvZ3m9nnZIa07xaPwAZq/xMjeG8iApHrnmRu18gCM9ks9lnw8dzpWuXTW1FbCpFWSJum08p+gEgspONfGYmIt4EXp2MiQawnQ4UoTJcDjSiIoiAqQhT3ORtIdckszrfKjxL/fZhuY9xrQ2Fp/LQxnxd9msaX70QeE70Ur9G5yIig4Hf5iwrrewpm7TlY6sY3BSeb06ZEeJ51XNzdba8V1ltEHhcj5V3luZPKc0MVy3KTA1DBSmonUyPZf2Ziv5oOD370vDi0lJb5uwaSLhzRYPG25mvGPdKwb0TL/lgt8yItyLXyfKAOsr2d1+GaQgGvx4rxNNjXs19Ej8c09mlsgCwTWwwQf0xAXwPe0+W0MiK/45rlyUUj8wET+ypMEORTIGUTvjwngd6MsUuOf011OIyjFkeRcTICeYuYknE4AjsrEGGxYD/ByBEWXGtJArIF0p5fwso6rpX72P/oytI3EMl+tkhIm23zKByl9YIl4fMN+uFszL9F3u6mBQIbSH2YKM4l6GtW2CcVrrNXiC4/Db+G6nAtmn6lUVNwUobWplNTRb2uRvK3wF1B/S2Ml+Ta0XSV9QWV/dwK+8Gs+EkWTiOmjtr0fB50sF2fVLx0Vm1KXw3lbVC30nAeaNFXGiW1KHF+ivhNLerRupOowx+nB/bkOqJjP5QOnltE2PXolTnfipr39Fj6ZXv9/vkMzP8MKEdw1WRAUTkoM+LOiTYCORkhL/OJkedPJpBr4i/Be4K+YhOMc6mAmFFNLsqYmUeZsXdvtvWbe0Wg2+yG/4x+EAFJR0taIGH2YgvjTwsCy5qlKyzqsmwr+8O6sqTdfcK4qoEEIpH4XQqyUZAy3p/h/hvUfRX8IDu7OE9p9/mq4PDJzAdfpA2fj4R5OVU0pnGPODdprxB8JehjUrE8LQmwKjpIg77K8xwV6QQ6eC5+PuirUnH6x9S/qgr+FPR7qGgojYgqqCs09dpS+F6wzhhAbvZjj8O60sVFRLg0rJdrMF8asMO4SY5fNmnZV6GF+GP3mzTQcR7oeM9Jh+my0OpZr9Qzvzfw/Tcgq1zIMLCv18i+TSNKdifnhxG3BhPTNrHPysRzIhNWElwSeSvl5UlmSJp+04xztE5SJALPyda4OoL9kRGQtsgmFpSVRjILssnFLgssWel/rIgmmfuwlefRkZwPkfCWOXktw9VIaBZvrDQoTRSuEz0R/ZFO5eALhfmzgv5SSFBwW6CJIS6F52ThPkmqfm6nwrpD2DfXmcp9YpgXjZVAR0mJF9pyyCXqc+hcJR0TvDV4X1XsJpuwqOOD5WDTloIj60rjpQFSbrqrxRwJPzSYLImlhueBGjSUCx7h+c3TJhSwYZ5z8w4RGB3O7STBXwcJ9/063hvRM//Usz9WD9mOuxhQY0q+D5c1BtTLSx3KmDKX7zjkp971L4fn87uuLhx+5HcT80MT+1zN2EP20d5mnlebIY9d1OV9pWnjIgLkKl94O4L9YBZ+fwv3cQvWFCLHlxUJVB4GhXGVlBVyR0LKPeK+Bvd/FO4bCohVzRLnKumv+L7xKQF0gXclUVGgX01vrECuVwhcFNTXFMZhSkp8hOpzCD8F9/oUnieLuioNRgqIbbX5LPgL2YZKivyuR4tvok7LRTolpT8E54dmyHWjO3rItvaXln3kGsbJYTwc9GtrsOPHRoEwtbzXqoW0VcZrIeXtxjrWx3WM73SQNvSmetZvwvp/kGcZeJ/KgC/X63Rf+9bAuM2IryQHHzTiEMliSUbGlybYvaZAudkm9hOYeF5sRr4C5KA0o4kEmmbGtRG8LxrB89AIroMWSNvHVAvay8U3C+vz1pS8Cc43FPwqDcrhOhv6+v/j2kDbGePSifwb0XGHTvsw/CrhRrzC+xAKJF10h85B4f6mpNTfUH9dQWMJkZ+/yMGJmjI/uqOnQaaK/BIYqZDleKsCWc7zRaXMS5aQHX2kHpFka1mrTdEL80hiruH5lIb1Tw2eOLZFvRH9NTg31bJfTQsJt6vpeN9OhyztyFmn43qp53mWHtoyhr3qA/E1yYcFDHj1efCyV6MMkPKKYmCfnxHziK6uNkLaZ11G3gszYcZ/S2LOjzdB2k5OmTgvBB+icUhbM+i32x81s38wAnKdYlQEbnYsVXnbtQieI0Wwf87C+xoKFlE6i/yQa1V2hft++HVY0w9zPhoUnt8L3JOXGrCC+9vIWCbyj9a9xPeD+k24HmcgGi3qbnBvSuF9ZIX3URXsz0sBKXAyyfAOhf2ICs4T7RZ5HfQdKeyXVnGxFTU6FZupXDRWec6hwE22qx2RyCgXvE3M4/SQ8GKcFo3fZEwbdUfD+xAauEiONmjQa9t8Qe3D+Rr0hWjZT6mFKFpUEPCOaMIMHfrJxVgd4zk9ZLkZr0d6slvcCffZYwTvmhnQkNYO/zaw/9+YwntCOlQ0jbHTmUCulQNtQ/jdxPMUE+/hmFHj4dkySUvNCJZxM0aTTaxMBO/5RKTcz/RSAFLYhyTuC603ifst12sDCvO6cB8N1eGQbhDSgYPzyDAfCdXhnAQ3BR99ah45u2h02FcTOregDqSwnqqwrzv89SS5WKKwf1H02zE0EVd5z0kFuSQOV1d5v1xh/3Ak+hPdbWhKmZMG59Ra3uPToAuNMw5qOF41kHLqBw3sHeiOaZmXa+Fuf9f7UK+FpMvFdSg2Kv3y0xN0iCEZ45KO5/t63nvXs69Ojx20fvpVj4FyUcwAaXPeZOB4N+AbyUG5jewvNaJud9roMnI/N7LPKzwfCM7xTfidaE8rM/qSXWGvOWXOEowXFfTUhHaCT5ymcbnIg6DfU2EfrKiL0sgePucg7lVSdNdQPAT3dhVIe4pFQfZTs0q9FfkanHspWDqBjEsKCkvBVMHn6hRw4TyUMoCo6yF+OyTvRAE9FLz5iwYCClrIhX+F77uIP1qbENe/hsqz6K95zraOnyPqdJCnKryHZuV5rZGvS5dyXkG/mQYVpbFHgzFyYV2Dkuuni8qlZf+glvdntSB1tM99Lc+hdZB27z/CutPrXLSpoeP5gx7nSD6ar4dozp86WvSsKxgg6fUsA/txDNhYfWblEsWMkPabUUbIteejRvb7mnheZsI+9cEXrDDx3MaUcv82Oc/s2yLyQl52INwvQ/tDIX4ZxPnh/LtL6x4iP+Q6x3eFfcgKblanSFIh1+8FX5F2jHxh/hHU11TItYrUKu+Rh3EtTX0vibiR8qjI6+B+iqgPY4iIqym6RLA/qniIw3F3c6g8h1BT/NrBuawK2j44Ib6fkcYd32z4VJB+0srPMTCCtoR+uaoDaHxZSZvCbzpLIVkDaW8SPCeoz4V1/+BzEbS8RybynNagPmlBW5z7Buh4bqXDP11IsNKzr07Pe5l63Cc7u0MPuWZcxMB+DwPv2Yf9ikG+bGQfnREbP1LhNHIcmVL0mhBvDPIlFcSWd6UN88LQ1zF/7TuvFa9B/6ia8vNBv4GKeLJl5VLRj9ZpRd0LzslUyPVqwSeD/jGV9U+Vn1ug8nNOVGSpQpsoKu/DhnlrSPcPnWcVuagt+It80EQ4b5vLBdQwPhsmiajC+0sq+4tVOF5TYivI2IxOzIY/pKBghRzTnzJCjruO6dBCDkq1PK/SQD52ZZsG1KVm3NVAruF+DPskgs/P0LL/XvAeWtt+poWEvYLHBvcUdOzX1vGcWA9p/+mp5z3Y8Jwntxz8G7BQPmjCAFI37jwwsI/KyHq+MSXvQvVsGbW95DC+DOHZUH4E+Vn465D+GtpbCM55wl8Pp7VLUX9XViHjpoJeg4jBKDA1IuChQMJuNcxDIvZUWbPKGsY9IVwUwsdtM/77o7DAxbI9iNc7tN6UHH4N+S3SXnTfQmy47tPWTi7Rj4P9ReHn3Si49/rKyO0iTslFFiP+bnCua2PfqYX3L4y8FyPyimS+GlrOFw37ijU8T9Mwr9Lwc2IEvrrecOy1/lrm+SIepCFLC7nWX1+Hve2og4T7bHDPWMf7yuF6nHUudUw9pG1b4OOgf86AfnJwbUAPKXgrPF9ScI3GYQJXvm/bR1C4MN//T7Y5hXG4gvo34g6UE+cV7CMKtm8jY3YYF4W+DurEYTwcet/Qv4fmZaG4CfGaEM4J6RFz5QOPwv3Z0ZwIdfj9QtcdfG5IOC9DfCiEz0J15wXZp0X9CPqlw3Oc4PxbTYlfuU5w0YYOBHPeWdgfYcTrKjRoCudr8HkeGhxPVSBq/wENyD3c9ZKG/VEaDCNanl/Lexxa9rFqmY9oseN4bCFPBR2k3W6OwE0img1XdFz/9CnnGvR16JFUiZ78pEdpCbT1KTyjuzQCKTzPD+OQ4D5u+DV0X0M4U9pO48P5EIqLUL4GnycUxiVB3qwgjfffmGKi7wZ5kAL5uCHxapZrm+E6EOrfQZ9teN4S0h9C+CuS1kmfhXXg4F50WE8K5eflRrRRGuZF3+W6fLhOh/ytEvYJnuMTp7esjMp6qgK5bnLfxntKVshx/y0j8y4dypJc1lYLm5MMURrmHZqU/A35YSS8za3FTVr36CXigOTkv7SYJA0MWkh7Tx4d+6l0kLRjn47vt46vSx9s54P07IML84SQLhbSz0ZJYVGFtEsKfBHi8cE5arjOhnSgAdKQHz7vEK8JPqdEwS+5yQGvsF82zDdDcRLSd9ocOztv+6Pw3DR0LqF5WChvg7hQ1EeyfSSF8zhUF0Lzt1AdDj7vI8yDQucbfB5NuG6H3r/J2ex5E8V9kGsnecJ5G/S5KTi7jwqwDSXILtjYCimXeI2sU+pYL9YyvtfwXEQDaQsQuCnI8zSMP7Q4RHC4hRZ55GRWC9r2zKlosZrWGNPoWFfXsZ9Dx8+50LGPTE3BoSG8H6pHQX1a4blcuD6GPkeo3oX4fqgPhvpdqA6G6qtck/yffw/pANMykhNbnMtQcnAKPinpuMLzAgWPb5Owo/CeksLPSVAYbyj8fDZxv+nxTuL3QnpeUAcLX0fw+RJh/hPyT4T045AeFfR7hetCKE5C8x75GAKBj4N5pab0paNka//HxjzECjmmFHwhiBf1PEfRIkcNenKBBr1kAmhYX9VwPQvnaxKVOWh5PqVFLfngPS2GSaOrDtIG2kYH+dgHXfj+hfpfcP6r8P664BlUPfUK+74FHiR74E3B/6Sgq6S8T0j3CeolCvu7lBRfZbNB5CAKx0Nwnz58zsHn6Cnscw3X0ZDOt5Po2P/EVejrUByF6maoXwafjyV4Jj3GQVzPPLlII/okrTVEhOvCFFojjgrjsBBOC8VZqN5XlwNGhX224foewsdBnKLwHpD4fXqM21UbqLv9M9qKFfFUmExwliWAr0c7Ggst1/L90eAprUOd1vA+moZxmgYDhlIH1fLzULS8X6PFp260Wa1N0bGlrf11GL+HdJnucmFdxZ7V3Qv0y6QyL1ZTfNYhv0doThXijUFfrQr5OCrBU57TWuiXsL9Tylni69D3Q1+H6kHQZx+ub6H+J2mn4LFBHqfgUClScMPXH/Q7Kfw8lHD+BH3yCj/nTOXnSITn5KF6HZoLhPpECI+Hzi3Up0O4LFTvQ/0zxKeDPngV0mYt6nGof8UJNPMgwcY4zQr5OJY1Jkib9kg9P09Dy/mhYT+ohn3qGmynY16jAblUXx3UcN5o8H+ANIMRAgAAAACAAACMAgAAZRsAABIBAAA=eJw93W3ot2ddx/Glo7lktcZYLVmtMXQlsjS5zMJcJLZSHCnZ2NJaZXeIVFbSSMu1JTMnoqYub1h3RqzCamE1YmERaBhkQlFClFFhECEskkTa6/zwPq9HLw7O//Xo/T1+z77H7T900U03P/S4my567N+L3/+40zf/68Wnb3/smxsfvfj8Jvsm++aqC5ec32Tf5G+87pLz/3zm91x62nn/j/PsvL91nr/6fU88//YrP3HZaef9rfPsvL91nr/kyy4///ayW6847by/dZ6d97fO8+PfceX5t5/526tOO+9vnWfn/a3z/N9ffPX5t/92y5NOO+9vnWfn/a3z/In7rjn/9mN/9RWnnfe3zrPz/tZ5/vCl151/+8i3XH/aeX/rPDvvb53nP7znyeffPvjnN5x23t86z877W+f5Vz7vqeffvuu5TzvtvL91np33t87zm1974/m3dz/89NPO+1vn2Xl/6zzf+ZmvPf/2x5514bTz/tZ5dt7fOs8v+4OvP/+WO//WG597nnPnFx785vOcO7/uKTef59z5F/3aC89z7vz/vvzbz3Pu/D9++TvOc+7841fddp5z53/21pef59z573zh953n3Pn9b/zB85w7/4XPf+V5zp3/+F0/ep5z59/9uZ84z7nzF9z50+c5d/6s/3ntec6dX/Hs15/n3PkTXvPz5zl3/rmH7jnPufNHP/2G85w7/8+veeN5zp3/86vedJ5z53/3228+z7nzj37qLec5d/4XN7ztPOfO/+QHfuk8584/8OvvPM+58/f/y/3nOXf+3mvfc55z5297+fvOc+783vc8cJ5z5z/7D796nnPnP/mlv3Gec+evfOlvnufc+fe+/bfOc+781o89eJ5z5y+6/HfPc+78eS/6wHnOnX/Dm37/POfOn/6Rh85z7vwpT/jgec6dX/P8Pz7PufMr7374POfOv+BDf3qec+ePTdV5zp37zf3sT1162G9u9pubffPJDz7x/Cb7Jvud7Xu/s9l53zjPfk/7xu9pdt43zrPfzb7xu5md943z7Pexb/w+Zud94zz7Hewbv4PZed84z37v+sbvXXbeN86z37W+8buWnfeN8+z3q2/8fmXnfeM8+53qG79T2XnfOM9+j/rG71F23jfOs9+dvvG7k533jfPsNyj73cl+a7Lfl+w3JfsdyX47st+L7Dci+13Ifguy+z+787N7Prvbs/s8u8Ozezu7q7P7ObuTs3s4u3uz+za7Y7N7NbtLs/szuzOzezK7G7P7MLsDs3svu+uy+y2707J7LLu7svsqu6Oyeym7i7L7J7tzsvvkI/972WH3SXafZN/83rMvP7/Jvsnulr53t2TnfeM8u1v6xt2SnfeN8+xu6Rt3S3beN86zu6Vv3C3Zed84z+6WvnG3ZOd94zy7W/rG3ZKd943z7G7pG3dLdt43zrO7pW/cLdl53zjP7pa+cbdk533jPLtb+sbdkp33jfPsPsnuk+w+ye6T7D7J7pPsPsnuk+w+ye6T7D7J7pPsPsnuk+w+ye6T7D7J7pPsPsnuk+w+ye6T7D7J7pPsPsnuk+w+ye6T7D7J7pPsPsnuk+w+ye6T7D7J7pPsPsnuk+w+ye6T7D7J7pPsPsnuk+w+ye6T7K54551XHHZXZHdF9s3rHr7y/Cb7Jrs3+t69kZ33jfPs3ugb90Z23jfOs3ujb9wb2XnfOM/ujb5xb2TnfeM8uzf6xr2RnfeN8+ze6Bv3RnbeN86ze6Nv3BvZed84z+6NvnFvZOd94zy7N/rGvZGd943z7K7I7orsrsjuiuyuyO6K7K7I7orsrsjuiuyuyO6K7K7I7orsrsjuiuyuyO6K7K7I7orsrsjuiuyuyO6K7K7I7orsrsjuiuyuyO6K7K7I7orsrsjuiuyuyO6K7K7I7orsrsjuiuyuyO6K7K7I7orsrsjuiuyuyO6BV3z2qsPugeweyL554XOuPr/JvsnuhL53J2TnfeM8uxP6xp2QnfeN8+xO6Bt3QnbeN86zO6Fv3AnZed84z+6EvnEnZOd94zy7E/rGnZCd943z7E7oG3dCdt43zrM7oW/cCdl53zjP7oHsHsjugeweyO6B7B7I7oHsHsjugeweyO6B7B7I7oHsHsjugeweyO6B7B7I7oHsHsjugeweyO6B7B7I7oHsHsjugeweyO6B7B7I7oHsHsjugeweyO6B7B7I7oHsHsjugeweyO6B7B7I7oHsHsjugeweyO6B7B7IZvwZr3vSYTOezXj2zdWPXHN+k32TzXvfm/fsvG+cZ/PeN+Y9O+8b59m89415z877xnk2731j3rPzvnGezXvfmPfsvG+cZ/PeN+Y9O+8b59m89415z877xnk249mMZzOezXg249mMZzOezXg249mMZzOezXg249mMZzOezXg249mMZzOezXg249mMZzOezXg249mMZzOezXg249mMZzOezXg249mMZzOezXg249mMZzOezXg249mMZzOezXg249mMZzOezXg249n8XnTRtYfNbza/2Tf/ftN15zfZN9ks971Zzs77xnk2y31jlrPzvnGezXLfmOXsvG+cZ7PcN2Y5O+8b59ks941Zzs77xnk2y31jlrPzvnGezW82v9n8ZvObzW82v9n8ZvObzW82v9n8ZvObzW82v9n8ZvObzW82v9n8ZvObzW82v9n8ZvObzW82v9n8ZvObzW82v9n8ZvObzW82v9n8ZvObzW82v9n8ZvObzW82v9n8ZvObzW82v9n8ZvObzW82v9ls/vXrrz9sNrPZzL556ENPPr/JvsnmtO/NaXbeN86zOe0bc5qd943zbE77xpxm533jPJvTvjGn2XnfOM/mtG/MaXbeN86z2cxmM5vNbDaz2cxmM5vNbDaz2cxmM5vNbDaz2cxmM5vNbDaz2cxmM5vNbDaz2cxmM5vNbDaz2cxmM5vNbDaz2cxmM5vNbDaz2cxmM5vNbDaz2cxmM5vNbDaz2cxmM5vNbDaz2cxmM5vNbDaz2cxmM5vNbO7e/fivOmzusrnLvrnreU89v8m+yWaw781gdt43zrMZ7BszmJ33jfNsBvvGDGbnfeM8m8G+MYPZed84z+Yum7ts7rK5y+Yum7ts7rK5y+Yum7ts7rK5y+Yum7ts7rK5y+Yum7ts7rK5y+Yum7ts7rK5y+Yum7ts7rK5y+Yum7ts7rK5y+Yum7ts7rK5y+Yum7ts7rK5y+Yum7ts7rK5y+Yum7ts7rK5y+Yum7ts7rK5y2bqh+952mEzlc1U9s0tf3nj+U32TTZffW++svO+cZ7NV9+Yr+y8b5xn89U35is77xvn2UxlM5XNVDZT2UxlM5XNVDZT2UxlM5XNVDZT2UxlM5XNVDZT2UxlM5XNVDZT2UxlM5XNVDZT2UxlM5XNVDZT2UxlM5XNVDZT2UxlM5XNVDZT2UxlM5XNVDZT2UxlM5XNVDZT2UxlM5XNVDZT2UxlM5XNVDZT2Uxl83LhkmccNi/ZvGTfXHPzM89vsm+y2el7s5Od943zbHb6xuxk533jPJuXbF6yecnmJZuXbF6yecnmJZuXbF6yecnmJZuXbF6yecnmJZuXbF6yecnmJZuXbF6yecnmJZuXbF6yecnmJZuXbF6yecnmJZuXbF6yecnmJZuXbF6yecnmJZuXbF6yecnmJZuXbF6yecnmJZuXbF6yecnmJZuXbF6yWbj43guHzUI2C9k3n/rw153fZN9kc9H35iI77xvn2Sxks5DNQjYL2Sxks5DNQjYL2Sxks5DNQjYL2Sxks5DNQjYL2Sxks5DNQjYL2Sxks5DNQjYL2Sxks5DNQjYL2Sxks5DNQjYL2Sxks5DNQjYL2Sxks5DNQjYL2Sxks5DNQjYL2Sxks5DNQjYL2Sxks5DNQjYL2Sxks5DNQtb5H73gOYe1nXWbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1e89Hv+mwbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbl9yy/MP6zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26/bav/m2w7rNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbr9rxffcli3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3D3/8JYd1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1e+9Lbz2s26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus2+/8++86rNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNvrb7vjsG6zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus24//Y+vOKzbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbR172I4d1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1e98/veqwbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbm+749WHdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdXvDJ19zWLdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbePfv/PHNZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdbtHa/+ucO6zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus23H7vH7zq8fePzdoPP2+89b0f3vD3b83Zlz9t3PW9n9by90/N2R8/b/zxvh/O8nczz9jDP2708b9/yvB3L8/Yqz9ulPG9/8rydyfP2JM/bjTxvH/K8Hcjz9h7P23U8b7/xvJ3G8/YYz9tdPG9f8bwdxfP2Es/bRTxv//C8ncPz9gzP2y08b5/wvB3C8/YGz9sVPG8/8LydwPP2AM/b/Ttv3++8Hb/z9vrO2+U7b3/vvJ298/b0ztvNO28f77wdvPP24d99eDvw5+2un7d/ft4O+Xl74Oftcp+3j33eTvV5e9Hn7Taft5983o7xWbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3eW80vOHw3mWY97bCvPcR5r1xMO+dgnlvDcx7L2Dezv95e/vn7d6ftz9/3g78eXvv5+26n7ffft5O+3l77Oftrp+3r37ejvp5e+nn7aKft39+3s75eXvm5+2Wn7dPft4O+Xl74+ftip+3H37eTvh5e+Dn7X6ft+993o73eXvd5+1yn7e/fd7O9nl72uftZp+3j33eDvZ5e9fn7Vqft1993k71eXvU5+1On7cvfd6O9Hl70eftQp+3/3zezvN5e87n7Tm/9/B2m8/bVT5vD/m8HePz9ofP2w0+b+/3vJ3e8/Z1z9vFPW/P9rwd2rNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbvN27//i4e3bn7dLf96e/Hk78Oftt5+3u37eXvp5O+fn7ZOftyt+3h74eTve5+14n7fjfd6O93k73ufteJ+3433ejvd5O97n7Xift+N93o73eTve5+14n7fjfd6O93k73ufteJ+3433ejvd5O97n7Xift+N93o73eTve5+14n7fjfd6O93k73ufteJ+3433ejvd5O97n7Xift+N93o73eTve5+14n7fjfd6O93k73ufteJ+3433ejvd5O97n7Xift+P9vsPb6z5vT/u8Hezz9qvP250+by/6vJ3n8/aZz9tVPm8P+bwd47Nus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNu894deMvhvTUw7x2BeW8EzNv/P2+3/7y9/fN28s/btz9vl/68PfnzduDP24E/bwf+vB3483bgz9uBP28H/rwd+PN24M/bgT9vB/68HfjzduDP24E/bwf+vB3483bgz9uBP28H/rwd+PN24M/bgT9vB/68HfjzduDP24E/bwf+vB3483bgz9uBP28H/rwd+PN24M/bgT9vB/68HfjzduDP24E/bwf+vB3483bgz9uBP28H/rwd+PN24M/bgT9vB/68HfhvPby99/P22M/bUT9v//y83fLz9sbP2wk/b9/7vF3u8/a0z7rNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus26zbrNus17l+Hth/cWw7x3Fua9oTDvfYR5bx/Me9dg3psF894jmPfWwLx3BOa9IzDvHYF57wjMe0dg3jsC894RmPeOwLx3BOa9IzDvHYF57wjMe0dg3jsC894RmPeOwLx3BOa9IzDvHYF57wjMe0dg3jsC894RmPeOwLx3BOa9IzDvHYF57wjMe0dg3jsC894RmPeOwLx3BOa9IzDvHYF57wjMe0dg3jsC894RmPeOwLx3BOa9IzDvHYF57wjMe0dg3jsC894RmPeOwLx3BN5xeG8HzHsLYN6e/3k7/Oft55+3e3/eXv15O/Pn7cOfdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3Wb97bF/Yf3nsW8tyrmvUMx742Jee9HzHsbYt67D/PedJj3XsO89xrmvdcw772Gee81zHuvYd57DfPea5j3XsO89xrmvdcw772Gee81zHuvYd57DfPea5j3XsO89xrmvdcw772Gee81zHuvYd57DfPea5j3XsO89xrmvdcw772Gee81zHuvYd57DfPea5j3XsO89xrmvdcw772Gee81zHuvYd57DfPea5j3XsO89xrmvdcw772Gee81zHuvYd57DfPea5j3XsO89xrefXhvNMx7c2Heewrz3kqY9w7CvDcO5r1fMO9tglm3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3WbdZt1m3eW+IvPfw3g2Z9ybIvPc+5r3lMe+djnlvcMx7X2Pe2xnz3s6Y93bGvLcz5r2dMe/tjHlvZ8x7O2Pe2xnz3s6Y93bGvLcz5r2dMe/tjHlvZ8x7O2Pe2xnz3s6Y93bGvLcz5r2dMe/tjHlvZ8x7O2Pe2xnz3s6Y93bGvLcz5r2dMe/tjHlvZ8x7O2Pe2xnz3s6Y93bGvLcz5r2dMe/tjHlvZ8x7O2Pe2xnz3s6Y93bGvLcz5r2dMe/tjHlvZ8x7O2Pe2xnz3s6Y93bGA4f3Xsa89y/mvW3xwE3/DwSBZPd4nD3RTSiDcQCA8f9JS/loaa0Wk9S7i9hlix2mJrPolQMtZWqKyxIiWUkYy1paRkyj5TO9aLESSxNO5DJq5cZB4raillp2eg5P/e6PEEKUONXNQsQKCZF71uCPTh1OP+pxyl6LlTsD3rDWYV/SiEfNJtx33oQd9VZsUmy4RmrDZbsd+K+qC39uduMXTS++WXHhk9IBHAkM4cUiDx6bG8H9+XHc7p3C5t9prG6cxarJeZxPLOCfrB9/NwTw23AQZ46X8dNXCN8bwvhqcA3H99bxwXsEb1VHcdi1jZeiMTzzuoMntPvY03OI3atH2JlWsFx+ilvkOLYEz7DxIYEl1QWubL3EFb4kLr69xoVj+B9R6Io0AwAAAACAAACgTAAARBUAAHMUAABBDAAAeJx13UOwIE23RuG/8Nm2bdu2bdu2bdu2bdu2bVt3cOsZ5BunzmRHrl6ZNdwrOqL7/O9///9TdbPtZhO87uYgPZ7zYN0cNLh7g4fn3SG6OVT4+JDdHLrHcx4mvoO7N2x43h2umyOEjw/fzRF7POeR4ju4eyOH591Rujla+Pio3Ry9x3MeI76DuzdmeN4dq5vjhI+P3c1xezzn8eI7uHvjh+fdCbo5Ufj4hN2cuMdzniS+g7s3aXjenaybU4SPT97NKXs856niO7h7U4fn3Wm6OV34+LTdnL7Hc54hvoO7N2N43p2pm7OEj8/czVl7POfZ4ju4e7OH5905ujlX+Pic3Zy7x3OeJ76DuzdveN6dr5sLhI/P380FezznheI7uHsLh+fdRbq5WPj4ot1cvMdzXiK+g7u3ZHjeXaqbS4eHL9PNZcPDl+vm8uHhK3RzxfDwlbq5cnj4Kt1cNTx8tW6uHh6+RjfXDA9fq5trh4ev0811w8PX6+b64eEbdHPD8PCNurlxePgm3dw0PHyzbm4eHr5FN7cMD9+qm1uHh2/TzW3Dw7fr5vbh4Tt0c8fw8J26uXN4+C7d3DU8fLdu7h4evkc39wwP36ube4eH79PNfcPD9+vm/uHhB3TzwPDwg7p5cHj4Id08NDz8sG4eHh5+RDePDA8/qptHh4cf081jw8OP6+bx4eEndPPE8PCTunlyePgp3Tw1PPy0bp4eHn5GN88MDz+rm2eHh5/TzXPDw8/r5vnh4Rd088Lw8Iu6eXF4OlovX9rNS4Lr3ct6POcrunl5cPeuDM+7evmq8HG9e3WP53xNfAd379rwvKuXrwsf17vX93jON8R3cPduDM+7evmm8HG9e3OP53xLfAd379bwvKuXbwsfH7+bt/d4znfEd3D37gzPu3r5rvBxvXt3j+d8T3wHd+/e8Lyrl+8LH9e79/d4zg/Ed3D3HgzPu3r5ofBxvftwj+f8SHwHd+/R8Lyrlx8LH9e7j/d4zk/Ed3D3ngzPu3r5qfBxvft0j+f8THwHd+/Z8Lyrl58LH9e7z/d4zi/Ed3D3XgzPu3r5pfBxvfxyj+f8SnwHd+/V8Lyrt18LD9fbr4eH6+03wsP19pvh4Xr7rfBwvf12eLjefic8XG+/Gx6ut98LD9fb74eHr9/ND8LD9faH4eF6+6PwcL39cXi43v4kPFxvfxoerrc/Cw/X25+Hh+vtL8LD9faX4eF6+6vwcL39dXi43v4mPFxvfxserre/Cw/X29+Hh+/fzR/Cw/X2j+Hhevun8HC9/XN4uN7+JTxcb/8aHq63fwsP19u/h4fr7T/Cw/X2n+Hhevuv8HC9/Xd4uN7+Jzxcb/8bHq63/wsP19v+wvq/4Of746r0cL1dV6WH6/KmKj0drZcH6XhblVzvDloN7DkP3s3Bgrs3RHje1ctDho/r3aGqgT3noeM7uHvDhOddvTxs+LjeHa4a2HMePr6DuzdCeN7VyyOGj+vdkaqBPeeR4zu4e6OE5129PGr4uN4drRrYcx49voO7N0Z43tXLY4aP692xqoE957HjO7h744TnXb08bvi43h2vGthzHj++g7s3QXje1csTho/r3YmqgT3nieM7uHuThOddvTxp+Ljenawa2HOePL6DuzdFeN7Vy1OGj+vdqaqBPeep4zu4e9OE5129PG34uN6drhrYc54+voO7N0N43tXDM4aH6+GZqtLD9fDMVenheniWqvRwPTxrVXq4Hp6tKj1cD89elR6uh+eoSg/Xw3NWpYfr4bmq0sPf7+bcVenhH3Rznqr0cD08b1V6uB6eryo9XA/PX5UerocXqEoP18MLVqWH6+GFqtLD9fDCVenheniRqvRwPbxoVXq4Hl6sKj1cDy9elR6uh5eoSg/Xw0tWpYfr4aWq0sP18NJV6eF6eJmq9HA9vGxVergeXq4qPVwPL1+VHq6HV6hKD9fDK1alh+vhlarSw/XwylXp4Xp4lar0cD28alV6uB5erSo9XA+vXpUerofXqEoP18NrVqWH6+G1qtLD9fDaVenhenid8HA9vG54uG5eLzydq2c36Ob6wfXohj2e88bd3Ci4e5uE5109u2n4uB7drMdz3jy+s2nc2yI87+rZLcPH9ehWPZ7z1vGdLePeNuF5V89uGz6uR7fr8Zy3j+9sG/d2CM+7enbH8HE9ulOP57xzfGfHuLdLeN7Vs7uGj+vR3Xo8593jO7vGvT3C866e3TN8XI/u1eM57x3f2TPu7ROed/XsvuHjenS/Hs95//jOvnHvgPC8q2cPDB/Xowf1eM4Hx3cOjHuHhOddPXto+LgePazHcz48vnNo3DsiPO/q1SPDw/XqUeHhevXo8HC9ekx4uF49Njxcrx4XHq5Xjw8P16snhIfr1RPDw/XqSeHhevXk8HC9ekp4uF49NTxcr54WHq5XTw8P16tnhIfr1TPDw/XqWeHhevXs8HC9ek54uF49Nzxcr54XHq5Xzw8P16sXhIfr1QvDw/XqReHhevXi8HC9ekl4uF69NDxcr14WHq5XLw8P16tXhIfr1SvDw/XqVeHhevXq8HC9ek14uF69Njxcr14XHq5Xrw8P16s3hIfr1RvDw/XqTeHhevXm8HC9ekt4uF69NTxcr94WHq5rbw9Ph+rNO7t5R3C9eFeP53xPN+8O7t694XlXb94XPq4X7+/xnB+I79wX9x4Mz7t686Hwcb34cI/n/Eh856G492h43tWbj4WP68XHezznJ+I7j8W9J8Pzrt58KnxcLz7d4zk/E995Ku49G5539eZz4eN68fkez/mF+M5zce/F8LyrN18KH9eLL/d4zq/Ed16Ke6+G5129+Vr4uF58vcdzfiO+81rcezM87+rNt8LH9eLbPZ7zO/Gdt+Leu+F5V0++Fx6uJ98PD9eTH4SH68kPw8P15Efh4Xry4/BwPflJeLie/DQ8XE9+Fh6uJz8PD9eTX4SH68kvw8P15Ffh4Xry6/BwPflNeLie/DY8XE9+Fx6uJ78PD9eTP4SH68kfw8P15E/h4Xry5/BwPflLeLie/DU8XE/+Fh6uJ38PD9eTf4SH68k/w8P15F/h4Xry7/BwPflPeLie/Dc8XE/+Fx6uJ/2DrP+C68mqLj1cT9Z16eF6sqlLD9eTbV16uJ4cpC49XE8OWpcericHq0sP15OD16WH68kh6tLD9eSQdenhenKouvRwPTl0XXq4nhymLj1cdw5bl55O1IPDd3y4uuR6boR6YM95pG6OGNy9kcPzrh4cJXxcz41aD+w5jxbfwd0bPTzv6sExwsf13Jj1wJ7zWPEd3L2xw/OuHhwnfFzPjVsP7DmPF9/B3Rs/PO/qwQnCx/XchPXAnvNE8R3cvYnD864enCR8XM9NWg/sOU8W38Hdmzw87+rBKcLH9dyU9cCe81TxHdy9qcPzrh6cJnxcz01bD+w5Txffwd2bPjzv6r0ZwsP13ox16eF6b6a69HC9N3Nderjem6UuPVzvzVqXHq73ZqtLD9d7s9elh+u9OerSw/XenHXp4Xpvrrr0cL03d116uN6bpy49XO/NW5cervfmq0sP13vz16WH670F6tLD9d6Cdenhem+huvRwvbdwXXq43lukLj1c7y1alx6u9xarSw/Xe4vXpYfrvSXq0sP13pJ16eF6b6m69HC9t3RderjeW6YuPVzvLVuXHq73lqtLD9d7y9elh+u9FerSw/XeinXp4Xpvpbr0cL23cni43lslPFzvrRoervdWCw/Xe6uHh+u9NcLD9d6a4eF6b63wcL23dni43lsnPFzvrRservfWCw/Xe+uHh+vCDcLTcXpto25uGFxvbdzjOW/azU2Cu7dZeN7Va5uHj+utLXo85y3jO5vHva3C865e2zp8XG9t0+M5bxvf2TrubReed/Xa9uHjemuHHs95x/jO9nFvp/C8q9d2Dh/XW7v0eM67xnd2jnu7heddvbZ7+Lje2qPHc94zvrN73NsrPO/qtb3Dx/XWPj2e877xnb3j3n7heVeP7R8erscOCA/XYweGh+uxg8LD9djB4eF67JDwcD12aHi4HjssPFyPHR4erseOCA/XY0eGh+uxo8LD9djR4eF67JjwcD12bHi4HjsuPFyPHR8ersdOCA/XYyeGh+uxk8LD9djJ4eF67JTwcD12ani4HjstPFyPnR4ersfOCA/XY2eGh+uxs8LD9djZ4eF67JzwcD12bni4HjsvPFyPnR8erscuCA/XYxeGh+uxi8LD9djF4eF67JLwcD12aXi4HrssPFyPXR4erseuCA/XY1eGh+uxq8LD9djV4eF67JrwcD12bXi4HrsuPFyPXR8erttuCE9n6ambunljcD10c4/nfGs3bwnu3m3heVdP3R4+rofu6PGc74zv3B737grPu3rq7vBxPXRPj+d8b3zn7rh3X3je1VP3h4/roQd6POcH4zv3x72HwvOunno4fFwPPdLjOT8a33k47j0Wnnf11OPh43roiR7P+cn4zuNx76nwvKuXng4P10vPhIfrpWfDw/XSc+Hheun58HC99EJ4uF56MTxcL70UHq6XXg4P10uvhIfrpVfDw/XSa+Hheun18HC99EZ4uF56MzxcL70VHq6X3g4P10vvhIfrpXfDw/XSe+Hheun98HC99EF4uF76MDxcL30UHq6XPg4P10ufhIfrpU/Dw/XSZ+Hheunz8HC99EV4uF76MjxcL30VHq6Xvg4P10vfhIfrpW/Dw/XSd+Hheun78HC99EN4uF76MTxcL/0UHq6Xfg4P10u/hIfrpV/Dw/XSb+Hheun38HC99Ed4uF76MzxcL/0VHq6X/g4P10v/hIfrqn/D00F6x394+l9wvVI1A3vOTTfr8Nxrw/Ou3hkkfFyvDNoM7DkPFt/B3Rs8PO/qnSHCx/XKkM3AnvNQ8R3cvaHD867eGSZ8XK8M2wzsOQ8X38HdGz487+qdEcLH9cqIzcCe80jxHdy9kcPzrp4ZJTxcz4zalB6uZ0ZrSg/XM6M3pYfrmTGa0sP1zJhN6eF6Zqym9HA9M3ZTerieGacpPVzPjNuUHq5nxmtKD9cz4zelh+uZCZrSw/XMhE3p4Xpmoqb0cD0zcVN6uJ6ZpCk9XM9M2pQermcma0oP1zOTN6WH65kpmtLD9cyUTenhemaqpvRwPTN1U3q4npmmKT1cz0zblB6uZ6ZrSg/XM9M3pYfrmRma0sP1zIxN6eF6Zqam9HA9M3NTeriemaUpPVzPzNqUHq5nZmtKD9czszelh+uZOZrSw/XMnE3p4Xpmrqb0cD0zd1N6uJ6Zpyk9XM/M25Qermfma0oP1zPzN6WH65kFmtLD9cyCTenhemahpvRwPbNwU3q4nlmkKT1czyzalB6uZxZrSg/XPYs3padT9MiS3VwiuJ5YqsdzXqabSwd3b9nwvKtHlgsf1xPL93jOK8R3lot7K4bnXT2yUvi4nli5x3NeJb6zUtxbNTzv6pHVwsf1xOo9nvMa8Z3V4t6a4XlXb6wVHq431g4P1xvrhIfrjXXDw/XGeuHhemP98HC9sUF4uN7YMDxcb2wUHq43Ng4P1xubhIfrjU3Dw/XGZuHhemPz8HC9sUV4uN7YMjxcb2wVHq43tg4P1xvbhIfrjW3Dw/XGduHhemP78HC9sUN4uN7YMTxcb+wUHq43dg4P1xu7hIfrjV3Dw/XGbuHhemP38HC9sUd4uN7YMzxcb+wVHq439g4P1xv7hIfrjX3Dw/XGfuHhemP/8HC9cUB4uN44MDxcbxwUHq43Dg4P1xuHhIfrjUPDw/XGYeHheuPw8HC9cUR4uN44MjxcbxwVHq43jg4P1xvHhIfrjWPDw3XJceHpCL1wQjePD27fn9jjOZ/czZOCu3dKeN7VC6eGj9v3p/V4zqfHd06Ne2eE5129cGb4uH1/Vo/nfHZ858y4d0543tUD54aH64HzwsP1wPnh4XrggvBwPXBheLgeuCg8XA9cHB6uBy4JD9cDl4aH64HLwsP1wOXh4XrgivBwPXBleLgeuCo8XA9cHR6uB64JD9cD14aH64HrwsP1wPXh4XrghvBwPXBjeLgeuCk8XA/cHB6uB24JD9cDt4aH64HbwsP1wO3h4XrgjvBwPXBneLgeuCs8XA/cHR6uB+4JD9cD94aH64H7wsP1wP3h4XrggfBwPfBgeLgeeCg8XA88HB6uBx4JD9cDj4aH64HHwsP1wOPh4XrgifBwPfBkeLgeeCo8XA88HR6uB54JD9cDz4aH64HnwsP1wPPh4XrghfBwPfBieLhueCk8e94+f6WbLwe3j1/t8Zxf7+Zrwd17Izzv2udvho/bx2/1eM5vx3fejHvvhOdd+/rd8HD7+r3wcPv6/fBw+/qD8HD7+sPwcPv6o/Bw+/rj8HD7+pPwcPv60/Bw+/qz8HD7+vPwcPv6i/Bw+/rL8HD7+qvwcPv66/Bw+/qb8HD7+tvwcPv6u/Bw+/r78HD7+ofwcPv6x/Bw+/qn8HD7+ufwcPv6l/Bw+/rX8HD7+rfwcPv69/Bw+/qP8HD7+s/wcPv6r/Bw+/rv8HD7+p/wcPv63/Bw+/q/8HD72i/8/C+4fV21pYfb13Vberh93bSlh9vXbVt6uH09SFt6uH09aFt6uH09WFt6uH09eFt6uH09RFt6uH09ZFt6uH09VFt6uH09dFt6uH09TFt6uH09bFt6uH09XFt6uH09fFt6uH09Qlt6uH09Ylt6uH09Ult6uL0+clt69rB9OGrHR2lLbt+N1pYebt+N3pYebt+N0ZYebt+N2ZYebt+N1ZYebt+N3ZYebt+N05Yebt+N25Yebt+N15Yebt+N35Yebt9N0JYebt9N2JYebt9N1JYebt9N3JYebt9N0pYebt9N2pYebt9N1pYebt9N3pYebt9N0ZYebt9N2ZYebt9N1ZYebt9N3ZYebt9N05Yebt9N25Yebt9N15Yebt9N35Yebt/N0JYebt/N2JYebt/N1JYebt/N3JYebt/N0pYebt/N2pYebt/N1pYebt/N3pYebt/N0ZYebt/N2ZYebt/NFR5u380dHm7fzRMebt/NGx5u380XHm7fzR8ebt8tEB5u3y0YHm7fLRQebt8tHB5u3y0SHm7fLRoebt8tFh5u3y0eHm7fLREebt8tGR5u3y0VHm7fLR0ebt8tEx5uLy4bnj1o3y3fzeWC23crhIfbdyuGh9t3K4WH23crh4fbd6uEh9t3q4aH23erhYfbd6uHh9t3a4SH23drhofbd2uFh9t3a4eH23frhIfbd+uGh9t364X3fz7D0SZ4nF3VUxBGh9lF4aTJOd+J0di2bdu2baNBY9s2Gtu2bdtGk7RBk3/mn/NcvHvf7Jk1635NPvQQ/78p+t+o/w2DT9n/xuHhU/W/SXj41P1vGh4+Tf+bhYdP2//m4eHT9b9FePj0/W8ZHj5D/1uFh8/Y/9bh4TP1v014+Mz9bxsePkv/24WHz9r/9uHhs/W/Q3j47P3vGB4+R/87hYfP2f/O4eFz9b9LePjc/e8aHj5P/7uFh8/b/+7h4fP1v0d4+Pz97xkevkD//wgPX7D/vcLDF+p/7/DwhfvfJzx8kf73DQ9ftP9/hocv1v9+4eGL979/ePgS/R8QHr5k/weGhy/V/0Hh4Uv3f3B4+DL9HxIevmz/h4aHL9f/YeHhy/d/eHj4Cv0fEd6K/a/U/1H9Hxl85f6PDg9fpf9jwsNX7f/Y8PDV+j8uPHz1/o8PD1+j/xPCw9fs/8Tw8LX6Pyk8fO3+Tw4PX6f/U8LD1+3/1PDw9fo/LTx8/f5PDw/foP8zwsP17szwcL07Kzxc784OD9e7c8LD9e7c8HC9Oy88XO/ODw/XuwvCw/XuwvBwvbsoPFzvLg4P17tLwsP17tLwcL37V3i43l0WHq53l4eH690V4eF6d2V4uN5dFR6ud1eHh+vdNeHhendteLjeXRcernfXh4fr3Q3h4Xp3Y3i43t0UHq53N4eH690t4eF6d2t4uN7dFh6ud7eHh+vdHeHhendneLje3RUernd3h4fr3T3h4Xp3b3i43t0XHq5394eH690D4eG6+GB4Oqh3D/f/UHC9eyQ8XO8eDQ/Xu8fCw/Xu8fBwvXsiPFzvngwP17unwsP17unwcL17Jjxc754ND9e758LD9e758HC9eyE8XO9eDA/Xu5fCw/Xu5fBwvXslPFzvXg0P17vXwsP17vXwcL17Izxc794MD9e7t8LD9e7t8HC9eyc8XO/eDQ/Xu/fCw/Xu/fBwvfsgPFzvPgwP17uPwsP17uPwcL37JDxc7z4ND9e7z8LD9e7z8HC9+yI8XO++DA/Xu6/Cw/Xu6/BwvfsmPFzvvg0P17vvwsP17vvwcL37ITxc734MD9e7f4eH691P4eF693N4uN79Eh6ud/8JD9e7/4aH692v4eF691t4uN79Hh6ui3+Ep4N692f//wuud3+Fh+vdEE31cL0bsqkernd/a6qH691QTfVwvRu6qR6ud01TPVzv2qZ6uN4Nmurhetc11cP1bpimerjeDdtUD9e74Zrq4Xo3fFM9XO9GaKqH692ITfVwvRupqR6udyM31cP1bpSmerjejdpUD9e7vzfVw/VutKZ6uN6N3lQP17sxmurhejdmUz1c78Zqqofr3dhN9XC9G6epHq534zbVw/VuvKZ6uN6N31QP17sJmurhejdhUz1c7yZqqofr3cRN9XC9m6SpHq53kzbVw/VusqZ6uN5N3lQP17spmurhejdlUz1c76Zqqofr3dRN9XC9m6apHq530zbVw/VuuqZ6uN5N31QP17sZmurhejdjUz1c72Zqqofr3cxN9XC9m6WpHq53szbVw/VutqZ6uN7N3lQP18U5murpoN7N1fM5m8r1bu6merjezdNUD9e7ecPD9W6+8HC9mz88XO8WCA/XuwXDw/VuofBwvVs4PFzvFgkP17tFw8P1brHwcL1bPDxc75YID9e7JcPD9W6p8HC9Wzo8XO+WCQ/Xu2XDw/VuufBwvVs+PFzvVggP17sVw8P1bqXwcL1bOTxc71YJD9e7VcPD9W618HC9Wz08XO/WCA/XuzXDw/VurfBwvVs7PFzv1gkP17t1w8P1br3wcL1bPzxc7zYID9e7DcPD9W6j8HC92zg8XO82CQ/Xu03Dw/Vus/Bwvds8PFzvtggP17stw8P1bqvwcL3bOjxc77YJD9e7bcPD9W678HC92z48XO92CA/Xux3Dw3Vxp/B0UO926X/n4Hq3a3i43u0WHq53u4eH690e4eF6t2d4uN79Izxc7/YKD9e7vcPD9W6f8HC92zc8XO/+GR6ud/uFh+vd/uHhendAeLjeHRgerncHhYfr3cHh4Xp3SHi43h0aHq53h4WH693h4eF6d0R4uN4dGR6ud0eFh+vd0eHhendMeLjeHRsernfHhYfr3fHh4Xp3Qni43p0YHq53J4WH693J4eF6d0p4uN6dGh6ud6eFh+vd6eHhendGeLjenRkerndnhYfr3dnh4Xp3Tni43p0bHq5354WH69354eF6d0F4uN5dGB6udxeFh+vdxeHhendJeLjeXRoernf/Cg/Xu8vCw/Xu8vBwvbsiPFwXrwxPB/Xu6v6vCq5314SH69214eF6d114uN5dHx6udzeEh+vdjeHhendTeLje3Rwerne3hIfr3a3h4Xp3W3i43t0eHq53d4SH692d4eF6d1d4uN7dHR6ud/eEh+vdveHhendfeLje3R8erncPhIfr3YPh4Xr3UHi43j0cHq53j4SH692j4eF691h4uN49Hh6ud0+Eh+vdk+HhevdUeLjePR0ernfPhIfr3bPh4Xr3XHi43j0fHq53L4SH692L4eF691J4uN69HB6ud6+Eh+vdq+HhevdaeLjevR4erndvhIfr3Zvh4Xr3Vni43r0dHq5374SH69274eF69154uN69Hx6udx+Eh+vdh+HhevdReLgufhyeDurdp/1/ElzvPgsP17vPw8P17ovwcL37Mjxc774KD9e7r8PD9e6b8HC9+zY8XO++Cw/Xu+/Dw/Xuh/BwvfsxPFzv/h0ernc/hYfr3c/h4Xr3S3i43v0nPFzv/hserne/hofr3W/h4Xr3e3i43v0RHq53/wsP17s/w8P17q/wcL0boq0erndDttXD9e5vbfVwvRuqrR6ud0O31cP1rmmrh+td21YP17tBWz1c77q2erjeDdNWD9e7Ydvq4Xo3XFs9XO+Gb6uH690IbfVwvRuxrR6udyO11cP1buS2erjejdJWD9e7Udvq4Xr397Z6uN6N1lYP17vR2+rhejdGWz1c78Zsq4fr3Vht9XC9G7utHq5347TVw/Vu3LZ6uN6N11YP17vx2+rhujhBWz0d1LuJej5hW7neTdxWD9e7Sdrq4Xo3aVs9XO8ma6uH693kbfVwvZuirR6ud1O21cP1bqq2erjeTd1WD9e7adrq4Xo3bVs9XO+ma6uH6930bfVwvZuhrR6udzO21cP1bqa2erjezdxWD9e7Wdrq4Xo3a1s9XO9ma6uH693sbfVwvZujrR6ud3O21cP1bq62erjezd1WD9e7edrq4Xo3b3i43s0XHq5384eH690C4eF6t2B4uN4tFB6udwuHh+vdIuHherdoeLjeLRYerneLh4fr3RLh4Xq3ZHi43i0VHq53S4eH690y4eF6t2x4uN4tFx6ud8uHh+vdCuHherdieLjerRQerncrh4fr3Srh4Xq3ani43q0WHq53q4eH690a4eF6t2Z4uC6uFZ4O6t06/a8dXO/WDQ/Xu/XCw/Vu/fBwvdsgPFzvNgwP17uNwsP1buPwcL3bJDxc7zYND9e7zcLD9W7z8HC92yI8XO+2DA/Xu63Cw/Vu6/BwvdsmPFzvtg0P17vtwsP1bvvwcL3bITxc73YMD9e7ncLD9W7n8HC92yU8XO92DQ/Xu93Cw/Vu9/BwvdsjPFzv9gwP17t/hIfr3V7h4Xq3d3i43u0THq53+4aH690/w8P1br/wcL3bPzxc7w4ID9e7A8PD9e6g8HC9Ozg8XO8OCQ/Xu0PDw/XusPBwvTs8PFzvjggP17sjw8P17qjwcL07Ojxc744JD9e7Y8PD9e648HC9Oz48XO9OCA/XuxPDw3XxpPB0UO9O6f/k4Hp3ani43p0WHq53p4eH690Z4eF6d2Z4uN6dFR6ud2eHh+vdOeHhendueLjenRcernfnh4fr3QXh4Xp3YXi43l0UHq53F4eH690l4eF6d2l4uN79Kzxc7y4LD9e7y8PD9e6K8HC9uzI8XO+uCg/Xu6vDw/XumvBwvbs2PFzvrgsP17vrw8P17obwcL27MTxc724KD9e7m8PD9e6W8HC9uzU8XO9uCw/Xu9vDw/XujvBwvbszPFzv7goP17u7w8P17p7wcL27Nzxc7+4LD9e7+8PD9e6B8HC9ezA8XO8eCg/Xu4fDw/XukfBwvXs0PFzvHgsP17vHw8P17onwcL17Mjxc754KD9fFp8PTQb17tv9nguvdc+Hhevd8eLjevRAerncvhofr3Uvh4Xr3cni43r0SHq53r4aH691r4eF693p4uN69ER6ud2+Gh+vdW+Hhevd2eLjevRMernfvhofr3Xvh4Xr3fni43n0QHq53H4aH691H4eF693F4uN59Eh6ud5+Gh+vdZ+Hhevd5eLjefREerndfhofr3Vfh4Xr3dXi43n0THq5334aH69134eF69314uN79EB6udz+Gh+vdv8PD9e6n8HC9+zk8XO9+CQ/Xu/+Eh+vdf8PD9e7X8HC9+y08XO9+Dw/Xuz/Cw/Xuf+HhevdneLje/RUerndDDKqH692Qg+rheve3QfVwvRtqUD1c74YeVA/Xu2ZQPVwX20H1dFDvup4PBpXr3TCD6uF6N+ygerjeDTeoHq53ww+qh+vdCIPq4Xo34qB6uN6NNKgerncjD6qH690og+rhejfqoHq43v19UD1c70YbVA/Xu9EH1cP1boxB9XC9G3NQPVzvxhpUD9e7sQfVw/VunEH1cL0bd1A9XO/GG1QP17vxB9XD9W6CQfVwvZtwUD1c7yYaVA/Xu4kH1cP1bpJB9XC9m3RQPVzvJhtUD9e7yQfVw/VuikH1cL2bclA9XO+mGlQP17upB9XD9W6aQfVwvZt2UD1c76YbVA/Xu+kH1cP1boZB9XC9m3FQPVzvZhpUD9e7mQfVw/VulkH1cL2bdVA9XO9mG1QP17vZB9XD9W6OQfVwvZtzUD1c7+YaVA/Xu7kH1cP1bp5B9XC9mzc8XO/mCw/Xu/nDw/VugfBwvVswPFwXFwpPB/Vukf4XDq53i4aH691i4eF6t3h4uN4tER6ud0uGh+vdUuHherd0eLjeLRMernfLhofr3XLh4Xq3fHi43q0QHq53K4aH691K4eF6t3J4uN6tEh6ud6uGh+vdauHherd6eLjerREerndrhofr3Vrh4Xq3dni43q0THq5364aH69164eF6t354uN5tEB6udxuGh+vdRuHherdxeLjebRIernebhofr3Wbh4Xq3eXi43m0RHq53W4aH691W4eF6t3V4uN5tEx6ud9uGh+vdduHherd9eLje7RAernc7hofr3U7h4Xq3c3i43u0SHq53u4aH691u4eF6t3t4uN7tER6ud3uGh+vdP8LD9W6v8HBd3Ds8HdS7ffvfJ7je/TM8XO/2Cw/Xu/3Dw/XugPBwvTswPFzvDgoP17uDw8P17pDwcL07NDxc7w4LD9e7w8PD9e6I8HC9OzI8XO+OCg/Xu6PDw/XumPBwvTs2PFzvjgsP17vjw8P17oTwcL07MTxc704KD9e7k8PD9e6U8HC9OzU8XO9OCw/Xu9PDw/XujPBwvTszPFzvzgoP17uzw8P17pzwcL07Nzxc784LD9e788PD9e6C8HC9uzA8XO8uCg/Xu4vDw/XukvBwvbs0PFzv/hUerneXhYfr3eXh4Xp3RXi43l0ZHq53V4WH693V4eF6d014uN5dGx6ud9eFh+vd9eHhendDeLje3Rgernc3hYfr4s3h6aDe3dr/LcH17rbwcL27PTxc7+4ID9e7O8PD9e6u8HC9uzs8XO/uCQ/Xu3vDw/XuvvBwvbs/PFzvHggP17sHw8P17qHwcL17ODxc7x4JD9e7R8PD9e6x8HC9ezw8XO+eCA/XuyfDw/XuqfBwvXs6PFzvngkP17tnw8P17rnwcL17Pjxc714ID9e7F8PD9e6l8HC9ezk8XO9eCQ/Xu1fDw/XutfBwvXs9PFzv3ggP17s3w8P17q3wcL17Ozxc794JD9e7d8PD9e698HC9ez88XO8+CA/Xuw/Dw/Xuo/Bwvfs4PFzvPgkP17tPw8P17rPwcL37PDxc774ID9e7L8PD9e6r8HC9+zo8XO++CQ/XxW/D00G9+77/74Lr3Q/h4Xr3Y3i43v07PFzvfgoP17ufw8P17pfwcL37T3i43v03PFzvfg0P17vfwsP17vfwcL37Izxc7/4XHq53f4aH691f4eF6N0RXPVzvhuyqh+vd37rq4Xo3VFc9XO+G7qqH613TVQ/Xu7arHq53g656uN51XfVwvRumqx6ud8N21cP1briuerjeDd9VD9e7Ebrq4Xo3Ylc9XO9G6qqH693IXfVwvRulqx6ud6N21cP17u9d9XC9G62rHq53o3fVw/VujK56uN6N2VUP17uxuurhejd2Vz1c78bpqofr3bhd9XC9G6+rHq5343fVw/Vugq56uN5N2FUP17uJuurhejdxVz1c7ybpqofr3aRd9XC9m6yrHq53k3fVw/Vuiq56uN5N2VUP18WpuurpoN5N0/Opu8r1btquerjeTddVD9e76bvq4Xo3Q1c9XO9m7KqH691MXfVwvZu5qx6ud7N01cP1btauerjezdZVD9e72bvq4Xo3R1c9XO/m7KqH691cXfVwvZu7qx6ud/N01cP1bt7wcL2bLzxc7+YPD9e7BcLD9W7B8HC9Wyg8XO8WDg/Xu0XCw/Vu0fBwvVssPFzvFg8P17slwsP1bsnwcL1bKjxc75YOD9e7ZcLD9W7Z8HC9Wy48XO+WDw/XuxXCw/VuxfBwvVspPFzvVg4P17tVwsP1btXwcL1bLTxc71YPD9e7NcLD9W7N8HC9Wys8XO/WDg/Xu3XCw/Vu3fBwvVsvPFzv1g8P17sNwsP1bsPwcL3bKDxc7zYOD9fFTcLTQb3brP9Ng+vd5uHherdFeLjebRkerndbhYfr3dbh4Xq3TXi43m0bHq5324WH69324eF6t0N4uN7tGB6udzuFh+vdzuH9H1LLRXF4nF3VQxAwxgIE4TjZjW3btm3btm3btm3btu38sW3nVb3a77Azl6nq6nvPPtRA/98c7Xdqv2PwOdvvHB4+V/tdwsPnbr9rePg87XcLD5+3/e7h4fO13yM8fP72e4aHL9B+r/DwBdvvHR6+UPt9wsMXbr9vePgi7fcLD1+0/f7h4Yu1PyA8fPH2B4aHL9H+oPDwJdsfHB6+VPtDwsOXbn9oePgy7Q8LD1+2/eHh4cu1PyI8fPn2R4aHr9D+qPDwFdsfHR6+UvtjwsNXbn9sePgq7Y8LD1+1/fHh4au1PyE8fPX2J4aHr9H+pPDwNdufHB6+VvtTwsPXbn9qePg67U8LD1+3/enh4eu1PyM8fP32Z4aHb9D+rPDwDdufHR6+Uftzwtu4/Sbtz2t/bvBN258fHr5Z+wvCwzdvf2F4+BbtLwoP37L9xeHhW7W/JDx86/aXhodv0/6y8PBt218eHr5d+yvCw7dvf2V4+A7trwoP17urw8P17prwcL27Njxc764LD9e768PD9e6G8HC9uzE8XO9uCg/Xu5vDw/XulvBwvbs1PFzvbgsP17vbw8P17o7wcL27Mzxc7+4KD9e7u8PD9e6e8HC9uzc8XO/uCw/Xu/vDw/XugfBwvXswPFzvHgoP17uHw8P17pHwcL17NDxc7x4LD9e7x8PD9e6J8HC9ezI8XO+eCg/Xu6fDw/XumfBwvXs2PFzvngsP17vnw8P17oXwcL17MTxc714KD9e7l8PD9e6V8HC9ezU8XBdfC08H9e6N9q8H17s3w8P17q3wcL17Ozxc794JD9e7d8PD9e698HC9GxAernfvh4fr3Qfh4Xr3YXi43n0UHq53H4eH690n4eF692l4uN59Fh6ud5+Hh+vdF+HhevdleLjefRUerndfh4fr3Tfh4Xr3bXi43n0XHq5334eH690P4eF692N4uN79FB6udz+Hh+vdL+HhevdreLje/RYerne/h4fr3R/h4Xr3Z3i43v0VHq53f4eH690/4eF69294uN79Fx6udwOV3sP1buDSe7jeDVJ6D9e7QUvv4Xo3WOk9XO8GL72H690QpfdwvRuy9B6ud0OV3sP1rpTew/Wult7D9W7o0nu43g1Teg/Xu2FL7+F6N1zpPVzvhi+9h+viCKX3dFDvRmp8xNJzvRu59B6ud6OU3sP1btTSe7jejVZ6D9e70Uvv4Xo3Ruk9XO/GLL2H691YpfdwvRu79B6ud+OU3sP1btzSe7jejVd6D9e78Uvv4Xo3Qek9XO8mLL2H691EpfdwvZu49B6ud5OU3sP1btLSe7jeTVZ6D9e7yUvv4Xo3Rek9XO+mLL2H691UpfdwvZu69B6ud9OU3sP1btrSe7jeTVd6D9e76Uvv4Xo3Q+k9XO9mLL2H691MpfdwvZu59B6ud7OU3sP1btbSe7jezVZ6D9e72Uvv4Xo3R+k9XO/mLL2H691cpfdwvZs7PFzv5gkP17t5w8P1br7wcL2bPzxc7xYID9e7BcPD9W6h8HC9Wzg8XO8WCQ/Xu0XDw/VusfBwvVs8PFzvlggP17slw8N1canwdFDvlmm/dHC9WzY8XO+WCw/Xu+XDw/VuhfBwvVsxPFzvVgoP17uVw8P1bpXwcL1bNTxc71YLD9e71cPD9W6N8HC9WzM8XO/WCg/Xu7XDw/VunfBwvVs3PFzv1gsP17v1w8P1boPwcL3bMDxc7zYKD9e7jcPD9W6T8HC92zQ8XO82Cw/Xu83Dw/Vui/BwvdsyPFzvtgoP17utw8P1bpvwcL3bNjxc77YLD9e77cPD9W6H8HC92zE8XO92Cg/Xu53Dw/Vul/Bwvds1PFzvdgsP17vdw8P1bo/wcL3bMzxc7/YKD9e7vcPD9W6f8HC92zc8XO/2Cw/Xu/3Dw/XugPBwvTswPFzvDgoP17uDw8N18ZDwdFDvDmt/aHC9Ozw8XO+OCA/XuyPDw/XuqPBwvTs6PFzvjgkP17tjw8P17rjwcL07Pjxc704ID9e7E8PD9e6k8HC9Ozk8XO9OCQ/Xu1PDw/XutPBwvTs9PFzvzggP17szw8P17qzwcL07Ozxc784JD9e7c8PD9e688HC9Oz88XO8uCA/XuwvDw/XuovBwvbs4PFzvLgkP17tLw8P17rLwcL27PDxc764ID9e7K8PD9e6q8HC9uzo8XO+uCQ/Xu2vDw/XuuvBwvbs+PFzvbggP17sbw8P17qbwcL27OTxc724JD9e7W8PD9e628HC9uz08XO/uCA/XuzvDw/XurvBwvbs7PFzv7gkP17t7w8N18b7wdFDvHmh/f3C9ezA8XO8eCg/Xu4fDw/XukfBwvXs0PFzvHgsP17vHw8P17onwcL17Mjxc754KD9e7p8PD9e6Z8HC9ezY8XO+eCw/Xu+fDw/XuhfBwvXsxPFzvXgoP17uXw8P17pXwcL17NTxc714LD9e718PD9e6N8HC9ezM8XO/eCg/Xu7fDw/XunfBwvXs3PFzv3gsP17sB4eF69354uN59EB6udx+Gh+vdR+HhevdxeLjefRIernefhofr3Wfh4Xr3eXi43n0RHq53X4aH691X4eF693V4uN59Ex6ud9+Gh+vdd+Hhevd9eLje/RAernc/hofr3U/h4Xr3c3i43v0SHq53v4aH691v4eG6+Ht4Oqh3f7b/I7je/RUernd/h4fr3T/h4Xr3b3i43v0XHq53A9Xew/Vu4Np7uN4NUnsP17tBa+/hejdY7T1c7wavvYfr3RC193C9G7L2Hq53Q9Xew/Wu1N7D9a7W3sP1bujae7jeDVN7D9e7YWvv4Xo3XO09XO+Gr72H690ItfdwvRux9h6udyPV3sP1buTae7jejVJ7D9e7UWvv4Xo3Wu09XO9Gr72H690YtfdwvRuz9h6ud2PV3sP1buzae7jejVN7D9e7cWvv4Xo3Xu09XO/Gr72H690EtfdwvZuw9h6udxPV3sP1buLae7jeTVJ7D9e7SWvv4Xo3We09XO8mr72H690UtfdwvZuy9h6ud1PV3sP1burae7jeTVN7D9e7aWvv4Xo3Xe09XO+mr72H690MtfdwvZux9h6uizPV3tNBvZul8Zlrz/Vu1tp7uN7NVnsP17vZa+/hejdH7T1c7+asvYfr3Vy193C9mzs8XO/mCQ/Xu3nDw/VuvvBwvZs/PFzvFggP17sFw8P1bqHwcL1bODxc7xYJD9e7RcPD9W6x8HC9Wzw8XO+WCA/XuyXDw/VuqfBwvVs6PFzvlgkP17tlw8P1brnwcL1bPjxc71YID9e7FcPD9W6l8HC9Wzk8XO9WCQ/Xu1XDw/VutfBwvVs9PFzv1ggP17s1w8P1bq3wcL1bOzxc79YJD9e7dcPD9W698HC9Wz88XO82CA/Xuw3Dw/Vuo/Bwvds4PFzvNgkP17tNw8P1brPwcL3bPDxc77YID9e7LcPD9W6r8HC92zo8XBe3CU8H9W679tsG17vtw8P1bofwcL3bMTxc73YKD9e7ncPD9W6X8HC92zU8XO92Cw/Xu93Dw/Vuj/BwvdszPFzv9goP17u9w8P1bp/wcL3bNzxc7/YLD9e7/cPD9e6A8HC9OzA8XO8OCg/Xu4PDw/XukPBwvTs0PFzvDgsP17vDw8P17ojwcL07Mjxc744KD9e7o8PD9e6Y8HC9OzY8XO+OCw/Xu+PDw/XuhPBwvTsxPFzvTgoP17uTw8P17pTwcL07NTxc704LD9e708PD9e6M8HC9OzM8XO/OCg/Xu7PDw/XunPBwvTs3PFzvzgsP17vzw8P17oLwcL27MDxc7y4KD9e7i8PD9e6S8HC9uzQ8XBcvC08H9e6K9pcH17srw8P17qrwcL27Ojxc764JD9e7a8PD9e668HC9uz48XO9uCA/XuxvDw/XupvBwvbs5PFzvbgkP17tbw8P17rbwcL27PTxc7+4ID9e7O8PD9e6u8HC9uzs8XO/uCQ/Xu3vDw/XuvvBwvbs/PFzvHggP17sHw8P17qHwcL17ODxc7x4JD9e7R8PD9e6x8HC9ezw8XO+eCA/XuyfDw/XuqfBwvXs6PFzvngkP17tnw8P17rnwcL17Pjxc714ID9e7F8PD9e6l8HC9ezk8XO9eCQ/Xu1fDw/XutfBwvXs9PFzv3ggP17s3w8P17q3wcL17Ozxc794JD9e7d8PD9e698HC9GxAerovvh/c/hc0wHg==AQAAAACAAAAoUwAAzQ0AAA==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AQAAAACAAABlCgAAGgAAAA==eJztwSEBAAAAwyC9/oVf4hIoAAA4G4r2XY4=
26
+ </AppendedData>
27
+ </VTKFile>
CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/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/Kn0p28/simulation0585_Kn0p28Ma5p4/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 0.28
13
+ variable Ma equal 5.4
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/Kn0p28/simulation0585_Kn0p28Ma5p4/cylinder.surf ADDED
@@ -0,0 +1,410 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ surf file from Pointwise
2
+
3
+ 200 points
4
+ 200 lines
5
+
6
+ Points
7
+
8
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CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/gas.species ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Species data
2
+
3
+ # species name
4
+ # molecular weight (atomic mass units, e.g. 16 for oxygen)
5
+ # molecular mass (kg)
6
+ # rotational degrees of freedom (integer, unitless)
7
+ # inverse rotational relaxtion number (unitless)
8
+ # vibrational degrees of freedom (integer, unitless)
9
+ # inverse vibrational relaxation number (unitless)
10
+ # vibrational temperature (K)
11
+ # species weight (unitless)
12
+ # multiple of electon charge (1 for a proton)
13
+
14
+ Ar 39.95 6.63E-26 0 0.0 0 0.0 0.0 1.0 0.0
CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/gas.vhs ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ # VHS collision model parameters for each species
2
+
3
+ # species name
4
+ # diameter (m)
5
+ # omega (unitless)
6
+ # tref (referenced temperature)
7
+ # alpha (unitless)
8
+
9
+ Ar 4.17e-10 0.81 273 1.0
CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/grid/Grid_0_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/grid/Grid_1_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/grid/Grid_2_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/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/Kn0p28/simulation0585_Kn0p28Ma5p4/grid/Grid_3_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/grid/final-grid.dat ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/log.sparta ADDED
@@ -0,0 +1,319 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 0.28
17
+ variable Ma equal 5.4
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 0.28*${L}
23
+ variable mfp equal 0.28*1
24
+ variable cpmfp equal 4
25
+ variable nden equal 1.0/sqrt(2.0)/${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}*${Kn})
29
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.28/${cpmfp}*${Kn})
30
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.28/4*${Kn})
31
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.28/4*0.28)
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 5.4*${sos}
38
+ variable vo equal 5.4*307.815564238681
39
+ variable vx equal ${vo}*cos(${theta}*2*PI/360)
40
+ variable vx equal 1662.20404688888*cos(${theta}*2*PI/360)
41
+ variable vx equal 1662.20404688888*cos(0*2*PI/360)
42
+ variable vy equal ${vo}*sin(${theta}*2*PI/360)
43
+ variable vy equal 1662.20404688888*sin(${theta}*2*PI/360)
44
+ variable vy equal 1662.20404688888*sin(0*2*PI/360)
45
+ variable ppc equal 30
46
+ variable xncells equal (${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)/0.28*${cpmfp}
50
+ variable xncells equal (6--5)/0.28*4
51
+ variable yncells equal (${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)/0.28*${cpmfp}
55
+ variable yncells equal (5--5)/0.28*4
56
+ variable Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
57
+ variable Fnum equal 6.60399822965135e+19*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
58
+ variable Fnum equal 6.60399822965135e+19*(6-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
59
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
60
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(5-${ymin})/${ppc}/${xncells}/${yncells}
61
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(5--5)/${ppc}/${xncells}/${yncells}
62
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(5--5)/30/${xncells}/${yncells}
63
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(5--5)/30/157.142857142857/${yncells}
64
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(5--5)/30/157.142857142857/142.857142857143
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}/${xncells}/10/4
68
+ variable tstep equal (--5+6)/1662.20404688888/${xncells}/10/4
69
+ variable tstep equal (--5+6)/1662.20404688888/157.142857142857/10/4
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 6.60399822965135e+19
81
+ global fnum ${Fnum}
82
+ global fnum 1.07865304417639e+16
83
+ timestep ${tstep}
84
+ timestep 1.05281899853117e-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 157.142857142857 ${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 157.142857142857 142.857142857143 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 97600 child grid cells
100
+ CPU time = 0.126525 secs
101
+ create/ghost percent = 0.951505 99.0485
102
+ balance_grid rcb cell
103
+ Balance grid migrated 97380 cells
104
+ CPU time = 0.112671 secs
105
+ reassign/sort/migrate/ghost percent = 52.7136 0.0302563 7.704 39.5521
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 1662.20404688888 ${vy} 0.0 temp ${To}
110
+ mixture air Ar vstream 1662.20404688888 0 0.0 temp ${To}
111
+ mixture air Ar vstream 1662.20404688888 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
+ 456 0 = cells overlapping surfs, overlap cells with unmarked corner pts
121
+ 87188 9956 456 = cells outside/inside/overlapping surfs
122
+ 456 = surf cells with 1,2,etc splits
123
+ 109.215 109.215 = cell-wise and global flow volume
124
+ CPU time = 0.115575 secs
125
+ read/check/sort/surf2grid/ghost/inout/particle percent = 20.7446 20.1428 2.27928 20.6641 36.1692 5.53698 0.113674
126
+ surf2grid time = 0.0238826 secs
127
+ map/comm1/comm2/comm3/comm4/split percent = 15.2733 23.8621 5.9099 1.69113 11.2966 6.6114
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 1938 cells
133
+ CPU time = 0.0541184 secs
134
+ reassign/sort/migrate/ghost percent = 5.23597 0.0594419 17.985 76.7196
135
+ create_particles air n 0
136
+ WARNING: Created unexpected # of particles: 668660 versus 668661 (../create_particles.cpp:346)
137
+ Created 668660 particles
138
+ CPU time = 0.0164353 secs
139
+ stats 10000
140
+ stats_style step cpu np nattempt ncoll nscoll npave nscollave
141
+ run 200000
142
+ Memory usage per proc in Mbytes:
143
+ particles (ave,min,max) = 1.79297 0 3.375
144
+ grid (ave,min,max) = 4.297 1.51379 7.13879
145
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
146
+ total (ave,min,max) = 6.11057 3.22189 8.84689
147
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
148
+ 0 0 668660 0 0 0 0 0
149
+ 10000 17.792163 738049 12722 11113 20 696089.17 19.8585
150
+ 20000 40.006517 745511 12795 11301 24 719892.48 20.0974
151
+ 30000 62.323989 746098 12816 11197 17 728656.96 20.195933
152
+ 40000 85.226974 746672 12941 11378 28 733127.16 20.250275
153
+ 50000 106.71174 745298 12879 11330 29 735626.43 20.2499
154
+ 60000 129.07979 745769 12815 11211 16 737332.77 20.270067
155
+ 70000 152.58276 746685 12871 11239 23 738639.26 20.294071
156
+ 80000 174.59881 745808 12938 11320 21 739613.78 20.309963
157
+ 90000 197.07484 745827 12961 11372 26 740350.17 20.312011
158
+ 100000 219.47781 746773 12952 11323 14 740951.37 20.326
159
+ 110000 241.687 746606 13097 11488 29 741451.36 20.329873
160
+ 120000 264.63421 745923 12876 11275 18 741837.04 20.331642
161
+ 130000 286.62438 745508 13067 11406 26 742147.8 20.333562
162
+ 140000 308.95525 746211 12918 11318 22 742402.15 20.339279
163
+ 150000 332.42823 745940 12909 11311 21 742654.97 20.342953
164
+ 160000 354.60631 745638 12822 11245 26 742875.44 20.345175
165
+ 170000 376.69609 745842 12966 11312 12 743066.88 20.348147
166
+ 180000 399.75798 745350 12950 11299 22 743212.45 20.350728
167
+ 190000 421.95988 746610 12973 11339 24 743365.79 20.352426
168
+ 200000 444.86777 746477 12936 11301 16 743531.08 20.35403
169
+ Loop time of 444.869 on 128 procs for 200000 steps with 746477 particles
170
+
171
+ MPI task timing breakdown:
172
+ Section | min time | avg time | max time |%varavg| %total
173
+ ---------------------------------------------------------------
174
+ Move | 0.022431 | 18.661 | 123.65 | 576.6 | 4.19
175
+ Coll | 0.48511 | 17.885 | 175.55 | 628.9 | 4.02
176
+ Sort | 0.16331 | 3.4684 | 31.051 | 264.5 | 0.78
177
+ Comm | 72.858 | 107.5 | 119.84 | 95.2 | 24.16
178
+ Modify | 0.020904 | 0.15057 | 2.8802 | 108.5 | 0.03
179
+ Output | 0.0067739 | 0.021028 | 0.023177 | 1.6 | 0.00
180
+ Other | | 297.2 | | | 66.80
181
+
182
+ Particle moves = 148706216761 (149B)
183
+ Cells touched = 155360882036 (155B)
184
+ Particle comms = 248624616 (249M)
185
+ Boundary collides = 0 (0K)
186
+ Boundary exits = 24046066 (24M)
187
+ SurfColl checks = 237547559 (238M)
188
+ SurfColl occurs = 4070806 (4.07M)
189
+ Surf reactions = 0 (0K)
190
+ Collide attempts = 3033993264 (3.03B)
191
+ Collide occurs = 2357219828 (2.36B)
192
+ Reactions = 0 (0K)
193
+ Particles stuck = 0
194
+ Axisymm bad moves = 0
195
+
196
+ Particle-moves/CPUsec/proc: 2.61148e+06
197
+ Particle-moves/step: 743531
198
+ Cell-touches/particle/step: 1.04475
199
+ Particle comm iterations/step: 1
200
+ Particle fraction communicated: 0.00167192
201
+ Particle fraction colliding with boundary: 0
202
+ Particle fraction exiting boundary: 0.000161702
203
+ Surface-checks/particle/step: 0.00159743
204
+ Surface-collisions/particle/step: 2.73748e-05
205
+ Surf-reactions/particle/step: 0
206
+ Collision-attempts/particle/step: 0.0204026
207
+ Collisions/particle/step: 0.0158515
208
+ Reactions/particle/step: 0
209
+
210
+ Particles: 5831.85 ave 41294 max 0 min
211
+ Histogram: 84 16 6 10 2 6 0 2 0 2
212
+ Cells: 762.5 ave 763 max 762 min
213
+ Histogram: 64 0 0 0 0 0 0 0 0 64
214
+ GhostCell: 19721.7 ave 36096 max 1099 min
215
+ Histogram: 20 10 12 10 18 2 6 4 16 30
216
+ EmptyCell: 0 ave 0 max 0 min
217
+ Histogram: 128 0 0 0 0 0 0 0 0 0
218
+ Surfs: 200 ave 200 max 200 min
219
+ Histogram: 128 0 0 0 0 0 0 0 0 0
220
+ GhostSurf: 0 ave 0 max 0 min
221
+ Histogram: 128 0 0 0 0 0 0 0 0 0
222
+ compute 1 grid all air n nrho massrho u v w
223
+ compute 2 grid all air trot
224
+ compute 3 tvib/grid all air
225
+ compute 4 thermal/grid all air press temp
226
+ fix 1 ave/grid all 1 ${nave} ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
227
+ fix 1 ave/grid all 1 10000 ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
228
+ fix 1 ave/grid all 1 10000 10000 c_1[*] c_4[*] c_2[*] c_3[*] ave running
229
+ dump 1 grid all ${noutput} output/grid.*.dat id xc yc f_1[*]
230
+ dump 1 grid all 300000 output/grid.*.dat id xc yc f_1[*]
231
+ dump_modify 1 format float %12.5g
232
+ compute 5 surf all air n press px py shx shy fx fy etot erot evib
233
+ fix 2 ave/surf all 1 ${nave} ${nave} c_5[*] ave running
234
+ fix 2 ave/surf all 1 10000 ${nave} c_5[*] ave running
235
+ fix 2 ave/surf all 1 10000 10000 c_5[*] ave running
236
+ dump 2 surf all ${noutput} output/surf.*.dat id v1x v1y v2x v2y f_2[*]
237
+ dump 2 surf all 300000 output/surf.*.dat id v1x v1y v2x v2y f_2[*]
238
+ dump_modify 2 format float %12.5g
239
+ compute 6 lambda/grid f_1[2] f_1[8] Ar kx
240
+ dump 3 grid all ${noutput} output/lambdakn.*.dat id xc yc c_6[*]
241
+ dump 3 grid all 300000 output/lambdakn.*.dat id xc yc c_6[*]
242
+ dump_modify 3 format float %12.5g
243
+ run 100000
244
+ Memory usage per proc in Mbytes:
245
+ particles (ave,min,max) = 1.8457 0 5.0625
246
+ grid (ave,min,max) = 4.297 1.51379 7.13879
247
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
248
+ total (ave,min,max) = 6.41953 3.47786 9.10336
249
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
250
+ 200000 0 746477 12936 11301 0 0 0
251
+ 210000 39.604912 745870 12906 11292 22 745820.9 20.4079
252
+ 220000 79.821286 745881 13028 11394 31 745794.18 20.36695
253
+ 230000 121.61496 746506 12874 11230 14 745973.74 20.369733
254
+ 240000 161.52836 745995 12889 11327 22 746067.66 20.362375
255
+ 250000 202.34281 746337 13019 11423 19 746139.63 20.37056
256
+ 260000 242.44984 746017 12996 11371 18 746137.59 20.364367
257
+ 270000 282.04087 746696 12992 11455 15 746188.53 20.358143
258
+ 280000 322.50427 745917 12872 11255 29 746226.46 20.358387
259
+ 290000 362.43888 746006 13039 11476 22 746208.25 20.361767
260
+ 300000 402.04834 745595 12747 11155 19 746150.18 20.36131
261
+ Loop time of 402.048 on 128 procs for 100000 steps with 745595 particles
262
+
263
+ MPI task timing breakdown:
264
+ Section | min time | avg time | max time |%varavg| %total
265
+ ---------------------------------------------------------------
266
+ Move | 0.012494 | 9.4521 | 62.11 | 408.4 | 2.35
267
+ Coll | 0.24435 | 9.1593 | 95.582 | 459.4 | 2.28
268
+ Sort | 0.09862 | 1.807 | 12.92 | 185.0 | 0.45
269
+ Comm | 45.349 | 62.815 | 69.902 | 66.5 | 15.62
270
+ Modify | 3.4605 | 25.652 | 159.41 | 615.4 | 6.38
271
+ Output | 0.044827 | 0.046417 | 0.04995 | 0.5 | 0.01
272
+ Other | | 293.1 | | | 72.91
273
+
274
+ Particle moves = 74615018050 (74.6B)
275
+ Cells touched = 77951271382 (78B)
276
+ Particle comms = 124626456 (125M)
277
+ Boundary collides = 0 (0K)
278
+ Boundary exits = 12065561 (12.1M)
279
+ SurfColl checks = 119100612 (119M)
280
+ SurfColl occurs = 2036131 (2.04M)
281
+ Surf reactions = 0 (0K)
282
+ Collide attempts = 1530654951 (1.53B)
283
+ Collide occurs = 1188979038 (1.19B)
284
+ Reactions = 0 (0K)
285
+ Particles stuck = 0
286
+ Axisymm bad moves = 0
287
+
288
+ Particle-moves/CPUsec/proc: 1.4499e+06
289
+ Particle-moves/step: 746150
290
+ Cell-touches/particle/step: 1.04471
291
+ Particle comm iterations/step: 1
292
+ Particle fraction communicated: 0.00167026
293
+ Particle fraction colliding with boundary: 0
294
+ Particle fraction exiting boundary: 0.000161704
295
+ Surface-checks/particle/step: 0.0015962
296
+ Surface-collisions/particle/step: 2.72885e-05
297
+ Surf-reactions/particle/step: 0
298
+ Collision-attempts/particle/step: 0.020514
299
+ Collisions/particle/step: 0.0159348
300
+ Reactions/particle/step: 0
301
+
302
+ Particles: 5824.96 ave 41343 max 0 min
303
+ Histogram: 84 16 6 10 2 6 0 2 0 2
304
+ Cells: 762.5 ave 763 max 762 min
305
+ Histogram: 64 0 0 0 0 0 0 0 0 64
306
+ GhostCell: 19721.7 ave 36096 max 1099 min
307
+ Histogram: 20 10 12 10 18 2 6 4 16 30
308
+ EmptyCell: 0 ave 0 max 0 min
309
+ Histogram: 128 0 0 0 0 0 0 0 0 0
310
+ Surfs: 200 ave 200 max 200 min
311
+ Histogram: 128 0 0 0 0 0 0 0 0 0
312
+ GhostSurf: 0 ave 0 max 0 min
313
+ Histogram: 128 0 0 0 0 0 0 0 0 0
314
+ write_grid grid/final-grid.dat
315
+ grid cells = 97600
316
+ CPU time = 0.0138704 secs
317
+ write_surf surf/geom.surf
318
+ surf elements = 200
319
+ CPU time = 0.00156067 secs
CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/mir.txt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ dimension 2
2
+ create_box -5.0 6.0 -5.0 5.0 -0.5 0.5
3
+ read_grid grid/final-grid.dat
CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/output/lambdakn.300000.dat ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/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 0.00416 0.13307 -0.13305 0.0020902 3.2847e-05 0.0020909 -0.0020894 6.5673e-05 25.731 0 0
11
+ 129 -0.31871 0.38526 -0.30645 0.39508 0.16359 5.3804 3.364 -4.199 0.73491 0.58878 0.064384 -0.056707 1280.5 0 0
12
+ 2 0.49975 -0.015705 0.49901 -0.031395 0.00371 0.11647 -0.11634 0.0054865 7.4338e-05 0.0015763 -0.0018262 0.00011094 22.943 0 0
13
+ 130 -0.30645 0.39508 -0.29389 0.40451 0.15802 5.2156 3.1316 -4.1709 0.79829 0.59937 0.061728 -0.056099 1273.8 0 0
14
+ 3 0.49901 -0.031395 0.49778 -0.047054 0.00405 0.12945 -0.12905 0.010156 -0.00042647 -0.0054188 -0.0020337 7.4416e-05 29.374 0 0
15
+ 131 -0.29389 0.40451 -0.28104 0.41354 0.14747 4.8752 2.8033 -3.9887 0.76927 0.54065 0.056115 -0.054159 1176.8 0 0
16
+ 4 0.49778 -0.047054 0.49606 -0.062667 0.00397 0.12403 -0.12328 0.013611 0.00028684 0.0025982 -0.001932 0.0002546 25.087 0 0
17
+ 132 -0.28104 0.41354 -0.26791 0.42216 0.13841 4.5492 2.4976 -3.8022 0.81537 0.5356 0.052038 -0.05131 1083.7 0 0
18
+ 5 0.49606 -0.062667 0.49384 -0.078217 0.00411 0.12868 -0.1274 0.018131 -3.4087e-05 -0.0002395 -0.0020016 0.00028103 24.763 0 0
19
+ 133 -0.26791 0.42216 -0.25452 0.43037 0.13314 4.4025 2.3003 -3.7537 0.79675 0.48825 0.048646 -0.051292 1063.2 0 0
20
+ 6 0.49384 -0.078217 0.49114 -0.093691 0.00363 0.11026 -0.10861 0.018956 3.4621e-05 0.00019837 -0.0017055 0.00030087 23.351 0 0
21
+ 134 -0.25452 0.43037 -0.24088 0.43815 0.12631 4.1483 2.0553 -3.6034 0.81107 0.46263 0.045023 -0.049333 1027.5 0 0
22
+ 7 0.49114 -0.093691 0.48796 -0.10907 0.00378 0.12361 -0.12104 0.025066 0.0012517 0.0060441 -0.0018815 0.00048865 24.608 0 0
23
+ 135 -0.24088 0.43815 -0.227 0.4455 0.1192 3.9381 1.8428 -3.4804 0.79222 0.41946 0.041389 -0.048079 967.47 0 0
24
+ 8 0.48796 -0.10907 0.48429 -0.12434 0.00374 0.11389 -0.11075 0.026588 0.00059058 0.0024599 -0.0017303 0.00045627 23.933 0 0
25
+ 136 -0.227 0.4455 -0.21289 0.45241 0.11024 3.6416 1.6021 -3.2702 0.75883 0.37175 0.037083 -0.045527 900.96 0 0
26
+ 9 0.48429 -0.12434 0.48015 -0.1395 0.00354 0.10984 -0.10595 0.028984 0.0014764 0.0053968 -0.001641 0.00054003 25.125 0 0
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+ 137 -0.21289 0.45241 -0.19857 0.45888 0.10546 3.4357 1.4138 -3.1313 0.79782 0.36023 0.034739 -0.043526 852.79 0 0
28
+ 10 0.48015 -0.1395 0.47553 -0.15451 0.00355 0.10277 -0.098226 0.030218 0.00087867 0.0028562 -0.0015291 0.00051951 23.071 0 0
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+ 138 -0.19857 0.45888 -0.18406 0.46489 0.09886 3.2279 1.2353 -2.9822 0.77161 0.31961 0.031522 -0.041822 785.53 0 0
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+ 11 0.47553 -0.15451 0.47044 -0.16937 0.00342 0.10566 -0.099964 0.034225 0.00077582 0.002266 -0.001558 0.00057318 23.144 0 0
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+ 139 -0.18406 0.46489 -0.16937 0.47044 0.09366 3.0753 1.087 -2.8768 0.80876 0.3056 0.029778 -0.040386 791.78 0 0
32
+ 12 0.47044 -0.16937 0.46489 -0.18406 0.00323 0.097215 -0.090939 0.034363 0.003131 0.0082859 -0.0013792 0.0006699 18.528 0 0
33
+ 140 -0.16937 0.47044 -0.15451 0.47553 0.08665 2.8422 0.92064 -2.689 0.75786 0.25947 0.026365 -0.038161 732.42 0 0
34
+ 13 0.46489 -0.18406 0.45888 -0.19857 0.00292 0.085492 -0.078985 0.032716 0.0045423 0.010966 -0.0011693 0.00068614 18.442 0 0
35
+ 141 -0.15451 0.47553 -0.1395 0.48015 0.08184 2.6737 0.78618 -2.5555 0.72805 0.22398 0.023784 -0.036622 676.02 0 0
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+ 14 0.45888 -0.19857 0.45241 -0.21289 0.00283 0.081436 -0.074221 0.033512 0.0090611 0.020068 -0.0010235 0.0008416 19.29 0 0
37
+ 142 -0.1395 0.48015 -0.12434 0.48429 0.07597 2.4745 0.65296 -2.3868 0.70928 0.19404 0.021397 -0.034443 642.12 0 0
38
+ 15 0.45241 -0.21289 0.4455 -0.227 0.00293 0.083005 -0.074541 0.036517 0.005224 0.010664 -0.0010888 0.00074108 19.353 0 0
39
+ 143 -0.12434 0.48429 -0.10907 0.48796 0.07036 2.2869 0.53386 -2.2237 0.6847 0.16438 0.01914 -0.032346 587.71 0 0
40
+ 16 0.4455 -0.227 0.43815 -0.24088 0.00353 0.10134 -0.089562 0.047421 0.012681 0.023951 -0.0012076 0.0011211 23.979 0 0
41
+ 144 -0.10907 0.48796 -0.093691 0.49114 0.06544 2.1251 0.43093 -2.0809 0.65731 0.13612 0.017093 -0.030547 557.86 0 0
42
+ 17 0.43815 -0.24088 0.43037 -0.25452 0.00284 0.081287 -0.070608 0.040274 0.015235 0.026709 -0.00086977 0.0010521 20.633 0 0
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+ 145 -0.093691 0.49114 -0.078217 0.49384 0.06137 2.0137 0.34621 -1.9837 0.66247 0.11562 0.015844 -0.029342 552.8 0 0
44
+ 18 0.43037 -0.25452 0.42216 -0.26791 0.00314 0.090307 -0.076999 0.047185 0.014269 0.023285 -0.00098532 0.0011069 25.235 0 0
45
+ 146 -0.078217 0.49384 -0.062667 0.49606 0.05714 1.8623 0.26239 -1.8437 0.65579 0.093333 0.014422 -0.027493 510.35 0 0
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+ 19 0.42216 -0.26791 0.41354 -0.28104 0.00323 0.089513 -0.074816 0.049145 0.020036 0.030502 -0.00086044 0.001251 24.976 0 0
47
+ 147 -0.062667 0.49606 -0.047054 0.49778 0.05243 1.6789 0.18423 -1.6687 0.5666 0.062553 0.011794 -0.025229 425.8 0 0
48
+ 20 0.41354 -0.28104 0.40451 -0.29389 0.00321 0.09118 -0.074599 0.052429 0.026825 0.038168 -0.00075039 0.001423 25.305 0 0
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+ 148 -0.047054 0.49778 -0.031395 0.49901 0.04874 1.5574 0.12219 -1.5526 0.57422 0.045192 0.010939 -0.023677 421.21 0 0
50
+ 21 0.40451 -0.29389 0.39508 -0.30645 0.00325 0.090568 -0.072426 0.054379 0.026588 0.035413 -0.00071998 0.0014104 27.021 0 0
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+ 149 -0.031395 0.49901 -0.015705 0.49975 0.04547 1.468 0.069152 -1.4664 0.53572 0.025264 0.009501 -0.022636 387.11 0 0
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+ 22 0.39508 -0.30645 0.38526 -0.31871 0.00293 0.079082 -0.061718 0.049446 0.031511 0.039332 -0.00047447 0.0013945 25.681 0 0
53
+ 150 -0.015705 0.49975 0 0.5 0.0414 1.3422 0.021082 -1.342 0.5447 0.0085568 0.0088869 -0.020945 377.23 0 0
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+ 23 0.38526 -0.31871 0.37506 -0.33066 0.00313 0.084995 -0.064631 0.0552 0.030689 0.035932 -0.00053314 0.0014314 23.669 0 0
55
+ 151 0 0.5 0.015705 0.49975 0.0383 1.2224 -0.019201 -1.2223 0.49941 -0.0078454 0.0075429 -0.019322 342.09 0 0
56
+ 24 0.37506 -0.33066 0.36448 -0.34227 0.00332 0.094826 -0.070137 0.063819 0.043312 0.047599 -0.00042135 0.0017501 29.524 0 0
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+ 152 0.015705 0.49975 0.031395 0.49901 0.03513 1.1222 -0.052864 -1.121 0.48612 -0.022925 0.0068053 -0.017968 318.64 0 0
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+ 25 0.36448 -0.34227 0.35355 -0.35355 0.00409 0.11246 -0.080762 0.078263 0.054945 0.056698 -0.00040551 0.0021199 42.738 0 0
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+ 153 0.031395 0.49901 0.047054 0.49778 0.03238 1.0294 -0.080766 -1.0262 0.4233 -0.033315 0.0053804 -0.016643 278.48 0 0
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+ 26 0.35355 -0.35355 0.34227 -0.36448 0.00404 0.11055 -0.076935 0.079391 0.056703 0.054949 -0.00031778 0.0021101 34.963 0 0
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+ 154 0.047054 0.49778 0.062667 0.49606 0.02953 0.9424 -0.10341 -0.93671 0.41597 -0.045924 0.0049095 -0.015435 277.79 0 0
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+ 27 0.34227 -0.36448 0.33066 -0.37506 0.00456 0.13076 -0.088004 0.096715 0.064805 0.058968 -0.0003644 0.0024454 41.653 0 0
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+ 155 0.062667 0.49606 0.078217 0.49384 0.0275 0.8764 -0.12349 -0.86766 0.40988 -0.058334 0.0044984 -0.014545 262.32 0 0
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+ 28 0.33066 -0.37506 0.31871 -0.38526 0.00509 0.14272 -0.092686 0.10852 0.080431 0.068695 -0.0001925 0.0027836 48.729 0 0
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+ 30 0.30645 -0.39508 0.29389 -0.40451 0.00549 0.15592 -0.093616 0.12469 0.084329 0.063316 -0.00014589 0.002953 53.469 0 0
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+ 159 0.12434 0.48429 0.1395 0.48015 0.01893 0.58848 -0.15528 -0.56762 0.30371 -0.083085 0.0023313 -0.010221 185.11 0 0
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+ 32 0.28104 -0.41354 0.26791 -0.42216 0.00671 0.19442 -0.10674 0.1625 0.11694 0.076816 0.00016023 0.0037589 66.241 0 0
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+ 160 0.1395 0.48015 0.15451 0.47553 0.0178 0.55009 -0.16175 -0.52577 0.30025 -0.09237 0.0021755 -0.0097094 171.27 0 0
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+ 33 0.26791 -0.42216 0.25452 -0.43037 0.00769 0.21998 -0.11494 0.18756 0.13168 0.080691 0.00026289 0.0042135 74.438 0 0
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+ 161 0.15451 0.47553 0.16937 0.47044 0.0159 0.49313 -0.15973 -0.46654 0.26134 -0.089478 0.0015961 -0.0087336 158.82 0 0
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+ 34 0.25452 -0.43037 0.24088 -0.43815 0.00831 0.24372 -0.12076 0.21171 0.1356 0.077342 0.00023309 0.0045402 76.128 0 0
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+ 35 0.24088 -0.43815 0.227 -0.4455 0.00935 0.27185 -0.12721 0.24025 0.15586 0.082525 0.0004501 0.00507 89.737 0 0
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+ 36 0.227 -0.4455 0.21289 -0.45241 0.01087 0.3281 -0.14434 0.29464 0.18965 0.092907 0.00071161 0.0060873 111.27 0 0
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+ 39 0.18406 -0.46489 0.16937 -0.47044 0.01445 0.45068 -0.1593 0.42158 0.23527 0.0889 0.0011932 0.0080184 145.27 0 0
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+ 169 0.26791 0.42216 0.28104 0.41354 0.00744 0.21622 -0.11871 -0.18072 0.1191 -0.078237 6.2169e-06 -0.0040674 74.084 0 0
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+ 42 0.1395 -0.48015 0.12434 -0.48429 0.01891 0.58487 -0.15433 0.56414 0.30108 0.082366 0.002305 0.010155 184.41 0 0
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CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/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/Kn0p28/simulation0585_Kn0p28Ma5p4/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/Kn0p28/simulation0585_Kn0p28Ma5p4/slurm-28429282.out ADDED
@@ -0,0 +1,205 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 97600 child grid cells
6
+ CPU time = 0.126525 secs
7
+ create/ghost percent = 0.951505 99.0485
8
+ Balance grid migrated 97380 cells
9
+ CPU time = 0.112671 secs
10
+ reassign/sort/migrate/ghost percent = 52.7136 0.0302563 7.704 39.5521
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
+ 456 0 = cells overlapping surfs, overlap cells with unmarked corner pts
18
+ 87188 9956 456 = cells outside/inside/overlapping surfs
19
+ 456 = surf cells with 1,2,etc splits
20
+ 109.214731023047 109.214731023047 = cell-wise and global flow volume
21
+ CPU time = 0.115575 secs
22
+ read/check/sort/surf2grid/ghost/inout/particle percent = 20.7446 20.1428 2.27928 20.6641 36.1692 5.53698 0.113674
23
+ surf2grid time = 0.0238826 secs
24
+ map/comm1/comm2/comm3/comm4/split percent = 15.2733 23.8621 5.9099 1.69113 11.2966 6.6114
25
+ Balance grid migrated 1938 cells
26
+ CPU time = 0.0541184 secs
27
+ reassign/sort/migrate/ghost percent = 5.23597 0.0594419 17.985 76.7196
28
+ Creating particles ...
29
+ WARNING: Created unexpected # of particles: 668660 versus 668661 (../create_particles.cpp:346)
30
+ Created 668660 particles
31
+ CPU time = 0.0164353 secs
32
+ Memory usage per proc in Mbytes:
33
+ particles (ave,min,max) = 1.79297 0 3.375
34
+ grid (ave,min,max) = 4.297 1.51379 7.13879
35
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
36
+ total (ave,min,max) = 6.11057 3.22189 8.84689
37
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
38
+ 0 0 668660 0 0 0 0 0
39
+ 10000 17.792163 738049 12722 11113 20 696089.17 19.8585
40
+ 20000 40.006517 745511 12795 11301 24 719892.48 20.0974
41
+ 30000 62.323989 746098 12816 11197 17 728656.96 20.195933
42
+ 40000 85.226974 746672 12941 11378 28 733127.16 20.250275
43
+ 50000 106.71174 745298 12879 11330 29 735626.43 20.2499
44
+ 60000 129.07979 745769 12815 11211 16 737332.77 20.270067
45
+ 70000 152.58276 746685 12871 11239 23 738639.26 20.294071
46
+ 80000 174.59881 745808 12938 11320 21 739613.78 20.309963
47
+ 90000 197.07484 745827 12961 11372 26 740350.17 20.312011
48
+ 100000 219.47781 746773 12952 11323 14 740951.37 20.326
49
+ 110000 241.687 746606 13097 11488 29 741451.36 20.329873
50
+ 120000 264.63421 745923 12876 11275 18 741837.04 20.331642
51
+ 130000 286.62438 745508 13067 11406 26 742147.8 20.333562
52
+ 140000 308.95525 746211 12918 11318 22 742402.15 20.339279
53
+ 150000 332.42823 745940 12909 11311 21 742654.97 20.342953
54
+ 160000 354.60631 745638 12822 11245 26 742875.44 20.345175
55
+ 170000 376.69609 745842 12966 11312 12 743066.88 20.348147
56
+ 180000 399.75798 745350 12950 11299 22 743212.45 20.350728
57
+ 190000 421.95988 746610 12973 11339 24 743365.79 20.352426
58
+ 200000 444.86777 746477 12936 11301 16 743531.08 20.35403
59
+ Loop time of 444.869 on 128 procs for 200000 steps with 746477 particles
60
+
61
+ MPI task timing breakdown:
62
+ Section | min time | avg time | max time |%varavg| %total
63
+ ---------------------------------------------------------------
64
+ Move | 0.022431 | 18.661 | 123.65 | 576.6 | 4.19
65
+ Coll | 0.48511 | 17.885 | 175.55 | 628.9 | 4.02
66
+ Sort | 0.16331 | 3.4684 | 31.051 | 264.5 | 0.78
67
+ Comm | 72.858 | 107.5 | 119.84 | 95.2 | 24.16
68
+ Modify | 0.020904 | 0.15057 | 2.8802 | 108.5 | 0.03
69
+ Output | 0.0067739 | 0.021028 | 0.023177 | 1.6 | 0.00
70
+ Other | | 297.2 | | | 66.80
71
+
72
+ Particle moves = 148706216761 (149B)
73
+ Cells touched = 155360882036 (155B)
74
+ Particle comms = 248624616 (249M)
75
+ Boundary collides = 0 (0K)
76
+ Boundary exits = 24046066 (24M)
77
+ SurfColl checks = 237547559 (238M)
78
+ SurfColl occurs = 4070806 (4.07M)
79
+ Surf reactions = 0 (0K)
80
+ Collide attempts = 3033993264 (3.03B)
81
+ Collide occurs = 2357219828 (2.36B)
82
+ Gas reactions = 0 (0K)
83
+ Particles stuck = 0
84
+ Axisymm bad moves = 0
85
+
86
+ Particle-moves/CPUsec/proc: 2.61148e+06
87
+ Particle-moves/step: 743531
88
+ Cell-touches/particle/step: 1.04475
89
+ Particle comm iterations/step: 1
90
+ Particle fraction communicated: 0.00167192
91
+ Particle fraction colliding with boundary: 0
92
+ Particle fraction exiting boundary: 0.000161702
93
+ Surface-checks/particle/step: 0.00159743
94
+ Surface-collisions/particle/step: 2.73748e-05
95
+ Surface-reactions/particle/step: 0
96
+ Collision-attempts/particle/step: 0.0204026
97
+ Collisions/particle/step: 0.0158515
98
+ Gas-reactions/particle/step: 0
99
+
100
+ Particles: 5831.85 ave 41294 max 0 min
101
+ Histogram: 84 16 6 10 2 6 0 2 0 2
102
+ Cells: 762.5 ave 763 max 762 min
103
+ Histogram: 64 0 0 0 0 0 0 0 0 64
104
+ GhostCell: 19721.7 ave 36096 max 1099 min
105
+ Histogram: 20 10 12 10 18 2 6 4 16 30
106
+ EmptyCell: 0 ave 0 max 0 min
107
+ Histogram: 128 0 0 0 0 0 0 0 0 0
108
+ Surfs: 200 ave 200 max 200 min
109
+ Histogram: 128 0 0 0 0 0 0 0 0 0
110
+ GhostSurf: 0 ave 0 max 0 min
111
+ Histogram: 128 0 0 0 0 0 0 0 0 0
112
+ Memory usage per proc in Mbytes:
113
+ particles (ave,min,max) = 1.8457 0 5.0625
114
+ grid (ave,min,max) = 4.297 1.51379 7.13879
115
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
116
+ total (ave,min,max) = 6.41953 3.47786 9.10336
117
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
118
+ 200000 0 746477 12936 11301 0 0 0
119
+ 210000 39.604912 745870 12906 11292 22 745820.9 20.4079
120
+ 220000 79.821286 745881 13028 11394 31 745794.18 20.36695
121
+ 230000 121.61496 746506 12874 11230 14 745973.74 20.369733
122
+ 240000 161.52836 745995 12889 11327 22 746067.66 20.362375
123
+ 250000 202.34281 746337 13019 11423 19 746139.63 20.37056
124
+ 260000 242.44984 746017 12996 11371 18 746137.59 20.364367
125
+ 270000 282.04087 746696 12992 11455 15 746188.53 20.358143
126
+ 280000 322.50427 745917 12872 11255 29 746226.46 20.358387
127
+ 290000 362.43888 746006 13039 11476 22 746208.25 20.361767
128
+ 300000 402.04834 745595 12747 11155 19 746150.18 20.36131
129
+ Loop time of 402.048 on 128 procs for 100000 steps with 745595 particles
130
+
131
+ MPI task timing breakdown:
132
+ Section | min time | avg time | max time |%varavg| %total
133
+ ---------------------------------------------------------------
134
+ Move | 0.012494 | 9.4521 | 62.11 | 408.4 | 2.35
135
+ Coll | 0.24435 | 9.1593 | 95.582 | 459.4 | 2.28
136
+ Sort | 0.09862 | 1.807 | 12.92 | 185.0 | 0.45
137
+ Comm | 45.349 | 62.815 | 69.902 | 66.5 | 15.62
138
+ Modify | 3.4605 | 25.652 | 159.41 | 615.4 | 6.38
139
+ Output | 0.044827 | 0.046417 | 0.04995 | 0.5 | 0.01
140
+ Other | | 293.1 | | | 72.91
141
+
142
+ Particle moves = 74615018050 (74.6B)
143
+ Cells touched = 77951271382 (78B)
144
+ Particle comms = 124626456 (125M)
145
+ Boundary collides = 0 (0K)
146
+ Boundary exits = 12065561 (12.1M)
147
+ SurfColl checks = 119100612 (119M)
148
+ SurfColl occurs = 2036131 (2.04M)
149
+ Surf reactions = 0 (0K)
150
+ Collide attempts = 1530654951 (1.53B)
151
+ Collide occurs = 1188979038 (1.19B)
152
+ Gas reactions = 0 (0K)
153
+ Particles stuck = 0
154
+ Axisymm bad moves = 0
155
+
156
+ Particle-moves/CPUsec/proc: 1.4499e+06
157
+ Particle-moves/step: 746150
158
+ Cell-touches/particle/step: 1.04471
159
+ Particle comm iterations/step: 1
160
+ Particle fraction communicated: 0.00167026
161
+ Particle fraction colliding with boundary: 0
162
+ Particle fraction exiting boundary: 0.000161704
163
+ Surface-checks/particle/step: 0.0015962
164
+ Surface-collisions/particle/step: 2.72885e-05
165
+ Surface-reactions/particle/step: 0
166
+ Collision-attempts/particle/step: 0.020514
167
+ Collisions/particle/step: 0.0159348
168
+ Gas-reactions/particle/step: 0
169
+
170
+ Particles: 5824.96 ave 41343 max 0 min
171
+ Histogram: 84 16 6 10 2 6 0 2 0 2
172
+ Cells: 762.5 ave 763 max 762 min
173
+ Histogram: 64 0 0 0 0 0 0 0 0 64
174
+ GhostCell: 19721.7 ave 36096 max 1099 min
175
+ Histogram: 20 10 12 10 18 2 6 4 16 30
176
+ EmptyCell: 0 ave 0 max 0 min
177
+ Histogram: 128 0 0 0 0 0 0 0 0 0
178
+ Surfs: 200 ave 200 max 200 min
179
+ Histogram: 128 0 0 0 0 0 0 0 0 0
180
+ GhostSurf: 0 ave 0 max 0 min
181
+ Histogram: 128 0 0 0 0 0 0 0 0 0
182
+ Writing grid file ...
183
+ grid cells = 97600
184
+ CPU time = 0.0138704 secs
185
+ Writing surface file ...
186
+ surf elements = 200
187
+ CPU time = 0.00156067 secs
188
+ Processing 4 grid chunk(s).
189
+ Completed grid chunk number: 3
190
+ Completed grid chunk number: 2
191
+ Completed grid chunk number: 1
192
+ Completed grid chunk number: 0
193
+
194
+ Done in 0:00:13 (wall clock time)
195
+
196
+ Processing 4 grid chunk(s).
197
+ Completed grid chunk number: 3
198
+ Completed grid chunk number: 2
199
+ Completed grid chunk number: 1
200
+ Completed grid chunk number: 0
201
+
202
+ Done in 0:00:12 (wall clock time)
203
+
204
+ Processing SPARTA surface information.
205
+ Processing dump result file: ['./output/surf.300000.dat']
CylinderKnMa/Kn0p28/simulation0585_Kn0p28Ma5p4/surf/Surf_300000.vtu ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ <?xml version="1.0"?>
2
+ <VTKFile type="UnstructuredGrid" version="0.1" byte_order="LittleEndian" header_type="UInt32" compressor="vtkZLibDataCompressor">
3
+ <UnstructuredGrid>
4
+ <Piece NumberOfPoints="400" NumberOfCells="200" >
5
+ <PointData>
6
+ </PointData>
7
+ <CellData>
8
+ <DataArray type="Float64" Name="id" format="appended" RangeMin="1" RangeMax="200" offset="0" />
9
+ <DataArray type="Float64" Name="v1x" format="appended" RangeMin="-0.5" RangeMax="0.5" offset="432" />
10
+ <DataArray type="Float64" Name="v1y" format="appended" RangeMin="-0.5" RangeMax="0.5" offset="1468" />
11
+ <DataArray type="Float64" Name="v2x" format="appended" RangeMin="-0.5" RangeMax="0.5" offset="2476" />
12
+ <DataArray type="Float64" Name="v2y" format="appended" RangeMin="-0.5" RangeMax="0.5" offset="3508" />
13
+ <DataArray type="Float64" Name="f_2[1]" format="appended" RangeMin="0.0027" RangeMax="0.33677" offset="4512" />
14
+ <DataArray type="Float64" Name="f_2[2]" format="appended" RangeMin="0.078047" RangeMax="11.052" offset="6500" />
15
+ <DataArray type="Float64" Name="f_2[3]" format="appended" RangeMin="-0.16175" RangeMax="11.051" offset="8512" />
16
+ <DataArray type="Float64" Name="f_2[4]" format="appended" RangeMin="-4.6226" RangeMax="4.6227" offset="10552" />
17
+ <DataArray type="Float64" Name="f_2[5]" format="appended" RangeMin="-0.00042647" RangeMax="0.81537" offset="12628" />
18
+ <DataArray type="Float64" Name="f_2[6]" format="appended" RangeMin="-0.77646" RangeMax="0.75492" offset="14708" />
19
+ <DataArray type="Float64" Name="f_2[7]" format="appended" RangeMin="-0.0022064" RangeMax="0.1736" offset="16832" />
20
+ <DataArray type="Float64" Name="f_2[8]" format="appended" RangeMin="-0.06136" RangeMax="0.060416" offset="18968" />
21
+ <DataArray type="Float64" Name="f_2[9]" format="appended" RangeMin="17.623" RangeMax="2472.6" offset="21104" />
22
+ <DataArray type="Float64" Name="f_2[10]" format="appended" RangeMin="0" RangeMax="0" offset="22424" />
23
+ <DataArray type="Float64" Name="f_2[11]" format="appended" RangeMin="0" RangeMax="0" offset="22476" />
24
+ </CellData>
25
+ <Points>
26
+ <DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="0.49999998503" RangeMax="0.50000001255" offset="22528" />
27
+ </Points>
28
+ <Cells>
29
+ <DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="23856" />
30
+ <DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="24760" />
31
+ <DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="25252" />
32
+ </Cells>
33
+ </Piece>
34
+ </UnstructuredGrid>
35
+ <AppendedData encoding="base64">
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AQAAAACAAABABgAA0QUAAA==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AQAAAACAAABABgAA5gUAAA==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AQAAAACAAABABgAAAwYAAA==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AQAAAACAAABABgAAJgYAAA==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AQAAAACAAABABgAAMAYAAA==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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
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38
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VTLcCrX2T36dvymbsuNviiZbDbBo9FHDyxh3mtvN+mR0yzabT67yuqboqMjanP9NsMEuRPJuU7QvamFtanuLjrs8h0YFHr9dEcBg7eJvD5/YqDpUY359MG2Vu4/fjp6LsuBT1ME6qe4bL2NWXhq4/beGStb/l6nKREmOf2FTpEBisRI0SE19uCXP3OZZ21/GVKZ6dz1tWpEz2Bf6XK815xN0g3GRXy6PcMaX9eV4qFHK+8ZtZpwp99blnkBqtSjVfYmWXUqXE2UNkqJGa66p4tp46ve7qUZOWq1P+scKrxls0aLVtTktykwaNvNpxULCHTw+iVcaL+/nkbjFjNHVUk86G7et0VRRQq/O74VEPAc39NkdAeR+kaakdAuqp4xeuXykk53OH+icihVQW2Gz9+JaQhja7bD8yLiTZI3JsnbTo7ktWFztdi2Zk+dxs1aKw5Hb747oiqgj1220aKiK++exlRHRkXHPg7pCIHnRkTEXYaJPB9c9uFsnalBLrmjv2VJua/WSB8cVkbmQoS0BM2YNJjhuLxNT+4rvvx17x/H10KDWptWZvvA4NuMkeUqtDO8SZHl84kvl7SehHY3hFaK5k/m4SRtfoHJ2jc3S+0M7ljugZPS+OngPmALnoFt3+V90+87RJdwpFn+jz3/Qpd0GH6PDvdmijVx+8wgm9obc/05v87ugKXS2sK/md0Q/6+X0/uyZ1Y9/moJOl3on8juhhqfTQ0HzF5U4s3Bebe2TMcOpzPxZZ8aqWB31iwRGOcIQjHOEIRzjCEY5whCMc4QhHOMIRjnCEIxzhCEc4whGOcIQjHOEIRzjCEY5whCMc4QhHOMIRjnCEIxzhCEc4whGOcITjknX8CZxzjKs=AQAAAACAAAAoUwAAWwIAAA==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AQAAAACAAAAoUwAAzQ0AAA==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AQAAAACAAABlCgAAGgAAAA==eJztwSEBAAAAwyC9/oVf4hIoAAA4G4r2XY4=
26
+ </AppendedData>
27
+ </VTKFile>
CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/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/Kn0p28/simulation0586_Kn0p28Ma5p5/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 0.28
13
+ variable Ma equal 5.5
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/Kn0p28/simulation0586_Kn0p28Ma5p5/cylinder.surf ADDED
@@ -0,0 +1,410 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ surf file from Pointwise
2
+
3
+ 200 points
4
+ 200 lines
5
+
6
+ Points
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+
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CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/gas.species ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Species data
2
+
3
+ # species name
4
+ # molecular weight (atomic mass units, e.g. 16 for oxygen)
5
+ # molecular mass (kg)
6
+ # rotational degrees of freedom (integer, unitless)
7
+ # inverse rotational relaxtion number (unitless)
8
+ # vibrational degrees of freedom (integer, unitless)
9
+ # inverse vibrational relaxation number (unitless)
10
+ # vibrational temperature (K)
11
+ # species weight (unitless)
12
+ # multiple of electon charge (1 for a proton)
13
+
14
+ Ar 39.95 6.63E-26 0 0.0 0 0.0 0.0 1.0 0.0
CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/gas.vhs ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ # VHS collision model parameters for each species
2
+
3
+ # species name
4
+ # diameter (m)
5
+ # omega (unitless)
6
+ # tref (referenced temperature)
7
+ # alpha (unitless)
8
+
9
+ Ar 4.17e-10 0.81 273 1.0
CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/grid/Grid_0_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/grid/Grid_1_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/grid/Grid_2_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/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/Kn0p28/simulation0586_Kn0p28Ma5p5/grid/Grid_3_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/grid/final-grid.dat ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0586_Kn0p28Ma5p5/log.sparta ADDED
@@ -0,0 +1,319 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 0.28
17
+ variable Ma equal 5.5
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 0.28*${L}
23
+ variable mfp equal 0.28*1
24
+ variable cpmfp equal 4
25
+ variable nden equal 1.0/sqrt(2.0)/${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}*${Kn})
29
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.28/${cpmfp}*${Kn})
30
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.28/4*${Kn})
31
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.28/4*0.28)
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 5.5*${sos}
38
+ variable vo equal 5.5*307.815564238681
39
+ variable vx equal ${vo}*cos(${theta}*2*PI/360)
40
+ variable vx equal 1692.98560331275*cos(${theta}*2*PI/360)
41
+ variable vx equal 1692.98560331275*cos(0*2*PI/360)
42
+ variable vy equal ${vo}*sin(${theta}*2*PI/360)
43
+ variable vy equal 1692.98560331275*sin(${theta}*2*PI/360)
44
+ variable vy equal 1692.98560331275*sin(0*2*PI/360)
45
+ variable ppc equal 30
46
+ variable xncells equal (${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)/0.28*${cpmfp}
50
+ variable xncells equal (6--5)/0.28*4
51
+ variable yncells equal (${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)/0.28*${cpmfp}
55
+ variable yncells equal (5--5)/0.28*4
56
+ variable Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
57
+ variable Fnum equal 6.60399822965135e+19*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
58
+ variable Fnum equal 6.60399822965135e+19*(6-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
59
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
60
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(5-${ymin})/${ppc}/${xncells}/${yncells}
61
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(5--5)/${ppc}/${xncells}/${yncells}
62
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(5--5)/30/${xncells}/${yncells}
63
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(5--5)/30/157.142857142857/${yncells}
64
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(5--5)/30/157.142857142857/142.857142857143
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}/${xncells}/10/4
68
+ variable tstep equal (--5+6)/1692.98560331275/${xncells}/10/4
69
+ variable tstep equal (--5+6)/1692.98560331275/157.142857142857/10/4
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 6.60399822965135e+19
81
+ global fnum ${Fnum}
82
+ global fnum 1.07865304417639e+16
83
+ timestep ${tstep}
84
+ timestep 1.03367683492151e-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 157.142857142857 ${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 157.142857142857 142.857142857143 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 97600 child grid cells
100
+ CPU time = 0.133981 secs
101
+ create/ghost percent = 0.951838 99.0482
102
+ balance_grid rcb cell
103
+ Balance grid migrated 97380 cells
104
+ CPU time = 0.106276 secs
105
+ reassign/sort/migrate/ghost percent = 54.1147 0.0270805 10.2588 35.5995
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 1692.98560331275 ${vy} 0.0 temp ${To}
110
+ mixture air Ar vstream 1692.98560331275 0 0.0 temp ${To}
111
+ mixture air Ar vstream 1692.98560331275 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
+ 456 0 = cells overlapping surfs, overlap cells with unmarked corner pts
121
+ 87188 9956 456 = cells outside/inside/overlapping surfs
122
+ 456 = surf cells with 1,2,etc splits
123
+ 109.215 109.215 = cell-wise and global flow volume
124
+ CPU time = 0.111599 secs
125
+ read/check/sort/surf2grid/ghost/inout/particle percent = 21.0579 21.7886 2.45342 22.6431 32.057 5.9458 0.127689
126
+ surf2grid time = 0.0252695 secs
127
+ map/comm1/comm2/comm3/comm4/split percent = 14.6715 25.0783 5.16375 1.69231 11.016 7.12567
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 1938 cells
133
+ CPU time = 0.0462991 secs
134
+ reassign/sort/migrate/ghost percent = 6.30672 0.0635649 19.7377 73.892
135
+ create_particles air n 0
136
+ WARNING: Created unexpected # of particles: 668660 versus 668661 (../create_particles.cpp:346)
137
+ Created 668660 particles
138
+ CPU time = 0.0167465 secs
139
+ stats 10000
140
+ stats_style step cpu np nattempt ncoll nscoll npave nscollave
141
+ run 200000
142
+ Memory usage per proc in Mbytes:
143
+ particles (ave,min,max) = 1.79297 0 3.375
144
+ grid (ave,min,max) = 4.297 1.51379 7.13879
145
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
146
+ total (ave,min,max) = 6.11057 3.22189 8.84689
147
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
148
+ 0 0 668660 0 0 0 0 0
149
+ 10000 15.911117 738169 12421 10848 30 696277.36 20.1095
150
+ 20000 37.3918 745075 12583 11068 14 720045.45 20.33435
151
+ 30000 58.623639 746416 12710 11166 17 728741.57 20.427833
152
+ 40000 80.469053 745868 12546 11024 22 733142 20.483625
153
+ 50000 101.77752 745420 12714 11065 17 735657.7 20.5161
154
+ 60000 122.9727 746862 12737 11138 16 737428.87 20.524283
155
+ 70000 144.43856 746147 12695 11124 21 738700.14 20.542229
156
+ 80000 165.65459 746242 12624 11094 21 739656.35 20.558163
157
+ 90000 187.43315 746031 12807 11190 21 740377.95 20.556
158
+ 100000 208.60961 745403 12851 11239 22 740952.86 20.56135
159
+ 110000 230.2695 746168 12655 11080 20 741401.21 20.561355
160
+ 120000 251.58896 745737 12694 11066 22 741744.03 20.566533
161
+ 130000 273.40237 745850 12754 11180 23 742086.84 20.571762
162
+ 140000 295.29933 746358 12790 11240 23 742375.7 20.579743
163
+ 150000 316.32062 746592 12684 11106 27 742631.73 20.585013
164
+ 160000 338.40686 746119 12856 11292 20 742881.13 20.590312
165
+ 170000 359.83708 746669 12605 11027 28 743097.23 20.599465
166
+ 180000 381.75451 745208 12727 11195 13 743271.11 20.597267
167
+ 190000 402.98028 746092 12706 11159 22 743417.65 20.5952
168
+ 200000 425.07876 745973 12659 11151 23 743551.84 20.598755
169
+ Loop time of 425.08 on 128 procs for 200000 steps with 745973 particles
170
+
171
+ MPI task timing breakdown:
172
+ Section | min time | avg time | max time |%varavg| %total
173
+ ---------------------------------------------------------------
174
+ Move | 0.0244 | 18.173 | 122.29 | 563.8 | 4.28
175
+ Coll | 0.48306 | 17.84 | 169.3 | 625.7 | 4.20
176
+ Sort | 0.16167 | 3.4832 | 29.095 | 261.6 | 0.82
177
+ Comm | 67.404 | 100.26 | 112.16 | 92.5 | 23.59
178
+ Modify | 0.021822 | 0.16614 | 3.6391 | 120.9 | 0.04
179
+ Output | 0.0038152 | 0.017462 | 0.019277 | 1.8 | 0.00
180
+ Other | | 285.1 | | | 67.08
181
+
182
+ Particle moves = 148710367835 (149B)
183
+ Cells touched = 155356520825 (155B)
184
+ Particle comms = 248399876 (248M)
185
+ Boundary collides = 0 (0K)
186
+ Boundary exits = 23996606 (24M)
187
+ SurfColl checks = 242194015 (242M)
188
+ SurfColl occurs = 4119751 (4.12M)
189
+ Surf reactions = 0 (0K)
190
+ Collide attempts = 2990588523 (2.99B)
191
+ Collide occurs = 2324198768 (2.32B)
192
+ Reactions = 0 (0K)
193
+ Particles stuck = 0
194
+ Axisymm bad moves = 0
195
+
196
+ Particle-moves/CPUsec/proc: 2.73313e+06
197
+ Particle-moves/step: 743552
198
+ Cell-touches/particle/step: 1.04469
199
+ Particle comm iterations/step: 1
200
+ Particle fraction communicated: 0.00167036
201
+ Particle fraction colliding with boundary: 0
202
+ Particle fraction exiting boundary: 0.000161365
203
+ Surface-checks/particle/step: 0.00162863
204
+ Surface-collisions/particle/step: 2.77032e-05
205
+ Surf-reactions/particle/step: 0
206
+ Collision-attempts/particle/step: 0.0201102
207
+ Collisions/particle/step: 0.015629
208
+ Reactions/particle/step: 0
209
+
210
+ Particles: 5827.91 ave 41191 max 0 min
211
+ Histogram: 84 16 6 10 2 6 0 2 0 2
212
+ Cells: 762.5 ave 763 max 762 min
213
+ Histogram: 64 0 0 0 0 0 0 0 0 64
214
+ GhostCell: 19721.7 ave 36096 max 1099 min
215
+ Histogram: 20 10 12 10 18 2 6 4 16 30
216
+ EmptyCell: 0 ave 0 max 0 min
217
+ Histogram: 128 0 0 0 0 0 0 0 0 0
218
+ Surfs: 200 ave 200 max 200 min
219
+ Histogram: 128 0 0 0 0 0 0 0 0 0
220
+ GhostSurf: 0 ave 0 max 0 min
221
+ Histogram: 128 0 0 0 0 0 0 0 0 0
222
+ compute 1 grid all air n nrho massrho u v w
223
+ compute 2 grid all air trot
224
+ compute 3 tvib/grid all air
225
+ compute 4 thermal/grid all air press temp
226
+ fix 1 ave/grid all 1 ${nave} ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
227
+ fix 1 ave/grid all 1 10000 ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
228
+ fix 1 ave/grid all 1 10000 10000 c_1[*] c_4[*] c_2[*] c_3[*] ave running
229
+ dump 1 grid all ${noutput} output/grid.*.dat id xc yc f_1[*]
230
+ dump 1 grid all 300000 output/grid.*.dat id xc yc f_1[*]
231
+ dump_modify 1 format float %12.5g
232
+ compute 5 surf all air n press px py shx shy fx fy etot erot evib
233
+ fix 2 ave/surf all 1 ${nave} ${nave} c_5[*] ave running
234
+ fix 2 ave/surf all 1 10000 ${nave} c_5[*] ave running
235
+ fix 2 ave/surf all 1 10000 10000 c_5[*] ave running
236
+ dump 2 surf all ${noutput} output/surf.*.dat id v1x v1y v2x v2y f_2[*]
237
+ dump 2 surf all 300000 output/surf.*.dat id v1x v1y v2x v2y f_2[*]
238
+ dump_modify 2 format float %12.5g
239
+ compute 6 lambda/grid f_1[2] f_1[8] Ar kx
240
+ dump 3 grid all ${noutput} output/lambdakn.*.dat id xc yc c_6[*]
241
+ dump 3 grid all 300000 output/lambdakn.*.dat id xc yc c_6[*]
242
+ dump_modify 3 format float %12.5g
243
+ run 100000
244
+ Memory usage per proc in Mbytes:
245
+ particles (ave,min,max) = 1.8457 0 5.0625
246
+ grid (ave,min,max) = 4.297 1.51379 7.13879
247
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
248
+ total (ave,min,max) = 6.41953 3.47786 9.10336
249
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
250
+ 200000 0 745973 12659 11151 0 0 0
251
+ 210000 38.741914 745309 12652 11057 25 745963.45 20.6299
252
+ 220000 79.486885 745883 12774 11173 12 745897.77 20.6206
253
+ 230000 118.87564 746726 12626 11027 15 746256.8 20.645467
254
+ 240000 157.41273 745768 12575 11028 24 746308.03 20.642375
255
+ 250000 196.04688 746444 12640 11081 20 746330.42 20.63078
256
+ 260000 234.72018 746517 12577 11037 26 746321.99 20.6232
257
+ 270000 274.36829 746349 12732 11155 28 746350.05 20.621857
258
+ 280000 312.44033 746314 12668 11092 16 746382.51 20.630713
259
+ 290000 351.4232 746022 12758 11224 16 746370.73 20.6307
260
+ 300000 390.97518 745974 12761 11209 17 746331.93 20.63747
261
+ Loop time of 390.976 on 128 procs for 100000 steps with 745974 particles
262
+
263
+ MPI task timing breakdown:
264
+ Section | min time | avg time | max time |%varavg| %total
265
+ ---------------------------------------------------------------
266
+ Move | 0.013059 | 9.2108 | 61.282 | 399.3 | 2.36
267
+ Coll | 0.24076 | 9.1553 | 92.294 | 457.6 | 2.34
268
+ Sort | 0.097711 | 1.8247 | 11.887 | 184.1 | 0.47
269
+ Comm | 39.775 | 56.882 | 63.284 | 64.0 | 14.55
270
+ Modify | 3.4095 | 25.46 | 159.37 | 616.6 | 6.51
271
+ Output | 0.039069 | 0.04058 | 0.044753 | 0.6 | 0.01
272
+ Other | | 288.4 | | | 73.76
273
+
274
+ Particle moves = 74633192681 (74.6B)
275
+ Cells touched = 77965873806 (78B)
276
+ Particle comms = 124538281 (125M)
277
+ Boundary collides = 0 (0K)
278
+ Boundary exits = 12040753 (12M)
279
+ SurfColl checks = 121519924 (122M)
280
+ SurfColl occurs = 2063747 (2.06M)
281
+ Surf reactions = 0 (0K)
282
+ Collide attempts = 1510507318 (1.51B)
283
+ Collide occurs = 1173670447 (1.17B)
284
+ Reactions = 0 (0K)
285
+ Particles stuck = 0
286
+ Axisymm bad moves = 0
287
+
288
+ Particle-moves/CPUsec/proc: 1.49133e+06
289
+ Particle-moves/step: 746332
290
+ Cell-touches/particle/step: 1.04465
291
+ Particle comm iterations/step: 1
292
+ Particle fraction communicated: 0.00166867
293
+ Particle fraction colliding with boundary: 0
294
+ Particle fraction exiting boundary: 0.000161332
295
+ Surface-checks/particle/step: 0.00162823
296
+ Surface-collisions/particle/step: 2.76519e-05
297
+ Surf-reactions/particle/step: 0
298
+ Collision-attempts/particle/step: 0.0202391
299
+ Collisions/particle/step: 0.0157259
300
+ Reactions/particle/step: 0
301
+
302
+ Particles: 5827.92 ave 41222 max 0 min
303
+ Histogram: 84 16 6 10 2 6 0 1 1 2
304
+ Cells: 762.5 ave 763 max 762 min
305
+ Histogram: 64 0 0 0 0 0 0 0 0 64
306
+ GhostCell: 19721.7 ave 36096 max 1099 min
307
+ Histogram: 20 10 12 10 18 2 6 4 16 30
308
+ EmptyCell: 0 ave 0 max 0 min
309
+ Histogram: 128 0 0 0 0 0 0 0 0 0
310
+ Surfs: 200 ave 200 max 200 min
311
+ Histogram: 128 0 0 0 0 0 0 0 0 0
312
+ GhostSurf: 0 ave 0 max 0 min
313
+ Histogram: 128 0 0 0 0 0 0 0 0 0
314
+ write_grid grid/final-grid.dat
315
+ grid cells = 97600
316
+ CPU time = 0.0137853 secs
317
+ write_surf surf/geom.surf
318
+ surf elements = 200
319
+ CPU time = 0.00169196 secs