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  1. .gitattributes +5 -0
  2. CylinderKnMa/Kn0p30/simulation0610_Kn0p30Ma2p9/output/grid.300000.dat +3 -0
  3. CylinderKnMa/Kn0p30/simulation0611_Kn0p30Ma3p0/output/grid.300000.dat +3 -0
  4. CylinderKnMa/Kn0p30/simulation0612_Kn0p30Ma3p1/output/grid.300000.dat +3 -0
  5. CylinderKnMa/Kn0p30/simulation0613_Kn0p30Ma3p2/output/grid.300000.dat +3 -0
  6. CylinderKnMa/Kn0p30/simulation0614_Kn0p30Ma3p3/output/grid.300000.dat +3 -0
  7. CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/Lambda/Lambda_0_300000.vtu +0 -0
  8. CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/Lambda/Lambda_1_300000.vtu +27 -0
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  12. CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/Surf.pvd +9 -0
  13. CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/grid/Grid_0_300000.vtu +0 -0
  14. CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/grid/Grid_1_300000.vtu +0 -0
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  16. CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/grid/Grid_300000.pvtu +29 -0
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  18. CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/grid/final-grid.dat +0 -0
  19. CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/log.sparta +319 -0
  20. CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/mir.txt +3 -0
  21. CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/output/lambdakn.300000.dat +0 -0
  22. CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/output/surf.300000.dat +209 -0
  23. CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/runmpirun128.sh +18 -0
  24. CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/runmpirun64.sh +18 -0
  25. CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/slurm-28429678.out +205 -0
  26. CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/surf/Surf_300000.vtu +38 -0
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  28. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/Grid.pvd +9 -0
  29. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/Lambda.pvd +9 -0
  30. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/Lambda/Lambda_0_300000.vtu +0 -0
  31. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/Lambda/Lambda_1_300000.vtu +27 -0
  32. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/Lambda/Lambda_2_300000.vtu +27 -0
  33. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/Lambda/Lambda_300000.pvtu +21 -0
  34. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/Lambda/Lambda_3_300000.vtu +27 -0
  35. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/Surf.pvd +9 -0
  36. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/config.txt +78 -0
  37. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/cylinder.surf +410 -0
  38. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/gas.species +14 -0
  39. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/gas.vhs +9 -0
  40. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/grid/Grid_0_300000.vtu +0 -0
  41. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/grid/Grid_1_300000.vtu +0 -0
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  43. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/grid/Grid_300000.pvtu +29 -0
  44. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/grid/Grid_3_300000.vtu +35 -0
  45. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/grid/final-grid.dat +0 -0
  46. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/log.sparta +319 -0
  47. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/mir.txt +3 -0
  48. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/output/lambdakn.300000.dat +0 -0
  49. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/output/surf.300000.dat +209 -0
  50. CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/runmpirun128.sh +18 -0
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AQAAAACAAACgWgAAjAIAAA==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AQAAAACAAACgWgAAVUoAAA==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CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/Lambda/Lambda_2_300000.vtu ADDED
@@ -0,0 +1,27 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ <?xml version="1.0"?>
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+ <UnstructuredGrid>
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+ <Piece NumberOfPoints="1818" NumberOfCells="1700" >
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+ <PointData>
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+ <DataArray type="Float64" Name="xc" format="appended" RangeMin="-4.9574" RangeMax="3.4845" offset="2984" />
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+ <DataArray type="Float64" Name="c_6[2]" format="appended" RangeMin="0.20824" RangeMax="0.3425" offset="15072" />
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+ <Points>
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+ </Points>
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+ <Cells>
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+ <DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="31048" />
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+ <DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="43352" />
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+ <DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="46420" />
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+ </Cells>
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+ </Piece>
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+ </UnstructuredGrid>
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+ <AppendedData encoding="base64">
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k4/Iw0ymKZuN6Yt7ubKAkk1Hp4So3lUw77fv4r4ySaUDV05Da7H2PdockC+x5f+9X7QxcK1NbnfDDW7bItKjVoDpz9vLzt/INuy77ZLpY2H+rk1KmYaV7m8Sw994pd+n5mT1XrHHQ0Q2RaZ7Rzr3pskzNSy/fG8bWI2J35fzPR2X61nNhUuODMrUyqBpayp5rNe96kbGKz5tFYEMTFZuvvh8DbqxqJNP0R1/HNvwWSlObHxCXewZTk79PHUgcpqQSoW1K4iWRJtqNPXkpXiD7qVuWth4h0NpD+vpPews0bUHRZ6+JAjk1PlRWHSlQ1LsVzjuuCfTiY4ZBIx2RPvjWux06VaRd/QwWCvtEOhx9sGFUhUipnu4ppiYSabWJnfhLkGhr2JdfHuckOva6ZGeOtoIGvt79btdEBWU1vhAwJlJB/+Stc/l0R0G+x5s2/WykpKpZDR928VBSQNGnRl7nldTC99bHe7VU9GX4xvvxVio6b5EjWUapaPqDye8n31LR6xlD2+/voqbpkX4zB61Sk3VraemAU2raSTuHrtINpmnzl3fIGxVM35Ma1JxgcXst99Fn7R0yrc8P672LHcdXXUwdFMjXZYHxrT7NWbxesr97q+lGmS7vPqFwCJVJmVpqoBPO4yXF8OrMATKPo8yaziO8N8s0x6xrppuvTFu2L31UPE+mPKOvzbMWsPUrPv5uKnterWV3khqyuH/mM67jAHb9Jj/Dkf4sv/qZzd9RX+K/T3Nu7b1lCcsrgwUZz6fLVL+rJiJZvPzyupc8TCZf55KDr61lut4qdqsj+3+cjvOT18t4nCM+3tlMX2LI4gzf/8Lkcv8+2/l3o17Yb49OXO3N8/OM1av8m1bsO82OdR45WaYEq/pH98+SaanBxqij82VyS3feXr2dz5ufdm6QCbs/rTi4of8qmXYX37rzD4trudDV+vth9j2W/RK9WZ2Ira7e+iaDvfdJh93hF3i9QH2JrxnVefQeno84jxaG1pq8lec7GZxaMYHlmYuVw8LaG/h3upqeNZ3M1mmxZavcxEMyeesWrB9yTCZ904EFvtdYXSjuEeCXxMdfVhpfPKYXe9/7vm9Dv4dS6vTxC9svDKb7exJOH22kpLlfja9vOS3S17tzI2KyBco+svi6s4tA894vZW8WaK5rbs1RH4F2ZxzaUfeMQGvexZt0eC7QzrYdV1h1Eene6O8zz7qJ9I+Y+9MiTqTWOnebjnsj0rUns97O7yOR9ZMG07p7SbT5+aoKr0yJmo268+KOloLaDTTKmTNNQQ4T8+qbhSro6xa/8pLzCmq7RjPDSpp23PJ+4AglFS1bZ229U0kK5wCnucVKSjWUvngMUJGZbsW1+64qio068tn7uIra/exTFFVXTX9XyupPC9TklhlXv26smoQj939kvVL/qZsjrdR9QxS8XpnfGL5pLJvfekXFN36tlKnP9ofejYN4HPUPNPrbidXh0+pF6UXjZcryuxTYkcXhwmTvjRkzZDrnYjzfleFPrmHKyiUsTj7uXn/pAntuWPSePYnsvLLw64n8Dbzeol5/1YQJi89IXeWRyFBeLzG+JfmnWs5Q8PFMt/KZcG0HP8d1p3J/FBewvNphZJ3T0V8mE53NF0+wOA1O73nakdX1236HDtjN4/gTOG9Nl0ssfg+Zumx76cPHvdrI9WAFO47Ir3pccYjHrfvbMeMtY2TKSJqXYnBcpiS5W8Mdqaz+pmcMmZMok57VzR8mLP7f+w/o4c7qd/f8ZhfTWR68XJjwaQOr6y2c3bqX7+LjPOwy3mKIWqZ9lg+qW7Dx+7tfOdrVj+cr8hh5V18nQ5wSxO8LNXw1QouN683kxpcu5cg0I3XINddzMjUwC50ensjn83d4pXEc22waM9WP5R8r5sdSDvDnDzZu8iOezVvt0yHDnQcyfrCmXpOfLcLI++6YRb3dg+lxr70R1SZKauQ79oTDLZEuL987fhzDiRGKW/uFVQJF3vN0G7tAINs8xTq9rQI51nMaE1UgkMnV1cniN4HWTV+clt1OpPRlDb9GLBb/5NtR3aPG6mqRnqnOtt7XTSJqYxUc6iZR5cl4vea5EpWfP6atX0tB7kebFPsNVdCxDf1N5gYo6PcyXVVQ3PHboxx0lVRRUSu9z2KGI8Gnsp8dUdKgWU0/Wj9Q0v1yTQCr6Lj/NJ/mLE/0k5puOpnI8KVHSd7wDyrSDesflWqqJmX9l91XBqj/zD/iLih3UMISFgdpu2/79DjAcdynlf4/e7fyuL9iPuyAfYRMhW0mvB2byo+Ig9Habc0VIRxHEAfAc8ThT5PDk53YcUqyxDKdxVl60zvSQo4P6a00b2RxmD/Wt+simX6V953nsInzki+ej8OaM35mykb9U+b4MGTem8xqtv5zo5+N1GXx0Hlew5icJM47EL+fzWs9OMtwRVNd/2F5Mjc7v7GBM3+vv9nb90VsPNod7LO1V8hkpm7ZPnwvx0/UZ7wX8wN+ifreJfmaiSH7zlVVgS/2ezLc1Y5PcGb1JKDKvfYthpv71BH+bux9g7/2GmrvwnF5mZ+Z0bQQ/r0xufrnw9i8Vw0/OWzZCXZ9scWKyeky2eQXfusYya+rWbhb95iK58WPJ+VZ9ZNlmmB0wMuf5ZGhkYb5yXQgyVdZfpbP0y/Vshu1U3n+47tapA04Yc54asDihv1q9wij245t/IMCgsnsuHO2/QQlvdDQvIcibZr/tcr1rEAWQ+t06rOM8a45trsCWJ74HTnDKqhAb9cf1GmSI5DXcu1Sz58cTyzKrLMazRap2NjBuDHjXV6lKzNq3xDJ335J+YBGErVMvfREtJLopdMIw4JgiZYr88eV/5AoPTPGZJaFgmJcf+y47K+gta/21TuRpiDHp86MKiuodkbdv1qSkl69ONnmnkJJmaUJFm0YntzMjVOYG6ooQO6+2sFJRa5P1ibcVavoweMxH5e9VlHMwHpys6FqcrRfOk2Hze/zpC5Pt+znPAj4jLoJ/oq4Ak7j921vuzr5qnk96uAVV7CW5d0M7V+zL+3h67rCJeJr2Gm2/uVnH9qz47OeftJdti6e9pOWj0jizwHf659d995RNp4iF12fyE18vcDnEzSofZDrI8QB4gN5HWd55i/LHZyfADfuG4q7w7bxusAWbfPDFKa/ovNmjU7g+AGdgroOvvR7mTfzcTVLfv33G1Z3Z9xoH7KW4W67wNE/ey//fziaNWeXHpuHxl7nj48N5vM3ys/7w0umy+pu/3tMTByv4x8a3ltrEMr5l4dh50bqbJl0qtotDknh69O1VWBaFuNLDxt+nlcex/MC46m9P9Xdfhvnu8AfvAf1BTwLeBRu/1dEHMv/K/M6rHJmvLXdtwo75Ysw2p3597zUi6FUdlbv9Hq7YJq+/MrrgNFKmulOj/1qSWS6Y5TjswKeJ0cj+na7tUQgl+8z7EIkgVK04hq3Zf8/1ExjE5FO1p3oWauPSOW2/bRsPURK8WpZHh8t0tvCfvp7ykU6Xt1Sq0xfot424uMmSyU69HxIx0exEgUdeFY/6YNElgPffMlheGLZup7xqZ0Kiv7H9MeKdAXdfneucPkzBQ2S7u9awvRTRYcnPhu3KKm81M1nc46Ser3INNHWUlGFaopd4xkqijxl1amXQkXR7ZscuHJV9Qefr1efOWkby3nprt1NLc+d4XGB/4Hza+YpGimYbuj+4rNwgemB6tzYHq4eMgn5Gy2z1svUybhH6WqB60DwK/D6Tl8nGHbx4nUV9RbXgW998+k+fIkX1ye4HuumyQJXhnOzGWttyeKlfVUtv2sxHL/ifOTbKjbuhtkUO4Hhl6V7J+ddMZwPeRe/P/2SPeeNywfpzmqOFyX2p9+ar+L4At31PrrNZ58F/H/wROTrXPd6G7PYfLbZ/m3u3RAex8NbuV+vOsDz477NSqs3rN7PT+j92JnF70nhHwO/NTx/ke9ZCzURyPEdul1lun1ZGuO5PQwKbfW2cZw+w1b74n7umyxPbfsi8jjHh6fVkTcDgvl8w1eA3wL9iHkFDoOPYX0SO3gExeoy3M3LD5n5OJRe9GpXssoxmIo/LqZpY5SUVLgjv1JHIpcSj517ngq08ftQ92sBTI/cE6Y3XyFQ2xPqcIMQgVqu6Rre7oFAh7/NYYpFILde4pM1I0QqSa7te2KtSJ6MjR1NZTrHRFPBRepfvOm6bieWH3UMK15Nlyhil/9uiwSJCi/p7xxWIhF7WL/HxgrSWdJx+Zp1Cuq01cLA4pCCkj6NNZ99TUGn+rdoXN5GSU/H3xwouinpd5k8rKQF2ULizB9K8o4O+rpppIrMfT5VFnir/tSP7mqTusvCeD3C+b/xBXH2X9kqEwPdwC6H+DziCByBroauAL/WMmjWISmM+1rgX4gv8Jd27nNNOrG62fbtySfet5iOYGox8SLXGXgu/J+t6ZaRxgxvGgY6ln1jemNvqx+DctbwdYdvhPfAn4Nfd9BPIwi5Htca/PnNqUns+/MbpQRZcf6HvIW/tk2naZ8ASxZXxsFOa2dwPQZ9D19BsuqsdlnEfbhbJuX63wWOn+BVyEfkoeHoi017sPrzzlADzPx58NsszMZEDwvg3wM9Dv2F68CXp6m/DL61lfuVwOfetjVpGSs5/+vL1OuS2TI10dhGztz/GN8saZO5GcPnKc9SDzwNI9tDbbaeehhKg++GthbEYBq+KKJfzXol5fcserCoh0TLmk+dVKIlUodOEeeaxwh0M7HWhNGMb+VnTC+KZHkyqrfHU788gXJSzqs/fhHoiF54bcfhIlnq9fWb7c31yXmGBl1+ibTa/EXExMESZW1yOLlqvkR5DeLdtVmeyNs0BU6iNvpPe59rqSCzJq07r5+loEahtXrnKRW0e3FBAZ1VUKpk3DXyo4Iy23o9MhmupHVlMX3feSipRl0YdyRTSQb7HZhUUP3xBxFvqO/wJw/kL1hQxdYl+e1b5dNN/Dr4S4i312161V8Xz/Ur8Abn8Dmhp+EnNTW2yBu5n+v24kI9FulsnbSHdJsfx3kc8AjxAhz5pNtRf+VyzpPydec8a7iV63XkIXQW4gi+0D6f9HQnxmvCbC5pWeey9a7uN3XrbVZXTTVOCNNHLS/6zciXqUxj51yVaYvLlhY3kjkvORLtEf9oG48vh6qD11z8+DhZEJgL9pzPof5iHnA/6gjiFXgCngu8xjn4GfAP64LnLlbfn1Z/Lddr0EXwBcB7WbL2qhvD+SjyEnrLV525fJgrP4JP4oj68/xFpU9oTRjp9dHzz3sZSuu9e05crQymrLQWXTrsU1J9I9OdhwZKNEP6a/P0TwJF/44cgRaPvT0mPEig4xkrM13jBLKbr2HUAm3vnxVSR5vxqs1xXezGieQ8eP/1TetEyk0oPGfM8EQ7MHhM5mORPOy3XdX6W6LB1ecWHnSU6PGZpkxhS7Toy9P5kYUS7b2fc+lnUwV5/5c4Udz7iHuebjxPHk/QKCEFPfqWUhLfSkkxZS4LZ8xSko/e1g8j9ij/xOErVcCJa1msvuQeHKV+wOJ/4dDV60pkqpf+ue7Hc0yXWk7ZNzpHpnW5NkEDmP4+YqMpGDyOoXvBb3papektiuQ48ChrrUdpIv8d+IO8Au40SYhao0jj/RTkFXxg8EHwL+CFV0Lzb8GsPjYa/fTjJ9//jTfkOfJ+aPKRibZu/PpQ9+Qrsz05j0Mcot8DPQWdP/Q3kZTJIP1e+24n+HejbgCvwHdQx8GnkEeIR3wH+Bp8QpxjPE2/Lq5X6cfjHnoI/tyuhI8trq3g9QO8C3k0K32za47IeR58KtSfo4XWLn2i+LpChyCv4Gfq2xqEBbDxzNax/N7ekeXnsg0/YsfKpDh9vfJGaRjFda8dVpIbSq3X1116ISqYXjq3zO/FeEz+g+ZWjRwkks5O/fCqrUh7aOq9lDieH99n134/JUEgRt7mWj8S6NbZb7T9q0C+jV5fON1JpCl1i6t+LBXpidp5Su1QkQYlvzqkd1ek3mYhry79EEmnOD30wFCJHu3qc79sm0QDolJNq89JdOV25zWj2yhoYrsprIQqqDBo8odOGxjfsv5a9OGygm68XGuq11JJGnScPJ7rFNSbMduz943cwuuvr2V1yaMI7ldObWXzsmsYj2vgA3gteBb0NvQAeDSuRzwV9NQYWfz58D2hh4Ev4B/g08gX8EDoC+AF7kceQefjf+hf+Jn/5nPIf8QH8hR+DvQU+jLId/Q7S4bf6WB6nut7fDfuh1898beBw8av3hIRPZ37c/Aj0G9CHiv86rDQZjq91SPr6uVc/yMPgBfgicBL6BQcoddxDh4M3wvzi3lEfmDeEAfgj607DL8/mOmxoNK2nqvnyBSiU2mZMZyN62XIJdMHYaRunf9xYk4osSJhpkoIpmfzNIxLSY09Zz5RBklk/btBJ1I717aMUnG+1dB1iKr0INfx30e07TyG5cnUu2Nv1GkvUse2x96MdxTJNbDBhbOxIiUbTbGfXCT+0T1+BesYE5BoVdTcbVK4RDnXN+o6nJao5bqf430rJNrZrrr1ocEKarX3M2Uz/mXc3Tu8LFpBh1ZGfkhmej7Ve9xsBdNR4Lvg//AvwUPQj0VdwbpjPlFXcI66B7xGftS5IfZLiOTzDh6M+9CXxBF1GPpiQXGTqLQo7rOA32C88J/wP/wq+Erwz8DnwNMRH/CJgEuIR9Rf+KeID4wTuIZ6Ct4G3or/cQSeIf/Bt1LchedBDLfmBL6ZkM90TN2Yn7opdrzv+NIv6OxOG76v4EK07bkW67jPgXzp1aH9x+XsvlH75575xO6Tq2za1nfg+AI+hH7PwNEHuzkwXVFo2vfUVKarnloudnzqzP056B3MF/APfMHOb1bjdnHcH3P0mtJOz0WmBrP8OiQy3dJJz+RNXyOZxm342czAOIwWdhiqvUc7hMyMb4c8/0dFZ/V//FxwXKLGL983uzBFpEtDjmz/fESgMQPSt9wNFsjk1SyfcJYnD/pPrH37tkDXAm6WPG4k0oJwrZ37uoi01ONC365LRErThPFhkW6aLm3T8qpIcak1Si2GJx+62LqvGSWR0X8Tn64d2DN9wnWJYu8fKDOpoyC9FqFBy0YrKFBTHgMVdP5TtzlB5xQULo1v4qql/FN/4Pu1fNFirbCa+/QPok2LLVb8rw4Ebmw0mX20B+NfwfLYd7bZMuU1bDHu2FGmPwuu1ow8xesP/JAFum+d6mZx/wjzDP5m49Pc9SLj/8kF9fPvFjC9vFArvvQC769AL1hG1+76gL3v8YeZ/fvlMdz74Klfw/S7k/mVLtMZP7xzeeu8V+VMV/jHnwt/wuLQTfUz/RbXwRi/X+qvWoUHua911bPN0oQMFj9MNWSe57gAvwl8HT63vrZd017se6cIScG+x3g9Qd8Vzx+bHm6zN5zzGuAe+CV8VYwPfA7+FHwt8Cz4aMeM9Kp3svVxLrUb1Xg1xwcz54Fzp6zm+2taV8xp/XIs329Qp2JtTepUrpPgB4K/Id9sXmRc6M2uq/Fb+eCMBeefnX3fuRU4cN8XfV7kP3grEzEPr7K8tjttpGkpUPNV4+94tQijDLMGtb7+FULt0yPOOFupSOPuBb6SaGBw5fGby0T661x0YKdCgTb2btOvXaxArk/Tuz9LE6giZceVOY8FGlmSaGf0QyCLFI+fp0eIVMc7wmrtapGqa+q9vXNRpBb7C15PKRWpShMWTSSaaWPf0ovhyfUvNmWxoRItc3qzVfVYog17nc/mtFfQmtvqZqvGK8ix1iT9wREKypN0R915ofjTb4AfDh767743cBs8BXUWfAB6DnoYeATdCF8efAr7KIomd09WFPB+F/YLQa9gHwb8ffj/+VnKGUkneD8L8Qf/E74scAQ86ZmDo123m4x/FD550eMh4+NyWOTJMhafujoTblxm36G96mN1JuORNs+fG9xg9dxwVKXTFX7EOJEfiH/0G5Bn6FujDkD/wzcHP6woSGnteZjzU+AtdN9JT9Mpnnn8+1Gv4Ytgnwn0DPgY1gV6A74j9EZEQlGv2k7s/RrbZS5bz7S/mdLiPhXqJfQX+C10Hnx99FWh75A37Zu9mHTflvt/jRwvZ9fqxXhvjIYghlFNt1dXzDqHkWXps5dzpobQXQtNp1JFmq7zww4Kemr10vFnuEjFi3rkdKpkemRl31Ct8wItTRTyRuQJNDmjzvClTwQy69ZtbM8vwp/+iffmn0WnmD7JMeq3yi9fJH2zEwWKBhJttmlvWTJEoi5JTnM8PCR6Uvl27pYzEn0f+eFaZGMFjRo3clsnSwXVHqdhngoK+554cX2igiSTEVccjvN+3W97L5PrCOyPAE8HrwHvwPoAB7C/CP0A8HnoV8QpeBD4DuID5+Az8N3Bj/6tT7AvD3UeeQP9DB8BdRt6ZMV2/9x4xp+tS1d1vbuRxxv6ANg3VV7zyuORC+/7w8dDf+Mfsw1ut8I5PiJPUWfA24Ar2JfQyEgTITL9tkXzGY+po3Fa+P4D9D0xLtQl6ETgC+oQeB38P+h31Hv40eBJmAf0rbBfCHEPvgCdgnoI3XVebtQpM573dYCviAP0ycBTwQdz3T21clg+blzWdYJ5R7a+Vy+mRS4IIw3ru5oYQppdg3kN1NTv2WjrgesUZPl1fNoUhgd2zVf0O9hYpFOxd/aevMj0ercbwsVbwh8/bODxos0lBiJNDdg0On6aSG+yh3Sa4COSn47F3glHRMooz165tbFEU02uPdpqLlHR0pjYD14SnajsyiCa6/daLTQVSUFBrvruSkHxh08iLqCHE8tjvgQm8/r46cOwyYsyuD+PeYbeAJ6Dn4GXAceh3/A7fCT4ouhTwXeCrsA+FuAJ1dyMGnGJ90Mm2vsPLszl9RU+GPYJo16D/6Du+xvW73IllesPrD/mAf0U7EPDvgJcB/8V+ijk//ZBw6dG3gJPwcugXxB3qDPAa/he8MVRL1AfwMMwH6hP4F3YX7bRatSGQSv/F/+B56g7mB/sO4BORD5dFbQGpi3nfAk+MfajgkfCz0AdxPOB/9jXgvcDhx4lbPLZz/jeJOvzJ1JWhJF1G5eWwpUQCtwY7vFkpJrqPhqw3iub6QOfKgOjNhJNPxsfYzVSpPxwt0bKVwKVTS8clFsmkPv6mW63dUSqHN/1r0kDRarwyhwwdpNIKQlV8dVZImnZepTpVYlUoCqpmTNA+uOjWbqdDCoOkaiFRbsA45sShQ387aRT2+uLR2bqK/6sC74TuvqxLv0yW8P5JPQnfBjoAcwD8Bv3Qb+gDiO+sN8CvBc+Ouoe4ne06fc6z47z+UU8od6hHsHfhD5EHxNxh/fC94EvNMhrx6vDfjweoQOAa/ClsP8D3w3/DjjWVQPjTpznw4fCvF233DouxYP7tzlvNYSK73uBr4x9oYgzvAe4BB2H8WK+wB/hkwG/0N9F/qLPgjoE3Y391Oh7gSchDoBP4AXYZwB9Ah0P3EGfBjoI8w/eh3zF7/C/bt/wGHi0J8PZ9cM/PjwcRiM026N7hVK78060K1ZNuye80h7QXPmnb96g7ICH2waRNOAfOkgkw+MflxzsKlJ03SWzrw4VKXtW2jLzWSLtYVEYqBRJadZw+bWzIvXJHjHU85lIhTaJyUk6Erkazl0+q7tEAR/q9ursyPJkoWaGeL8R84XvBw6g34Y4w/xhPzf27yG+wR/Av6EzwNPAYxHH8H9epa7Yct+N82H0qUPNCnQa28t0udi3U/pivg8QvjF8VOxTBT6Aj2A/BvaP43rsn4ky91xVyXjYb/rH8u/2wgsPJiTzPEGfH3wdfQjEPfAFdQXxDF8ZeQq+AR6Cuo/xoV7j93/vk8L+HvjCiFv4AtBjqwoPtBUZjpqn2rEZ4X3N1OGaDd2cz0G/wKdGPUB/BPshgZvwGeHvAtfgk8CPQT7iPswbfDzM67/nC/wTddO8ouOkqb3Z+E+PYJ8URsuvGze0tgmluTtGftLtGEy7m2mcYOWfvsYG2/MbphwSqZmmTWwmksala/JNoOT1tTLdywWaWG9TjxXFAinGfB6lrCv+6aP8ttkmi6TZhXB4CdPxpTkzhu1k/+8nV9sDItn/NhZE+g9Ugun2AQAAAACAAAAgNQAAsxwAAA==eJxlW3VcFOvXx8RERTFRsbuBK9axsLALAztQbLHw2oUKdncHBnagYivKzOzOLoyKraioIMY1rv2eZ9ivz+9z3/vP3l12J54551vnsVny3qBZew2qWPTA7+C1BjXc+ei8y0aD4l2mt7nFn+fu1f5RzT0GaeMLD404Z1Cxq5Z8dQ4ZtKPhlhsrdhr074/qjScdN8jXNTq8f5RBA5cvO3aYv38ycHXGvREGrXDyOjH8oEFH9hT9tf6AQbvaNszb74pBcecS8xW9aVDWq8nfMp01KGPG4I//Rht0tlyu7Cd2G9T+WUu71wqDZoW5ea2dZ9C5kH1NRvLrsg8rgrYsNkhtOOjH93CDvrZVJ9dYaVChru+bvVhm0M3ud+JcpsvXgtat26bPMijStbJL4DS+r76F5y2Zb9Aan175824w6Jhzj5kl9vPvM3Z1qXLUoOSRm18v5c9vONff0GWLQX77S4xZsouvw2fyj4d8XWWfzd6s7ZPXuWlG2cvz9si/H1o35Zi2yKCa9fstcObrGt+99fAGkQYtbnguss9hgzbuqfNs8GmDfp6LaDH3iEF97AUP7uDjNcno3njVeoNGuc6+GLvNoMmFro312y/fW9tmbn6T34/9muvVKV7/Sjt/7LzL5306/uesB3zc3eUqv5/B19+m5tj8n/l5nEp9EeHCz+Pe/bWbD181KNbt4fOS5w3KIm5rv7werFvXqZEn+/N6lbvbpcXXlgaF3xviNGpmPJ1a49ksea+dVpfdtfWen04jW7fr9jSdRtnORO+s0UMhj7+jvydGx9LMrPfPbNgTS530N2UW2WKJFy1Xr/aK4/gK+TYXV65Qx9PF5iZ3UGnJ6B7vth9SKcq7c/g/f2m0fp34T6P+rUrblPIWqvuo3aI1Iy2U7vvL+FVWCw1Kl/f0+L+sZF7eCSuNnvJmXZl0Oq3a0vn7uHo6eV5YnyFjsE7p2szJ2e6QTocPeFbI9ECnvNMitvzlZqMO82c02dvRRoOjC8YumGAjT7/08fFHbXR0QKnch5JtdLN4jnpfitlp2Zsp5NXbTu357K6z7dRA+edxKtdtguVLp0Sug6oZfcr32y37A8/le2SWX6eWG3Tw4lLj4GaDzNMd47rlVS5y0qCPbjsLhfHvLrhsrLX9uKyj8KhhWb9uNahnctick9x3H5wzWKNDDcr+dmyeRwvk8WIflw8Zz3V/fY8Tl7RBU0PSfbZxf0U2fzI5X6Q8zvj9STu/cP39Tqrep/cMg7p87pXnxyiDStxolLXWCINe9f255coUrqOrPaZk478nxqw9u3qprHPUx3PDJ/NArrNMD3pzhcp+3+DxuoFThMQL34HdrhVZJ/s05aJPqVZ/G3Si5pM130IMchs1sNjX2Qa923Pd7y++ny/jH2/Mw+dZ1XdM7X/4PNM6vol7z8cxH/tq2U+/mnx7k3zRoOmh2/nMBll+BLnkVg2q9XXwhiJxBtU3F0riC9YD+IP3C7tXmzd2u+z3KR8Otx/GfWa2+yaDzOXi+xRd5svPyT35qXdhPu/21AxL73Lf9A/Mtun2HYM6hdS9PPSSvP7dTQXg8XP377p+5ax4EqvSZqOdNtSOerStvE4rwjfOrf9GpQarG4xrNFWhOsVqtS/0O5Za9d40oOHnWDKsGxZ2LqhQeQEjIQrtjHk74tsxha7Vnp43Wx6VJnT2ahQ/VaUMPct0c7eotOOQh9bNU6PKU1/O+rZao6WzXQff/aVRLttLl/6BFlrHXZ4h1kJh7dJV39zISgFj71coesBKuaIKjbyYZKXNaz/1L19Op6TvEe/tbXQSq9Jrrk7e6d+fmXZJ55o/0zJHehtZvP9iKLHR6JNRNer3s1GZXmLFbeTUUdyZjRIfBQbUzm2n4ZMm76rcxP4HN/3NRpJ4tTzkWa7MXLefU5d82bfKILGKZfbJOppRKeFIHsbhW6LMJhoUMyPlU+oSg7wnLHh9cKZBzRy8hDrxKp165CMfN+2+DCq+6cyH7nz8l6F5Lu9YJPG6fNOLJTrzc2+3PJKRWOIleGvp1n9rvOB+sUU2jm23T/Yz3uM+6g071WsIf+9ikjiBrPNhlT6vecC8NOhZ5ZShoZJ/UL+WmBPb+m+U1/l61dEcYw7IugLPrWv+q+9jxuePV7I8sV03aE7zIs0PXDMoeEbfxcUucF/+aMO3YlDoHv/YmlyHOfdPKvUP98E080EwTpwQBCuvc/S6uEE1mE8yTC3Jt27Qvr6dO5bbKvsVOIb1XHvx4NkQvt+I0CHjnPl3L89dr9qBr+unaDMbr9uecYd/WQ2qs1yZ3uKCXM8ti2NydObrHRC1y1jKPNbDdevu1dx/4ilOPyeP3zZ7b4Y87p9bYds2DjEoyGyUeLr7a9WqsrvsFFSwQcndTXXyMYlBo7CaRbh1FXptnbZzfg6FLn+j0K8fYule/kHeN0orlG/1pIYJKxUqePSMEWxXSLC5l7NKYZ0L9swyVqVMQ69vf5Wi0pYJ/w472kyjzNW+ZbOHa/Sl2zc90yeNHi0QQGChcowu/twn/LCn1ilmdeCflQKNpKBKn61kHSz+R6dGokyH6bRbD1nUa7tOnSMSMhy8qJOogua/dDLhpZKNuHje9Oluox4DBWPZHM/ZRkIN0Hfbn/VHXS0Ry8frebTqyB3pzkke7zBs/cSN22Xdb3aeGPjmpKwLvDZbl7PmTa6DET5rnu47KnkEzx187nyy1eHaXIchy8dpzxj3+pQ+/jxgoUGMRRurhkl+gB56ndTGtyLrqSWF9oZP3yKPe3zxvrLzzxgO3pX88O7+36ef8fNPmBJQpCLXQ+Gw3cdWXJK6Y5+LAB7JK4L9jnHfmHKMz79h7NyJUXzeLEu8F3fj948FrCyXugf8CR7Ceacn1A/ptlfqS+D70RlCgBiU69ZvH3UN65vl/kkFmdeK5Q9q889ieb4DPg2rN2ec+bTx4/n3J+Q6QodVrtSmVaNTzCMNP0/+EsM85vZdSWWd+k+903WHnZLfK2ISjUH5zRvj62dWiOb7n2D+D+vPeoKgDDKX0SrX6XMpgSSy/3FfC/fHnq/EOnXezc6X9u6Mp7PTLo28c9JOrdYO5c7R6cDeS545imuU5HTJvf40hboOeuR2ifmknXmDsbQ7lxDqiuM4Cp0LuDqx/y2FartFVD+Zm/XWIiH4VBpXIbLi90iVjjx5xcjEffdz0Jdn/TQH32m0YK1ry481LVSDVf2YqxZ60qvq07o1rA7dbXXwr5XymcJDp/HFZ8SXbavT8pI1DzxdpNOod3P5DnTHdenEi99pXGnWWZvesgKwUfP6TXfUnW9zrJeN3orT8voOCSl2f9MJqYOUQPGBxE3oV+Bil4SJvu8uSDwF/gGP0HfgnUGFnnYrwM+vzPKXg/IpjH8jBVFJ/L3WRSyoPA70Xsmfn5nxWR9XEkpSPi+Brgv4+XfzOX5jwnnpj1AHqA/0deAHjZlV6hPwRq2rRxgJJC4UqBRUPSf7o0OWGiytDSplNr70Kc/aCgUn+eZJ6oEHE7bJ63IrevM5Me5We1A680zmXRO2lko+uvMp+4QrjCsmHR6R6/d19sykh3zeXl8rW2eflTj+PWDEtV9Hpf6qW8i9zCEL+7NCvxskXpbPo7rr3bFVua5LZxfMIvviflXP20P5eoYfbcZPXupU8A/0M/AlPFDXidev5P6e9cvxdflk//vuE+7/VZXOKb6sW/miuIN5veu2tS0LiKeF6QXw2Um4oBEddLqYceQDrZNG26LalqqySqHE+Sf+zeekkJZOOLRYojrjnx+rpzh4XKHlAUJpKrS0xsQqJYqr1KVNbi5plezhvnEJN1Uyy6UK66zyAkE06i3aIVlz8JeFqptG0ELBZyqX9S5udTxXK9kTv3j/TLCSuLvgHDplEbKe/ZN7n78Ht5yhU+KuDVc9DjOPiLK/p9PqEovHjylio2mj4rb8bGGjy67ijLY//Pz3VjdBfX/8XANGQS/NoDefhMCSfwfP12WXmY7rxDwt459pi7jezPbjvpoUNf/tVf5eDLO+F9fpD6/uO4pxnQ7I3silFevxjV8Nd4+1ElffdhENIL8HvYXvw5/g+3huIczalbgvrnwqH7CE66XcsPgmnnydaf7LoMbmD6RP7tt9aMds/N6v+7zat7ienIq+ULLz9ZkwskbyR7STMIYGmbHDLumTmj5w9jixQP79RWQZhmDpd+G7UdeoY+gX8K6xyvqhHvMbi5D0KVy3ffdnDLuyTvYv+t0WsGfZ6lipK9Gn1QcKJ2aQcM2Fd8jnVC1sgRZzQuYmourbxUh+6PjhtXuGo3K9kSuIVYnm483zcC6jHpfrCh6GHoNOLln4QaOU1obDR8fTydzPts5Zx3qd3a9bR51+JizJt4xxP+18ikPPKOTmv2qqf0bWW8d653jeVHHgiUIurDq631EoWshEL5V6rkzwWBGu0qPCdypeeqrS6UMZksLLa3Q+4cX1j3M08u9743VXq0Ynq8QOX9rSQrcLZGWqtdDabyGdlmWzOvrZSkOdRs3MeM1KwhVN/mKlYe8rOF2vpdPVxgeHPhyjU7ER7kfyb9GJwX5Vyh2dyhZr7/08m42+Nd1culct2x/8CErowRJH8gXeg7/BL6gzrOMNIdcvSN2C9QSPwG/DV9xcLIjUoBrJ19q3PS5zLegv1Bf0y7ET51sMYb6ZlFqfIZh1tIi/4qQexHGR/8A/5GCU9uV6S7XcHVFgvcwNcHy8Ip/L+TNvwAHWRe+rFni/aa3042n+0iDTdk5mnBgmKln2bUvTcBtUhVH/2AT2b8Kuz5R+DP4cucKk7KXLTwv/nxwu9eaVxgclfyLvQN/NETaV+9C0m4w/WfOH1rrA91MvuiNDnszbzjNK1d0l7wfHgf9K86FSLxecKhS/1LlF6wvklLwH/Re0c9eHCXOYl2497eQULvOPZU2r7eg20qBM15Yw8rP+zepXb+vweFrKbjXrBTsJ9dNjik7BpoDVKMvY9pdb31NouLVy1vadFPrJV5FYQyHTZvgqDn2pUFLi3fY1LOxfhM2oqVJc9SlNWy+Q/kS4jlrtNYc/0kigfs7HGpXP9nFBPe6T7p6bNuVYzP3yreS2KkkWmmAKKatDRzO/1BArayVT5hbQSajmTK11mv/x3u2ZwTrpwj7t1ymqU51uv5P0P/kg/C9yG+STab5Krh/qEvkJ6qznund+P8/J3AW+APoBfQU/PXfdyemD+HluCzz2OviE1B/AM+gM6DjwEeoFPDLaLBCpk640v7qyxXbp19GH0Hs4L+rSLHfWNQsXP/tQ3M593bxL3qYPWGeI9nhiOHQy+2kBg7eZ3xKjgwZdlvrnm6DBHVL/jRl7oUmHrZJfauVvE1huttRzwF+sA34P3YN8HXwCnQu+xnvoM/AfngtyxBOPffs0Wi/9GnwRcgHoXrvXilEno6ReBU/Cb13zODx2CPvFNP8t9eReAXv8Wi561JQ3fJ3ucXm5Ulin3RREH08RDwXw26mJgOmFuiNv0Bx8qBCbqDWezRTKaxp1hWZ1FYSgkElL2xSKGZC5YuIjfr9jfGevRqrDP6jU4Uu6FiOYT0zZXEojgfZvx2oUXFUgjEbpz2VyzUcWcu6ztrVbuIXSmwVlcfCClZJ9Xk1NHMY8ImKMRCv1rTd73q+sOsU08+h9u5pO4qmX6q9TxetfN7Sfz7or6dKD7lyHHvZRfZxZ13rOONVw1lPGqy7nloU8Y58c22pFR53Xw0soToNOj/+r3Xj23+stgniMP78Hf0DfmDHOKckD6XZ6c+nIz8E/6Cv8fvDWmr+msg4wYTZK5jt4btCD0F8mDXM99fYTnzC+uYjEUvIW6u0eo1WGVbLvF9gfPs6+QvqbmUcr+E9aI3Uc8lHgRr+aXapXjJA+34yDWH9uqioEjbzvpmHDk75HSL6Cz4aOwiv6CDyB+0CuB9+A97ie3yI+2ir7ETkX8jnk8MAP6C70kYdpUKTOQ04F3Qzdh+eKXAx9hTyzuxm0GmTGq6Gsr2/t5SdjOPJTg3QR7/aMp77MYlVi7eTf88iFlM06mTR7T6ML78UBVco92Xt/A3/ZH8dKN2xTpafi8EcKXb9/Ys4UXaEXJB6kStuEnByvkuo7pdzgaJVuV7uT815+jVZ+zswdodGtkWf1gD0aCTaLdbOQf9kfHWmUhQ4E57jR+62FupqC00o/QwVhWOlKxYc36n2wkmlDqur0uX/5cne7sD8Z/cI/mH0K8AZ4APxFHoK88oG4zGOyruFHoGuhs+C34Qego8EnqKc0/ch1P1JUkJwvIk/9L85DT6Nf4EvhL8AX+P1/fT78KHiJOjZlCDBIPJ2e/6Pn3g9Qe/ndkPWB60KeAz+V5CWCbNnvyG/Tnqf097hv/B55NXIsn1vXRnjOYJ359bR353CZj1y+GPz2yXLZx52UW6wYDPrl4juzAeP4ECUqn///8Cj4AnMr8CV8CuYa6Dt8jvkKci/wPNYR/YF1S5tjSP1ojhHYj7U2hQT3cYnubNEZ58wgmHGjRpYD7j3iKfi264dGVruDV3TKbwK1hezX87AlUKnhpWsLC7eWemtF0SIzJ/WSPt7HHLsodEaczlklU+4FqiSmjB6aSiZ9uGmOuYbmwHGNUjztHUPqWih0hGBACx0s0MTHFmmh5K7Wlm+LWMmUN6y/0nyBlVYGiQRcp8f3PgYS+yjoVOj/RpXEysn6xDwWuILnjnwVuIL1xXwE+dHK0Lk94rgOzfHpKbnu0ME4DvIlvAKH4S8qKLljzvD585oGWeYuyI2QP+HvWx/39825W34PuSj0HHQ6fJJIK8sfk7yUxvMSf8+IOOaUrA9cJ3gNeIp6w/2Ps3+/fnuzfIXeR66MPMI/4++eN5m3Pj4WAob1TtGxte5z31RY3bNHTq6/uuagS+4r0Mt9KP1qvcw50C/4HeaV2HcAPwY9lMdbOBiueyEfw6SvQo4OHQtfl4bLkv/A97rRNaXaWZmPIZ+uYRp2xrfsh5e07WXQ7KEicIqnsMKtr7zLE0fm+Pa97sjBGOcnrQn7t61KzZc84spUSExB6rN/z2QaZcUx/1Qc826FOgWIybBKu0UMNZb9u/rq6No7Kp3td2+7mlkjE2b8NIf+12hvwaRRjUtY6NrNn4wwFjokaFuzUMqD4m+7VLI61tFK0WJbx3MrOUUOZMml/8Ef6N/Bw6Yu03ndWggaYXzbExJToc7y/+8DwRv72Y3FMw9EfvJt3JP1WT6lysF5V6X+Av4ArzOxqu6jyXkJ1hn6zYQf1v9lC4mEivW5gBP24wzaXWZdk34hfaXQ/Al8PlOexhuUmVXndfbvewJEIm5QSgexkYHvp+2aa1df8PnF+Pe+9MG4/uJ+xc9sPS9zLefk3+4vFK5vVzGZkvtgXOYMTJf3tNTr4K+Lq1LuZOH7TctJJJ5g7orjtzJ/KPNd8C/0JXJVXB/w/+FisRFD5lrwH8jRTDvKz+dO8z2RU1bLfHlLd9H4cn/Nva/Tgs6Nk/sNMu2NGDRsquwD5IHQpei3iXPiZhXg77nOv81XLvUnF2mBFO67gPqi4+ScF3oWOjc9u4Vn3NfRRZ8cf+zL13c9/yz3lfFE4bmLjXCPI8FWOd1s5Hs2WwWKsJCLKRRUB48qVH1mz4n/dFbIPN0IxYF3CgWFXig7LF4hv9cZPfN4q5TPZG6VxHS9yW+V/NgVvCmjUbW9o1hJaI65nEafj1/ps8LLQmbMu95C/9wQG0ssZMorT6sjF7dS8IDJl11z6X90CPAfOhR+GfiGfAc6BjgL/Q4/Bz8MPoJvRC4PPTXC3AjA53W2FOpwV+ou5MvwK9iHgXwf+X/Fjv2Gl7gh51moP8zvkMuCR+Bn0vQv84Cgr0Q+jtP1WkNesl/2SV3pwj68lGkDWRfVy5Vq4esaZBo31uti+W7LuRzmiy8CxMRLzhvQZ9ClyJHh/4EP6K8xpiGQ/Ac9Cp2G/sf9A6/hzzGHhJ/5r6+C34BuQv/YnR6mz7qQebDp0FHv5sqcDnwCPYf5J/QtfB7yM8xVkePcvtg1a372IyLtPTldHpfJWunfn3WrkCF1uU+/j6s3eGs8pSaLDTtxjn1fNppibjCx0L+dxIRCpbZRl88GXFUcvKiQS7tDKwfNVxw8rTjmEHJ+ktcUVirdF9vHMmqU1FEQjebIQzQyZeUX7hdWo0eGMH98y8SUY6GC3H1hNa00W4xxBlsduGelWUkPr5SJkfO6AI9GLMENqmIOFOX+COh05DbQHcixsG8CPIx5APw8/Cv0POZR0DvwL3gPPYPcHfrov/5ETGm7HpX6H/UL/9zvcdSX0TclbsOPuJvBOfehiOW3yBwOc4DTDWc9jVkrdTbm/sjxMN/AccGP6FPkbfgeeOXPvgSxPYf7TaSLj7kv87I6H2zI/QfgHfQBcAk+EXkBcAg+Dfkf/DvmU8ijoSuBH5hbYb8Qvo88GD4FeAjfhfkh5jrQ36gD4Cz6DHrwU6BYKcbFt78mHephOPZfxTty7zhHDmEj5ywvXr7/2+rYD8J8Ytl1el+K4ti/p1BcaFVmBuVPHvbdVH4qmdsROqlUd9Hxzg8Xq+RRoSRbcJUe2INa3B+gOeZiGplw+Jv9iaClMAuZ8Rb797T5pdWxftY/+QXqAuvsJWzNZfmcJguZpchcHesMvwc+hz4baQaCksfh3/A5ciTUG54r+B0+CDkL+GSuZViKqyHnIWn7eSS+Yv6CfcKYc0L/ALddzUGR9B94/lgH6G7sQ4NvxveQv8IfYd8NeBd9Cz6FLkPOgboDzuB3yD+QkwMvsP8A+wixHuAP5FvYX5Y2v/7//I88DrgDPhPqLOmS9Inop7/MQZ/kI+TEyHWgI5FnAAdxfPA/9rVAT4CH3LPcTF92NB+v8Nmmn27FO+opzpHz2IhFW6lbT620yW9Ml4SJGlU0NxCqjlxGcfg8hURqnv0184ubeMIqBW4oEpd3tUo7O/lzq6oUK2xHA83hEzVq3Pe5XvKeRhfLigu2kFi10LkWKt/yduvzCRbKkHVh8QGplj98gPtEDp6231jqSeSMyGHgB7AO2GeL3yGfAQ6jvrDfAroXeXpLv+dvsuyRuuWWGAvEyPVF/gK8Ax4h38QcGfNj+H7kpsh9kAshJ0UOCx8AXkMuhX01qG/UL3isrHfx2/MWSp2PHAo+HLoDc0sGm0Ft18h9L8iVsS8UdfbfOTZyEVwv1gs5AXIy8BdyBPQv5izAIcwZsZ8acy/k4KgD5IXYd5y2v1b6E+yzAe9gTgMdh+cO3Yf5Dz5H/pU2b2d/e6lA2U6ZmL9EzJscR2MyNGCrYqfMn6oEn6ms/5mbfxN2aoVKfc1AgXXYxvtv2+dTqUvQ54aVqqv0ouT5vMd6q459YirlGZ2F/6TSmr0iQJM5V5pO1Cj2ihioa479u5Y/80asF3QReAB5BOoM69fODPrkfjrUN3Ij6G/4DOS9wC3UMZ6raTNXSD2MOfUjXs0IrrcSE8QOTKmDkRsvSvXgv8h9qtivDZ2E/RjYP47v43vIcWvXXPLj0kWJn+gTzPnxnIEPwAvsIweuoJ4xb8V+A+QP0CHAfeAo8Br7bLE+0CXYT4JcGLkYcgH4sQ5b2z1ryTwq0ryDdwyaPbLa0HDWbWbM8UTqOfgX5NTAA8xHsB8SOQByRuS7mPciJ0nzB7IfwbfQJbherCvWC3oTuSH+HcL8TRXG9R7A+GXtd/6ck+HY5xtPzkdqsXSwkwl/2/Q/c43BX57123ZLJeHyRniq9LSU+S9IHPv5FUedKY7cRs5RrEK2+ql06akYdKh04dQr67SdKt0QNtCq0oe3taq6Z9Ho/wAEN7t/AQAAAACAAAA4VQAA9xEAAA==eJxF1HuIRmtZh+FdWcREWZQFJmaFWWllFiPlTA6JSU0WjTgUO4tRKkMqZNPBJMWydollTZpleajI0ijKDhB4QiJEQcRERGSyA2KDDCFhJTHlNXA/zwcfXH+utd7fe99zz2ve+uhPfcbJPZ/8/eQTXzm+ftErxj/47peP3/ugl42//d7L8Vte85LxN374xePXPfJF44c++/7xb/7tC8ef+b8vGH/i5583/rfPfs74Xb993/jvvvzHx3/4588c/+o3PWP803//tPHFd3/v+PQDZ+PDH3ry+GH/8aTxwXO/dfyfn348vvr1x47f/sWPGf/Vax81fuXXP2J8/xu/dPzsJz1kfO97vnD8xKd93vjRH/ms8YPv+4zxA27vGX/w8/7rLfkvH/HR8S8e//P4+57yvvHX/ug7x5/6/LeO3/fSvxn/6etfP37+W189fsr7Xjr+yo/+yvi/P+1549//umeOv/3es/HHfulo/Ltv+IrxE64+d/z+z//4m/NXP+sd4+e+7VXj3/mGHx4f/cvnjJ/zhB940z7P7dFu4+Y4f/Mzvutb9twvx5/4+TePX/fI6/Gjrg8en3/hzQ8bf+DycPyYH/nO8a887unjDz3wZ8YP+dgvjZ/0wd8Y3/cPvzd+9V/88fgdr3jD+OMvfNP4y37i7eMnf98/Pn7f/Wr8R1/z7+N3f9F/jv/3U/5v/AUff8DJfueD8cmHHjh+6lMfNH7WOx48fsHjHzZ++V8/fPxnX/XI8dte9ejx+z//cHzzy48bP+D2ZPzg+75t/OiPnI6f+LTvGd/7nvPxs5/0/eP733gxvueT7frln33mnbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cratXs4G2tX1q6sXVm7snZl7cralbUra9c+z+3RbuPmOGvXnvvlWLt2n9dj7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF377ldj7cralbUra9d+54OxdmXtytqVtStrV9aurF17podj7doNn4y1azd/OtauvSPnY+3aO3Ux1q5/+tiP3Vm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXbuHs7F2Ze3K2pW1K2tX1q6sXVm7snbt89we7TZujrN27blfjrVr93k91q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytq173411q6sXVm7snbtdz4Ya1fWrqxdWbuydmXtytq1Z3o41q7d8MlYu3bzp2Pt2jtyPtauvVMXY+167LPuu7N2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu3YPZ2PtytqVtStrV9aurF1Zu7J2Ze3a57k92m3cHGft2nO/HGvX7vN6rF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbVr3/1qrF1Zu7J2Ze3a73ww1q6sXVm7snZl7cralbVrz/RwrF274ZOxdu3mT8fatXfkfKxde6cuxtr1a//6M3fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra9fu4WysXVm7snZl7cralbUra1fWrqxd+zy3R7uNm+OsXXvul2Pt2n1ej7Ura1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J27btfjbUra1fWrqxd+50PxtqVtStrV9aurF1Zu7J27ZkejrVrN3wy1q7d/OlYu/aOnI+1a+/UxVi7Pnzv8+6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q7dw9lYu7J2Ze3K2pW1K2tX1q6sXVm79nluj3YbN8dZu/bcL8fatfu8HmtX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXt2ne/GmtX1q6sXVm79jsfjLUra1fWrqxdWbuydmXt2jM9HGvXbvhkrF27+dOxdu0dOR9r196pi7F2fcn1C+6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q7dw9lYu7J2Ze3K2pW1K2tX1q6sXVm79nluj3YbN8dZu/bcL8fatfu8HmtX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXt2ne/GmtX1q6sXVm79jsfjLUra1fWrqxdWbuydmXt2jM9HGvXbvhkrF27+dOxdu0dOR9r196pi7F2fcdrX3hn7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snbtHs7G2pW1K2tX1q6sXVm7snZl7cratc9ze7TbuDnO2rXnfjnWrt3n9Vi7snZl7cralbUra1fWrqxdWbuydmXtytqVtStr17771Vi7snZl7cratd/5YKxdWbuydmXtytqVtStr157p4Vi7dsMnY+3azZ+OtWvvyPlYu/ZOXYy166eefv+dtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytq1ezgba1fWrqxdWbuydmXtytqVtStr1z7P7dFu4+Y4a9ee++VYu3af12PtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXfvuV2PtytqVtStr137ng7F2Ze3K2pW1K2tX1q6sXXumh2Pt2g2fjLVrN3861q69I+dj7do7dTHWrj946IvurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9au3cPZWLuydmXtytqVtStrV9aurF1Zu/Z5bo92GzfHWbv23C/H2rX7vB5rV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7dp3vxprV9aurF1Zu/Y7H4y1K2tX1q6sXVm7snZl7dozPRxr1274ZKxdu/nTsXbtHTkfa9feqYuxdr3rAy++s3Zl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7dg9nY+3K2pW1K2tX1q6sXVm7snZl7drnuT3abdwcZ+3ac78ca9fu83qsXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtWvf/WqsXVm7snZl7drvfDDWrqxdWbuydmXtytqVtWvP9HCsXbvhk7F27eZPx9q1d+R8rF17py7G2vU/v/WSO2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1a/dwNtaurF1Zu7J2Ze3K2pW1K2tX1q59ntuj3cbNcdauPffLsXbtPq/H2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbv23a/G2pW1K2tX1q79zgdj7cralbUra1fWrqxdWbv2TA/H2rUbPhlr127+dKxde0fOx9q1d+pirF0Pf8rlnbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cratXs4G2tX1q6sXVm7snZl7cralbUra9c+z+3RbuPmOGvXnvvlWLt2n9dj7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF377ldj7cralbUra9d+54OxdmXtytqVtStrV9aurF17podj7doNn4y1azd/OtauvSPnY+3aO3Ux1q7veeDL7qxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrt3D2Vi7snZl7cralbUra1fWrqxdWbv2eW6Pdhs3x1m79twvx9q1+7wea1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3ad78aa1fWrqxdWbv2Ox+MtStrV9aurF1Zu7J2Ze3aMz0ca9du+GSsXbv507F27R05H2vX3qmLsXb93DtffmftytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydu0ezsbalbUra1fWrqxdWbuydmXtytq1z3N7tNu4Oc7ated+Odau3ef1WLuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2vXvvvVWLuydmXtytq13/lgrF1Zu7J2Ze3K2pW1K2vXnunhWLt2wydj7drNn461a+/I+Vi79k5djLXrT+5/xZ21K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2rV7OBtrV9aurF1Zu7J2Ze3K2pW1K2vXPs/t0W7j5jhr15775Vi7dp/XY+3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxd++5XY+3K2pW1K2vXfueDsXZl7cralbUra1fWrqxde6aHY+3aDZ+MtWs3fzrWrr0j52Pt2jt1Mdau9z7hlXfWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra9fu4WysXVm7snZl7cralbUra1fWrqxd+zy3R7uNm+OsXXvul2Pt2n1ej7Ura1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J27btfjbUra1fWrqxd+50PxtqVtStrV9aurF1Zu7J27ZkejrVrN3wy1q7d/OlYu/aOnI+1a+/UxVi7Pvm/s3Zl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7dg9nY+3K2pW1K2tX1q6sXVm7snZl7drnuT3abdwcZ+3ac78ca9fu83qsXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtWvf/WqsXVm7snZl7drvfDDWrqxdWbuydmXtytqVtWvP9HCsXbvhk7F27eZPx9q1d+R8rF17py7G/w92rFXTAgAAAACAAACAVAAAohUAAFQOAAA=eJxd3dUTQFXZRnFP0N3d3d3d3d3dqYAgJYLSoXR3l9LdCkooqXQrLSkd38V3fhfvc26emTXrH1h75uz9s5/9/9cMu+OwOwRvh90pPLwbdufw8H7YXcLDRxh21/DwEYfdLTx8pGF3Dw8fedg9wsNHGXbP8PBRh90rPHy0YfcODx992J+Hh48x7C/Cw8ccdp/w8LGG3Tc8fOxh9wsPH2fYX4aHjzvs/uHh4w17QHj4+MP+Kjx8gmEPDA+fcNiDwsMnGvbg8PCJhz0kPHySYQ8ND5902F+Hh0827GHh4ZMP+5vw8CmGPTw8fMphjwgPn2rY34aHTz3s78LDpxn2yPDwaYc9Kjx8umGPDg+ffthjwsNnGPbY8PAZhz0uPHymYY8PD5952BPCw2cZ9sTw8FmHPSk8fLZhfx8ePvuwfwgPn2PYk8PD5xz2lPDwuYY9NTx87mFPCw+fZ9jTw8PnHfaM8PD5hj0zPHz+Yc8KD19g2LPDwxcc9pzw8IWGPTc8fOFhzwsPX2TY88PDFx32gvDwxYa9MDx88WEvCg9fYtiLw8OXHPaS8PClhr00PHzpYS8LD19m2MvDw5cd9orw8OWGvTI8fPlhrwoPX2HYq8PDVxz2mvDwlYa9Njx85WGvCw9fZdjrw8NXHfaP4eGrDfun8PDVh70hPHyNYW8MD19z2JvCw9ca9ubw8LWHvSU8fJ1hbw0PX3fY28LD1xv29vDw9Ye9Izx8g2HvDA/fcNi7wsM3Gvbu8PCNh70nPHyTYe8ND9902PvCwzcb9v7w8M2HfSA8fIthHwwP33LYh8LDtxr2z+HhWw/7l/DwbYZ9ODx822EfCQ/fbti/hodvP+zfwtMZeuKxYR8NriceDw/XE0+Eh+uJv4eH64l/hIfriSfDw/XEU+HheuLp8HA98Ux4uJ54NjxcTzwXHq4n/hkerif+FR6uJ54PD9cTL4SH64kXw8P1xEvh4Xri5fBwPfFKeLieeDU8XE+8Fh6uJ14PD9cTb4SH64k3w8P1xFvh4Xri7fDww4b9d3i4nvhPeLieeCc8XE+8Gx6uJ94LD9cT74eH64kPwsP1xIfh4Xrio/BwPfHf8HA98XF4uJ74JDxcT3waHq4nPgsP1xOfh4friS/Cw/XE/8LD9cSX4eF64qvwcD3xdXi4nvgmPFxPfBserie+Cw/XE9+Hh+uJH8LD9cSP4eF64qfwcD3hQOyn4HqiaaqH64m2qR6uJ7qmerie6Jvq4RcOO0JTPVxPjNhUD9cTIzXVw/XEyE31cD0xSlM9XE+M2lQP1xOjNdXD9cToTfVwPTFGUz1cT4zZVA/XE2M11cP1xNhN9XA9MU5TPVxPjNtUD9cT4zXVw/XE+E31cD0xQVM9XE9M2FQP1xMTNdXD9cTETfVwPTFJUz1cT0zaVA/XE5M11cP1xORN9XA9MUVTPVxPTNlUD9cTUzXVw/XE1E31cD0xTVM9XE9M21QP1xPTNdXD9cT0TfXw+4edoakeridmbKqH64mZmurhemLmpnq4npilqR6uJ2Ztqofridma6uF6YvameriemKOpHq475myqpzP0xNwDn6upXE/M01QP1xPzNtXD9cR8TfVwPTF/Uz1cTyzQVA/XEws21cP1xEJN9XA9sXBTPVxPLNJUD9cTizbVw/XEYk31cD2xeFM9XE8s0VQP1xNLNtXD9cRSTfVwPbF0Uz1cTyzTVA/XE8s21cP1xHJN9XA9sXxTPfz1YVdoqoe/MeyKTfVwPbFSUz1cT6zcVA/XE6s01cP1xKpN9XA9sVpTPVxPrN5UD9cTazTVw/XEmk31cD2xVlM9XE+s3VQP1xPrNNXD9cS6TfVwPbFeUz1cT6zfVA/XExs01cP1xIZN9XA9sVFTPVxPbNxUD9cTmzTVw/XEpk31cD2xWVM9XE9s3lQP1xNbNNXD9cSWTfVwPbFVUz1cT2zdVA/XE9s01cP1xLZN9XA9sV1TPVxPbN9UD9cTOzTVw/XEjuHhemKn8HA9sXN4uJ7YJTxcT+waHq4ndgsP1xO7h4friT3Cw/XEnuHhemKv8HA9sXd4uJ74eXi4nvhFeLie2Cc8XE/sGx6uJ/YLD9cTvwwP1xP7h4friQPCw/XEr8LD9cSB4eF64qDwcD1xcHi4njgkPFxPHBoerid+HR6uJw4LD9cTvwkP1xOHh4friSPCw/XEb8PD9cTvwsP1xJHh4XriqPBwPXF0eLieOCY8XE8cGx6uJ44LD9cTx4eH64kTwsP1xInh4XripPBwPfH78HA98YfwcD1xcni47jglPJ2hJ04b9tTgeuL08HA9cUZ4uJ44MzxcT5wVHq4nzg4P1xPnhIfriXPDw/XEeeHheuL88HA9cUF4uJ64MDxcT1wUHq4nLg4P1xOXhIfriUvDw/XEZeHheuLy8HA9cUV4uJ64MjxcT1wVHq4nrg4P1xPXhIfriWvDw/XEdeHheuL68HA98cfwcD3xp/BwPXFDeLieuDE8XE/cFB6uJ24OD9cTt4SH64lbw8P1xG3h4Xri9vBwPXFHeLieuDM8XE/cFR6uJ+4OD9cT94SH64l7w8P1xH3h4Xri/vBwPfFAeLieeDA8XE88FB6uJ/4cHq4n/hIericeDg/XE4+Eh+uJv4aH64m/hYfriUfDw/XEY+HheuLx8HA98UR4uJ74e3i4nvhHeLieeDI8XE88FR6uJ54OD9cTz4SH64lnw8P1xHPh4Xrin+HheuJf4eF64vnwcD3xQni4nngxPFxPvBQerideDg/XE6+Eh+uJV8PD9cRr4eF64vXwcD3xRni4nngzPFxPvBUerifeDg/XE/8OD9cT/wkP1xPvhIfriXfDw/XEe+HheuL98HA98UF4uJ74MDxcT3wUHq4n/hseric+Dg/XE5+Eh+uJT8PD9cRn4eF64vPwcD3xRXi4nvhfeLie+DI8XE98FR6uO74OT2foiW+H/Sa4nvguPFxPfB8erid+CA/XEz+Gh+uJn8LD9YQfUn4Krieatnq4nmjb6uF6omurh+uJvq0eridGaKuH64kR2+rhemKktnq4nhi5rR6uJ0Zpq4friVHb6uF6YrS2erieGL2tHq4nxmirh+uJMdvq4XpirLZ6uJ4Yu60erifGaauH64lx2+rhemK8tnq4nhi/rR6uJyZoq4friQnb6uF6YqK2eriemLitHq4nJmmrh+uJSdvq4XpisrZ6uJ6YvK0eriemaKuH64kp2+rhemKqtnq4npi6rR6uJ6Zpq4friWnb6uF6Yrq2eriemL6tHq4nZmirh+uJGdvq4XpiprZ6uJ6Yua0eridmaauH64lZ2+rhemK2tnq4npi9rR6uJ+Zoq4friTnb6uF6Yq62eriemLutHq4n5mmrh+uJedvq4XpivrZ6uJ6Yv60ericWaKuH64kF2+rhemKhtnq4nli4rR6uJxZpq4friUXb6uF6YrG2erieWLytHq4nlmirh+uJJdvq4XpiqbZ6uJ5Yuq0erieWaauH64ll2+rhemK5tnq4nli+rR6uJ1Zoq4friRXb6uF6YqW2erieWLmtHq4nVmmrh+uJVdvq4XpitbZ6uJ5Yva0erifWaKuH64k12+rhemKttnq4nli7rR6uJ9Zpq4friXXb6uF6Yr22erieWL+tHq4nNmirh+uJDdvq4Xpio7Z6uJ7YuK0eric2aauH64lN2+rhemKztnq4nti8rR6uO7Zoq6cz9MRWA9+yrVxPbN1WD9cT27TVw/XEtm31cD2xXVs9XE9s31YP1xM7tNXD9cSO4eF6YqfwcD2xc3i4ntglPFxP7Boerid2Cw/XE7uHh+uJPcLD9cSe4eF6Yq/wcD2xd3i4nvh5eLie+EV4uJ7YJzxcT+wbHq4n9gsP1xO/DA/XE/uHh+uJA8LD9cSvwsP1xIHh4XrioPBwPXFweLieOCQ8XE8cGh6uJ34dHq4nDgsP1xO/CQ/XE4eHh+uJI8LD9cRvw8P1xO/Cw/XEkeHheuKo8HA9cXR4uJ44JjxcTxwbHq4njgsP1xPHh4friRPCw/XEieHheuKk8HA98fvwcD3xh/BwPXFyeLieOCU8XE+cGh6uJ04LD9cTp4eH64kzwsP1xJnh4XrirPBwPXF2eLieOCc8XE+cGx6uJ84LD9cT54eH64kLwsP1xIXh4XriovBwPXFxeLieuCQ8XE9cGh6uJy4LD9cTl4eH64krwsP1xJXh4XriqvBwPXF1eLieuCY8XE9cGx6uJ64LD9cT14eH64k/hofriT+Fh+uJG8LD9cSN4eF64qbwcD1xc3i4nrglPFxP3BoeriduCw/XE7eHh+uJO8LD9cSd4eF64q7wcD1xd3i4nrgnPFxP3BserifuCw/XE/eHh+uJB8LDdceD4ekMPfHnYR8Krif+Eh6uJx4OD9cTj4SH64m/hofrib+Fh+uJR8PD9cRj4eF64vHwcD3xRHi4nvh7eLie+Ed4uJ54MjxcTzwVHq4nng4P1xPPhIfriWfDw/XEc+HheuKf4eF64l/h4Xri+fBwPfFCeLieeDE8XE+8FB6uJ14OD9cTr4SH64lXw8P1xGvh4Xri9fBwPfFGeLieeDM8XE+8FR6uJ94OD9cT/w4P1xP/CQ/XE++Eh+uJd8PD9cR74eF64v3wcD3xQXi4nvgwPFxPfBQerif+Gx6uJz4OD9cTn4SH64lPw8P1xGfh4Xri8/BwPfFFeLie+F94uJ74MjxcT3wVHq4nvg4P1xPfhIfriW/Dw/XEd+HheuL78HA98UN4uJ74MTxcT/wUHq4nXBj5U3A90XTVw/VE21UP1xNdVz1cT/Rd9XA9MUJXPVxPjNhVD9cTI3XVw/XEyF31cD0xSlc9XE+M2lUP1xOjddXD9cToXfVwPTFGVz1cT4zZVQ/XE2N11cP1xNhd9XA9MU5XPVxPjNtVD9cT43XVw/XE+F31cD0xQVc9XE9M2FUP1xMTddXD9cTEXfVwPTFJVz1cT0zaVQ/XE5N11cP1xORd9XA9MUVXPVxPTNlVD9cTU3XVw/XE1F31cD0xTVc9XE9M21UP1xPTddXD9cT0XfVwPTFDVz1cT8zYVQ/XHTN11dMZemKWgc/cVa4nZu2qh+uJ2brq4Xpi9q56uJ6Yo6serifm7KqH64m5uurhemLurnq4npinqx6uJ+btqofrifm66uF6Yv6uerieWKCrHq4nFuyqh+uJhbrq4Xpi4a56uJ5YpKsericW7aqH64nFuurhemLxrnq4nliiqx6uJ5bsqofriaW66uF6YumuerieWKarHq4nlu2qh+uJ5brq4Xpi+a56uJ5YoaseridW7KqH64mVuurhemLlrnq4nlilqx6uJ1btqofridW66uF6YvWuerieWKOrHq4n1uyqh+uJtbrq4Xpi7a56uJ5Yp6serifW7aqH64n1uurhemL9rnq4ntigqx6uJzbsqofriY266uF6YuOuerie2KSrHq4nNu2qh+uJzbrq4Xpi8656uJ7Yoqserie27KqH64mtuurhemLrrnq4ntimqx6uJ7btqofrie266uF6Yvuuerie2KGrHq4ndgwP1xM7hYfriZ3Dw/XELuHhemLX8HA9sVt4uJ7YPTxcT+wRHq4n9gwP1xN7hYfrib3Dw/XEz8PD9cQvwsP1xD7h4Xpi3/BwPbFfeLie+GV4uJ7YPzxcTxwQHq4nfhUericODA/XEweFh+uJg8PD9cQh4eF64tDwcD3x6/BwPXFYeLie+E14uJ44PDxcTxwRHq4nfhserid+Fx6uJ44MD9cTR4WH64mjw8P1xDHh4Xri2PBwPXFceLjuOD48naEnThz2hOB64qTwcD3x+/BwPfGH8HA9cXJ4uJ44JTxcT5waHq4nTgsP1xOnh4friTPCw/XEmeHheuKs8HA9cXZ4uJ44JzxcT5wbHq4nzgsP1xPnh4friQvCw/XEheHheuKi8HA9cXF4uJ64JDxcT1waHq4nLgsP1xOXh4friSvCw/XEleHheuKq8HA9cXV4uJ64JjxcT1wbHq4nrgsP1xPXh4friT+Gh+uJP4WH64kbwsP1xI3h4XripvBwPXFzeLieuCU8XE/cGh6uJ24LD9cTt4eH64k7wsP1xJ3h4XrirvBwPXF3eLieuCc8XE/cGx6uJ+4LD9cT94eH64kHwsP1xIPh4XriofBwPfHn8HA98ZfwcD3xcHi4nngkPFxP/DU8XE/8LTxcTzwaHq4nHgsP1xOPh4friSfCw/XE38PD9cQ/wsP1xJPh4XriqfBwPfF0eLieeCY8XE88Gx6uJ54LD9cT/wwP1xP/Cg/XE8+Hh+uJF8LD9cSL4eF64qXwcD3xcni4nnglPFxPvBoerideCw/XE6+Hh+uJN8LD9cSb4eF64q3wcD3xdni4nvh3eLie+E94uJ54JzxcT7wbHq4n3gsP1xPvh4friQ/Cw/XEh+HheuKj8HA98d/wcD3xcXi4nvgkPFx3fBqeztATnw/7WXA98UV4uJ74X3i4nvgyPFxPfBUerie+Dg/XE9+Eh+uJb8PD9cR34eF64vvwcD3xQ3i4nvgxPFxP/BQeric82PhTcD3R9NXD9UTbVw/XE11fPVxP9H31cD0xQl89XE+M2FcP1xMj9dXD9cTIffVwPTFKXz1cT4zaVw/XE6P11cP1xOh99XA9MUZfPVxPjNlXD9cTY/XVw/XE2H31cD0xTl89XE+M21cP1xPj9dXD9cT4ffVwPTFBXz1cT0zYVw/XExP11cP1xMR99XA9MUlfPVxPTNpXD9cTk/XVw/XE5H31cD0xRV89XE9M2VcP1xNT9dXD9cTUffVwPTFNXz1cT0zbVw/XE9P11cP1xPR99XA9MUNfPVxPzNhXD9cTM/XVw/XEzH31cD0xS189XE/M2lcP1xOz9dXD9cTsffVwPTFHXz1cT8zZVw/XE3P11cP1xNx99XA9MU9fPVxPzNtXD9cT8/XVw/XE/H31cD2xQF89XE8s2FcP1xML9dXD9cTCffVwPbFIXz1cTyzaVw/XE4v11cP1xOJ99XA9sURfPVxPLNlXD9cTS/XVw/XE0n31cD2xTF89XE8s21cP1xPL9dXD9cTyffVwPbFCXz1cT6zYVw/XEyv11cP1xMp99XA9sUpfPVxPrNpXD9cTq/XVw/XE6n31cD2xRl89XE+s2VcP1xNr9dXD9cTaffVwPbFOXz1cT6zbVw/XE+v11cP1xPp99XA9sUFfPVx3bNhXT2foiY0HvlFfuZ7YpK8eric27auH64nN+urhemLzvnq4ntiirx6uJ7bsq4fria366uF6Yuu+erie2KavHq4ntu2rh+uJ7frq4Xpi+756uJ7Yoa8erid2DA/XEzuFh+uJncPD9cQu4eF6YtfwcD2xW3i4ntg9PFxP7BEerif2DA/XE3uF938YiQYReJxd1/cXB2L9hnHF83xk7xmJkL1pIZItlBnK3pSkEpGKSpEGoWSrrFAySrKVvZVZZiEqq4jvOd/zvH543/cv9znXuf6Ba5qppvj/TTv+0+M/FXy68fuFh08//jPh4TOM3z88fMbxnw0Pn2n8AeHhM4//XHj4LOM/Hx4+6/gvhIfPNv7A8PDZx38xPHyO8QeFh885/uDw8LnGfyk8fO7xh4SHzzP+0PDwecd/OTz87eMPCw+fb/xXwsPnH//V8PB3jP9aePgC4w8PD3/n+CPCwxcc//Xw8IXGfyM8/F3jvxkevvD4I8PDFxn/rfDwRcd/Ozz83eOPCg9fbPzR4eGLj/9OePgS448JD19y/HfDw5ca/73w8KXHfz88fJnxPwgPX3b8seHhy40/Ljx8+fE/DA9fYfzx4eErjj8hPHyl8SeGh688/kfh4auM/3F4+HvGnxQe/t7xPwkPf9/4k8PD3z/+lPDwD4w/NTx81fGnhYevNv708PDVx58RHv7B8WeGh68x/qzw8DXH/zQ8/EPjfxYevtb4n4eHf3j82eHha48/Jzx8nfHnhoevO/688PD1xp8fHr7++F+Eh28w/oLw8A3HXxgevtH4i8LDPzL+l+HhG4//VXj4JuMvDg/fdPyvw8M/Ov6S8PCPjb80PHyz8ZeFh28+/vLw8C3G/ya8LcdvNf6K8b8NvvX434WHf3z8leHh24z/fXj4tuOvCg/fbvzV4eGfGH9NePgnx18bHr79+OvCw3cYf314+I7jbwgP32n8jeHhO4//Q3j4LuP/GB6+6/ibwsN3G39zePju428JD99j/K3h4XuOvy08fK/xt4eH7z3+jvDwfcbfGR6+7/i7wsP1xN3h4XrinvBwPXFveLieuC88XE/cHx6uJ/4UHq4n/hwericeCA/XEw+Gh+uJh8LD9cTD4eF64pHwcD3xaHi4nvhLeLie+Gt4uJ54LDxcTzweHq4nnggP1xNPhofriafCw/XE0+HheuJv4eF64u/h4XrimfBwPfFseLieeC48XE/8IzxcTzwfHq4nXggP1xP/DA/XE/8KD9cT/w4P1xMvhofriZfCw/XEy+HheuKV8HA98Wp4uJ74T3i4nvhveLieeC08XE+8Hh6uJ/4XHq4n3ggP1xNvhofriSla9XA98ZZWPVxPvLVVD9cTU7bq4XpiqlY9XE+0Vj1cT/RWPVxPTFr1cD0xdaserife1qqH64lpWvVwPTFtqx6uJ6Zr1cP1xPSteriemKFVD9cTM7bq4XpiplY9XE/M3KqH64lZWvVwPTFrqx6uJ2Zr1cP1xOyteriemKNVD9cTc7bq4XpirlY9XE/M3aqH64l5WvVwPTFvqx6uJ97eqofrifla9XA9MX+rHq4n3tGqh+uOBVr1dIaeWHDwd7bK9cRCrXq4nnhXqx6uJxZu1cP1xCKterieWLRVD9cT727Vw/XEYq16uJ5YvFUP1xNLtOrhemLJVj1cTyzVqofriaVb9XA9sUyrHq4nlm3Vw/XEcq16uJ5YvlUP1xMrtOrhemLFVj1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AQAAAACAAABoDwAAyAwAAA==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AQAAAACAAABoDwAAXw4AAA==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AQAAAACAAABoDwAA4wUAAA==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AQAAAACAAABoDwAAjAgAAA==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AQAAAACAAABoDwAAfw0AAA==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AQAAAACAAABoDwAAEw0AAA==eJxNl3lczdvfxQ0JuYlCyZRCISJkthJJpoiUoUSGlKFBg6HMSSkXN0WmlEylOaFrTJ35O55zypwkKUVkiJvf/p7nvF6e/qzTPnvvz1rvtfZoh/D8wBIWQ15uCvbZweL2/vJTDjUMMrc0n/lyl4G+aYtlkQcDtxfxAcs/0sjPvtyv9TSN2TGi7JjxNMbHe8S6tKXx1X74qLUhFM4sjN4z44oCETcK1+yukEPyymp7SLwck2ojqvwpGbx8Eq+8MJVhb+5Q9/BEKdzrbe5YGkixqfOPCxvyJChxyNz4IlCC4RU53aPVYugMXHZfZ4sYI1bUxR4oFGFnjxtOlTtEcEg4PZXWE+HsniEPoy6XgfKvN1SuKNPusxTG59t5T9lfCt3mEcG3rUvhp9kghwndjneY94pFp7fvPu1MZqFTc8Tqgz6Le13PjLmYz8DRJtVjy0YG2/4SeTW20njcmruzKZvGqlk5z1g/Grk+Ft2y6iio7y/t3OsQhZ7uCRHuOhT6x7SLMHdRoH+JosekLDmGdnjuxZrI0TFnzEGFvwwFPX9KG8RS9JyUlTN3iRRTnW+vb5JLMCdp40/3pRJYHHDq45QhRrvTnfqc8xIjrzHm1e7hYqytnWHM3xShsc+qneudRfB8Nqt9eBcRTKgLKbv3lSFozLM9lEEZ4vvfu1lLlSLZ7fz1zHIOU6LPDt3mxcHUuOuBtW05nLpz8m8DMt/aIaM7ZfRlMZRMpW0Fgx29HwfNvc7ArlqvMag7g4fznt7LZWms1R1W9XIDjaxV2X0KR9AQpvBcTqFQZdx580QK5eeWGV5IV8CgS0H69jI5xKF3z5vayNES6Ve87YQM07sKJ5Mist+EDTM3StFl55PKLLEE//zsR25Kgo3jBjXkfBFjsVTVYp4ixsHCM3MD3cTYNO2Gfs8qEQqfjhyr3ijS6kUE/+FfE5+fKMMVor6MRWW4Faf7sddsHrMv39h1soZDacnbqicLOfQatXdF2Oc/8+24K9Jk4BQWmuPWMchf1nzrSQwDcslDpd0YzPE662P/lUZRLRWZFk1r9UKjQvFtcdUlCgmzLyYusqa0c1LAwbuaNn8qx36beel6s+QIX6OKTTkjQ7yF6vXiNjK8uvUtQBwoxQ+D2ptZ7aWgaTx4HCNBUEz8m6YBEvzYv7fmxSMx3uuM7W43RYzuAZ3c/L6K0PSXYDQRtupvSvAOFEH/erjFZ1EZ1nTzmJgv4hE9K6zb5MU8mGMrW2e0cHh9vGpBrTeHgdWWymn9OBz46FsVXcDCNDVkybjpLCwvHM6urGVQVZZEJs9grMbYDPxvevre4Gi46DqJrwfTeIu0l3e70njiNvuHcwGFyEn9xyzsTeHcToPEvmF/zmtu+nx6/Twy5xNp/kNeytDu0+3IB1tk+DH67Y3Bb6TQXDvR9b11CxIfl0jwol3nmAE+EhgXvxs+e4wEPaQjMqNKxBBuy9ddDIu7Rnlef4lBxC2rzRWBj2jjmjxBiTBBRs95HEuu1N0VySP0UaHjKX0eg4TrPcLB3mj1I244h7pgwVEszs5aPmyrE4tst32PK2UMzvxQ9jVLYvDmX791D20Y3CG7LC+kETZi4IAvm2gs/GUSrDaktetR8M17T1aikJjZ7OiwQgG9kUt5b1MFNum8Dvlvnxwej/uccmqVYc3TizLdUzIMtp9PUCTF7rTov66HS7FkksfvmlFSGD5MjbNQSfDhjvn3l3Mk6Oka6fqBE+PLq4aM56FE5++KS0cuEqMLe8SRq1BiVWNreNZyJdY77zm9vJCH2/xuIQP28FCGCw7lkRH71LfNVg6u1jfzTQ056PxeIY6PYxFxjD4ZPJTV6ohBS1O7+tTFDHJvK4PZnzSISMg30dr7o9GuuINhD9A4IcjlPwoO1HpljR+FQHHg5W3ZCox/pP/91ygFroyTT17AyJFpY/gkaKQc+SceLGp6L0OHqAySBDK0fvIqsK2UgsDEqChECut1vV97GEtx0EGnr0OCBN1/bR082U6CA827u36uFuPb5B4dWmaqID0zMvawXImQUNsJc7yUaP6cbt6zlIe9n5Hlt8k8AhTR7ItXHKafzvGdNJnD5Q42LXosi6bshf6nw1hML75BCMRitcZYDPbqPD46OozBi9CUWwssGJysL+9UUkejSdheIvHtP8OLpY40At0qwhw/UnCnnAk6KTwIbqw8XqVAloPE5VqEAqM0G1HglKHzF9sYOTpsLL1YWy+DVXLQwbBbMtTyCVTTFBn+rerRT1wthSYGF0lhQuiX+FqiXUcCzfWWqqDBrJEKJhHCSkrsrW9uOPqNh+MdvaG4yiM2sHVID3Me5U4CsDgYWXfdEDmOQ3NKl/cr3rJ4IhaCkoVFz9Je+wifV5pN/+RD9Lwvtue4pCgGAgXLhzFIuSsYjIbkcCiRGI2B76e1uTqfxve4rKl5g2ig39HeV4iuCRyJ1Cm8qDYnTlPAcn/qG+VEBQj0ym4XyfG1i+AsOTT27CWHPz+DIEKGnHv156ZY/+H33bTRy53cpKCebDY+XadC3Ws70/srVDBjt67qqFBi8cmB8SGBSsRUn1w64zWPKesv2LZG8DAnv+1DfNva1XHvtGMcBFU9duMwQB0VE9jKYsZvHePhfiyufWLnr+nG4syzxoU93jEIqNty7j3hVdGbosWTSO+w0xibxo6HhgZWyTQEFZ31oeH9vma+4zAanwM3XzGp+TPnvoOzFKPNKIQefp+5N1OBilWhLv17KXC/5lD3h6lyBBTeGj11tRy/B/73NeSVDHnyuNrOc2VoktuNT7eUoT1xk/s0NUI0QaxC9ts2D/pOVSFmmU1UEJlrSV1LhzurldBTpwZM1VMi4J/iSWXEt//XR3i82rCSVAwOz84WkAT7M1/TsV9cAnJYbY4QPi9oCLPSY2E18/7AJVcZjKlMbNlOfHxAsPVgBtfrBZCQnrX59ZvIQzSe7xRuhEbKdwG4NP5e4PnDmqIQ53lxh783hYZOgnMU2nxVYKcmoBSIJS2iIkeOjyUZxjMmyrFdUwBksIy+bWDvp4avxuAqPF04WvHygAqVwse7qzD3+sDAo5eUWm4psZVMJbmSh0l4w9SVQTz6mSWlljWSfiHEQgqH4+/WEcRz8CTp9KGOha7+f0YrM1jc73yw04QDLNI/rFq20ZVFRt/laye/ZKAr2PwIg2l5gwhRGZwe3NbPr4LW5geNtpqCQ4ObLyQgjQbh3/VopNqfF51Io5BEbuuYHgWNHa8pcH7ArE5H7RRaTsi1epMj3dL6055ctZYbamRnjCXVTKXVO9FxweETP/upsP++JMWxUAlXA+Zd1zVKre54kBAhpOCRuUj4A48gQs1WioN1xLt9Lf/Px1bO6nl3K1jIa3OTynex2LJo/f55tiyKj21/Y6DLQrXlDr3yMgNhl/FE1y9d4hK3GDIwWLNB76yaxr6/rb3b3aSRwHf2Nd/0R9/9NaCnMN4lRCQPoDAjWEg8Cvrpq79HJylwfYgwSAUC20/DkW7l0NTIx2p4i94vpZzV6ELo87VWBRJ+SyNuqLT+VuH0KeFHqe33JIeetCYkDFFi96iPz3YW8UiKqrRYM4dHyhx5f98OPNJ6x6bnneDQJNjVg4OZl9qmXJ9Dcmu9U4yI1fKQhbNPfvy1ISw+DEv7lfaE0eqDgab+WzMwEnBbTYOEBakQNI6b22a8jqMRQGjSexGN9KJrRPk0NDaUUuizN9zzHtH33OoPROEUxmmKdTnGaIBTjryCu7N9pWpM8uxllHxUjXyRUETV0MQkOe+WqD4ff6xWwbZ9wqfGMSrYXZ/mviJHiZlXXPM6kvxNE77mM49Dm2Nt+6zltf2YB4Gv51wRhzmDGKkVmbNw++2ncdhBVOfThQMJtbKCFOJj4ePLyfvplyu2DmOxy3L9vyYS0qMFXAWR/iXg0ozR7p9B25/vSLKQ8xnXR22OpWFB2kIomfeSqkvJJWY0lELsFFHYRFl3Xri4Al+tVh592FwO/UChEZRjToFLmY9uufb9pMa3N6tTVGPVsB/ldPTlUxV6mQhNgHD6d9+30i4qwHVmlFuxEprnTLhS2xN4SMY/fZZ0jte+K3jwn5L2Sr5zsA3q9TX/Eadd989522xLsrG5z+IjobTRdhaS9JWVniNZtBTZLTnymcE17yWulhcYpJGU0V3LoF/G7+Ak0r9sjD+dTWqmUSvgIZPG/rE+zLZQGjU/rxLyk7mf4taNzqnAh7UCSSsgrhYKaTmWCs+YVeU4IsRfpRoCNVzi1JineSCokXvQrONgmUrbc1QYrAE2OS9JwzPPlKjqLQBXiZtWedOH9FZiwohwxv1vHuzPUvW5Zbz23crDbllq/4sMB9+TOleuruMQTNI/upHFoYWX1hvks5gcl7/kRTyLPecDK+1nE10LdaOF5PFEQXAMui82P+w1i8G56UKikffUJesZfUkfIWZueHuVxseLWWZyDxr/A+qmx4A=AQAAAACAAABoDwAALgYAAA==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AQAAAACAAABoDwAAGwAAAA==eJztwTEBAAAAwqD1T20JT6AAAACAlwEPaAABAQAAAACAAABoDwAAGwAAAA==eJztwTEBAAAAwqD1T20JT6AAAACAlwEPaAABAQAAAACAAABQGQAA0wQAAA==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AQAAAACAAACgPQAAlgkAAA==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AQAAAACAAADtAQAADgAAAA==eJzj5BwFIwYAALvgEVY=
34
+ </AppendedData>
35
+ </VTKFile>
CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/grid/final-grid.dat ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/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 0.34
17
+ variable Ma equal 2.5
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 0.34*${L}
23
+ variable mfp equal 0.34*1
24
+ variable cpmfp equal 4
25
+ variable nden equal 1.0/sqrt(2.0)/${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}*${Kn})
29
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.34/${cpmfp}*${Kn})
30
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.34/4*${Kn})
31
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.34/4*0.34)
32
+ variable sos equal sqrt(${gamma}*${R}*${To})
33
+ variable sos equal sqrt(1.666666667*${R}*${To})
34
+ variable sos equal sqrt(1.666666667*208.242684766214*${To})
35
+ variable sos equal sqrt(1.666666667*208.242684766214*273)
36
+ variable vo equal ${Ma}*${sos}
37
+ variable vo equal 2.5*${sos}
38
+ variable vo equal 2.5*307.815564238681
39
+ variable vx equal ${vo}*cos(${theta}*2*PI/360)
40
+ variable vx equal 769.538910596703*cos(${theta}*2*PI/360)
41
+ variable vx equal 769.538910596703*cos(0*2*PI/360)
42
+ variable vy equal ${vo}*sin(${theta}*2*PI/360)
43
+ variable vy equal 769.538910596703*sin(${theta}*2*PI/360)
44
+ variable vy equal 769.538910596703*sin(0*2*PI/360)
45
+ variable ppc equal 30
46
+ variable xncells equal (${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)/0.34*${cpmfp}
50
+ variable xncells equal (6--5)/0.34*4
51
+ variable yncells equal (${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)/0.34*${cpmfp}
55
+ variable yncells equal (5--5)/0.34*4
56
+ variable Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
57
+ variable Fnum equal 4.47883616959053e+19*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
58
+ variable Fnum equal 4.47883616959053e+19*(6-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
59
+ variable Fnum equal 4.47883616959053e+19*(6--5)*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
60
+ variable Fnum equal 4.47883616959053e+19*(6--5)*(5-${ymin})/${ppc}/${xncells}/${yncells}
61
+ variable Fnum equal 4.47883616959053e+19*(6--5)*(5--5)/${ppc}/${xncells}/${yncells}
62
+ variable Fnum equal 4.47883616959053e+19*(6--5)*(5--5)/30/${xncells}/${yncells}
63
+ variable Fnum equal 4.47883616959053e+19*(6--5)*(5--5)/30/129.411764705882/${yncells}
64
+ variable Fnum equal 4.47883616959053e+19*(6--5)*(5--5)/30/129.411764705882/117.647058823529
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}/${xncells}/10/4
68
+ variable tstep equal (--5+6)/769.538910596703/${xncells}/10/4
69
+ variable tstep equal (--5+6)/769.538910596703/129.411764705882/10/4
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 4.47883616959053e+19
81
+ global fnum ${Fnum}
82
+ global fnum 1.07865304417639e+16
83
+ timestep ${tstep}
84
+ timestep 2.76139383043318e-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 129.411764705882 ${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 129.411764705882 117.647058823529 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 66372 child grid cells
100
+ CPU time = 0.0982956 secs
101
+ create/ghost percent = 1.21519 98.7848
102
+ balance_grid rcb cell
103
+ Balance grid migrated 66244 cells
104
+ CPU time = 0.0861375 secs
105
+ reassign/sort/migrate/ghost percent = 61.3997 0.0377989 9.09888 29.4637
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 769.538910596703 ${vy} 0.0 temp ${To}
110
+ mixture air Ar vstream 769.538910596703 0 0.0 temp ${To}
111
+ mixture air Ar vstream 769.538910596703 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
+ 374 0 = cells overlapping surfs, overlap cells with unmarked corner pts
121
+ 59296 6702 374 = cells outside/inside/overlapping surfs
122
+ 374 = surf cells with 1,2,etc splits
123
+ 109.215 109.215 = cell-wise and global flow volume
124
+ CPU time = 0.0952552 secs
125
+ read/check/sort/surf2grid/ghost/inout/particle percent = 22.83 24.4803 2.72069 24.0807 25.8883 6.40251 0.173763
126
+ surf2grid time = 0.0229381 secs
127
+ map/comm1/comm2/comm3/comm4/split percent = 14.0388 24.5667 4.52225 1.69838 11.7944 7.07535
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 1906 cells
133
+ CPU time = 0.0354609 secs
134
+ reassign/sort/migrate/ghost percent = 7.74398 0.0805675 26.5331 65.6424
135
+ create_particles air n 0
136
+ WARNING: Created unexpected # of particles: 453485 versus 453486 (../create_particles.cpp:346)
137
+ Created 453485 particles
138
+ CPU time = 0.0133089 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) = 1.6084 0 1.6875
144
+ grid (ave,min,max) = 3.23499 1.51379 5.26379
145
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
146
+ total (ave,min,max) = 4.86398 3.22189 6.97189
147
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
148
+ 0 0 453485 0 0 0 0 0
149
+ 10000 11.906634 491406 13676 11320 11 471602.5 10.0582
150
+ 20000 26.87002 495723 13995 11671 7 483128.11 10.0969
151
+ 30000 40.655757 496309 13925 11637 10 487573.43 10.122167
152
+ 40000 54.313574 496542 13918 11692 15 489726.69 10.136
153
+ 50000 67.798466 495836 13781 11563 10 491183.44 10.14278
154
+ 60000 82.02411 497277 13962 11649 8 492086.25 10.138383
155
+ 70000 96.752924 496624 13811 11515 4 492779.68 10.141614
156
+ 80000 110.55595 496882 13856 11614 8 493241.43 10.138575
157
+ 90000 123.87613 496883 13831 11592 11 493613.65 10.140322
158
+ 100000 137.74012 496373 13831 11539 8 493952.2 10.14902
159
+ 110000 152.11407 496824 13894 11623 10 494149.91 10.149655
160
+ 120000 165.57008 497583 13829 11539 11 494347.37 10.150583
161
+ 130000 179.25124 496185 13650 11399 7 494492.89 10.147623
162
+ 140000 192.75399 495989 13844 11540 7 494590.86 10.1527
163
+ 150000 206.91762 496537 14034 11768 12 494740.22 10.152027
164
+ 160000 221.6581 496730 13913 11627 14 494871.43 10.153956
165
+ 170000 235.15536 495688 13611 11325 11 494956.8 10.150882
166
+ 180000 248.73162 496719 13781 11466 12 495028.54 10.153061
167
+ 190000 262.89562 496784 13868 11641 13 495125.26 10.154779
168
+ 200000 277.40128 496069 13743 11498 9 495200.84 10.156145
169
+ Loop time of 277.402 on 128 procs for 200000 steps with 496069 particles
170
+
171
+ MPI task timing breakdown:
172
+ Section | min time | avg time | max time |%varavg| %total
173
+ ---------------------------------------------------------------
174
+ Move | 0.023175 | 12.244 | 68.602 | 434.9 | 4.41
175
+ Coll | 0.33926 | 14.442 | 101.75 | 488.9 | 5.21
176
+ Sort | 0.11939 | 2.097 | 12.321 | 182.7 | 0.76
177
+ Comm | 53.883 | 85.466 | 96.18 | 94.7 | 30.81
178
+ Modify | 0.019349 | 0.12795 | 2.318 | 95.9 | 0.05
179
+ Output | 0.0037214 | 0.011704 | 0.013321 | 1.4 | 0.00
180
+ Other | | 163 | | | 58.76
181
+
182
+ Particle moves = 99040167837 (99B)
183
+ Cells touched = 103904497095 (104B)
184
+ Particle comms = 218398579 (218M)
185
+ Boundary collides = 0 (0K)
186
+ Boundary exits = 22400525 (22.4M)
187
+ SurfColl checks = 78511820 (78.5M)
188
+ SurfColl occurs = 2031229 (2.03M)
189
+ Surf reactions = 0 (0K)
190
+ Collide attempts = 3026052562 (3.03B)
191
+ Collide occurs = 2331891575 (2.33B)
192
+ Reactions = 0 (0K)
193
+ Particles stuck = 0
194
+ Axisymm bad moves = 0
195
+
196
+ Particle-moves/CPUsec/proc: 2.78928e+06
197
+ Particle-moves/step: 495201
198
+ Cell-touches/particle/step: 1.04911
199
+ Particle comm iterations/step: 1
200
+ Particle fraction communicated: 0.00220515
201
+ Particle fraction colliding with boundary: 0
202
+ Particle fraction exiting boundary: 0.000226176
203
+ Surface-checks/particle/step: 0.000792727
204
+ Surface-collisions/particle/step: 2.05091e-05
205
+ Surf-reactions/particle/step: 0
206
+ Collision-attempts/particle/step: 0.0305538
207
+ Collisions/particle/step: 0.0235449
208
+ Reactions/particle/step: 0
209
+
210
+ Particles: 3875.54 ave 23109 max 0 min
211
+ Histogram: 82 14 8 2 6 6 6 0 2 2
212
+ Cells: 518.531 ave 519 max 518 min
213
+ Histogram: 60 0 0 0 0 0 0 0 0 68
214
+ GhostCell: 13340.3 ave 24514 max 724 min
215
+ Histogram: 22 8 12 10 17 3 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) = 1.67432 0 3.375
246
+ grid (ave,min,max) = 3.23499 1.51379 5.26379
247
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
248
+ total (ave,min,max) = 5.10423 3.39595 7.14645
249
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
250
+ 200000 0 496069 13743 11498 0 0 0
251
+ 210000 23.066268 497112 13947 11688 11 496174.87 10.1592
252
+ 220000 46.542476 496547 13876 11579 9 496614.62 10.169
253
+ 230000 70.112627 496772 13940 11611 10 496577.6 10.161267
254
+ 240000 93.372381 496836 14106 11919 12 496648.82 10.169925
255
+ 250000 117.72865 496129 13850 11555 13 496661.4 10.1642
256
+ 260000 140.46797 496544 13877 11601 7 496562.31 10.167167
257
+ 270000 164.28113 496546 13879 11623 6 496567.42 10.171243
258
+ 280000 188.03417 496120 13874 11596 9 496567.43 10.168038
259
+ 290000 211.27594 496665 13905 11700 7 496541.8 10.161444
260
+ 300000 234.699 497137 13948 11632 14 496608.32 10.16508
261
+ Loop time of 234.699 on 128 procs for 100000 steps with 497137 particles
262
+
263
+ MPI task timing breakdown:
264
+ Section | min time | avg time | max time |%varavg| %total
265
+ ---------------------------------------------------------------
266
+ Move | 0.012657 | 6.17 | 34.568 | 307.4 | 2.63
267
+ Coll | 0.16882 | 7.2731 | 51.298 | 347.2 | 3.10
268
+ Sort | 0.068353 | 1.0662 | 6.176 | 129.0 | 0.45
269
+ Comm | 31.974 | 47.833 | 53.49 | 64.8 | 20.38
270
+ Modify | 2.3785 | 16.998 | 89.851 | 474.1 | 7.24
271
+ Output | 0.035071 | 0.036965 | 0.040998 | 0.6 | 0.02
272
+ Other | | 155.3 | | | 66.18
273
+
274
+ Particle moves = 49660832019 (49.7B)
275
+ Cells touched = 52097861508 (52.1B)
276
+ Particle comms = 109414466 (109M)
277
+ Boundary collides = 0 (0K)
278
+ Boundary exits = 11221878 (11.2M)
279
+ SurfColl checks = 39306897 (39.3M)
280
+ SurfColl occurs = 1016508 (1.02M)
281
+ Surf reactions = 0 (0K)
282
+ Collide attempts = 1523081443 (1.52B)
283
+ Collide occurs = 1173670771 (1.17B)
284
+ Reactions = 0 (0K)
285
+ Particles stuck = 0
286
+ Axisymm bad moves = 0
287
+
288
+ Particle-moves/CPUsec/proc: 1.65307e+06
289
+ Particle-moves/step: 496608
290
+ Cell-touches/particle/step: 1.04907
291
+ Particle comm iterations/step: 1
292
+ Particle fraction communicated: 0.00220323
293
+ Particle fraction colliding with boundary: 0
294
+ Particle fraction exiting boundary: 0.00022597
295
+ Surface-checks/particle/step: 0.000791507
296
+ Surface-collisions/particle/step: 2.0469e-05
297
+ Surf-reactions/particle/step: 0
298
+ Collision-attempts/particle/step: 0.0306697
299
+ Collisions/particle/step: 0.0236337
300
+ Reactions/particle/step: 0
301
+
302
+ Particles: 3883.88 ave 23450 max 0 min
303
+ Histogram: 82 14 8 2 6 6 6 0 2 2
304
+ Cells: 518.531 ave 519 max 518 min
305
+ Histogram: 60 0 0 0 0 0 0 0 0 68
306
+ GhostCell: 13340.3 ave 24514 max 724 min
307
+ Histogram: 22 8 12 10 17 3 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 = 66372
316
+ CPU time = 0.0091433 secs
317
+ write_surf surf/geom.surf
318
+ surf elements = 200
319
+ CPU time = 0.00147022 secs
CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/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/Kn0p34/simulation0706_Kn0p34Ma2p5/output/lambdakn.300000.dat ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/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 0.00396 0.040887 -0.040882 0.00064223 1.3778e-05 0.00087704 -0.00064194 2.3864e-05 1.098 0 0
11
+ 129 -0.31871 0.38526 -0.30645 0.39508 0.08424 0.91317 0.57096 -0.71267 0.12888 0.10325 0.010993 -0.0095723 86.799 0 0
12
+ 2 0.49975 -0.015705 0.49901 -0.031395 0.00413 0.043371 -0.043323 0.002043 6.648e-05 0.0014097 -0.00067944 5.4233e-05 1.7415 0 0
13
+ 130 -0.30645 0.39508 -0.29389 0.40451 0.08155 0.88444 0.53104 -0.70727 0.14425 0.10831 0.010607 -0.0094081 81.87 0 0
14
+ 3 0.49901 -0.031395 0.49778 -0.047054 0.00421 0.042077 -0.041947 0.0033013 -3.6676e-05 -0.00046601 -0.00065945 4.4535e-05 1.9932 0 0
15
+ 131 -0.29389 0.40451 -0.28104 0.41354 0.07645 0.83092 0.47778 -0.67981 0.13722 0.096439 0.00966 -0.0091633 83.721 0 0
16
+ 4 0.49778 -0.047054 0.49606 -0.062667 0.00379 0.039383 -0.039145 0.0043217 2.8593e-05 0.00025899 -0.00061442 7.195e-05 1.5758 0 0
17
+ 132 -0.28104 0.41354 -0.26791 0.42216 0.0731 0.79324 0.43551 -0.663 0.14854 0.097572 0.0091738 -0.0088813 78.88 0 0
18
+ 5 0.49606 -0.062667 0.49384 -0.078217 0.004 0.039769 -0.039372 0.0056035 0.00017432 0.0012248 -0.00061569 0.00010725 2.0551 0 0
19
+ 133 -0.26791 0.42216 -0.25452 0.43037 0.06932 0.7522 0.39302 -0.64135 0.14096 0.086379 0.0083874 -0.0087171 70.703 0 0
20
+ 6 0.49384 -0.078217 0.49114 -0.093691 0.00376 0.037345 -0.036789 0.0064206 -4.4458e-05 -0.00025473 -0.00057855 9.685e-05 0.99372 0 0
21
+ 134 -0.25452 0.43037 -0.24088 0.43815 0.06787 0.73378 0.36356 -0.63738 0.14233 0.081181 0.0079461 -0.0087364 70.774 0 0
22
+ 7 0.49114 -0.093691 0.48796 -0.10907 0.00363 0.036521 -0.035762 0.007406 0.00016098 0.00077734 -0.0005592 0.00012854 1.35 0 0
23
+ 135 -0.24088 0.43815 -0.227 0.4455 0.06521 0.70282 0.32887 -0.62113 0.15756 0.083423 0.0076405 -0.008446 69.226 0 0
24
+ 8 0.48796 -0.10907 0.48429 -0.12434 0.00371 0.037255 -0.036225 0.0086969 -5.8397e-05 -0.00024324 -0.00056992 0.00013278 0.66353 0 0
25
+ 136 -0.227 0.4455 -0.21289 0.45241 0.05998 0.64509 0.2838 -0.57931 0.144 0.070543 0.0067195 -0.0079914 66.015 0 0
26
+ 9 0.48429 -0.12434 0.48015 -0.1395 0.0037 0.037781 -0.036442 0.0099693 0.00037872 0.0013844 -0.00056645 0.00017834 2.0309 0 0
27
+ 137 -0.21289 0.45241 -0.19857 0.45888 0.05747 0.61749 0.25411 -0.56278 0.14469 0.065331 0.0062641 -0.0078137 62.504 0 0
28
+ 10 0.48015 -0.1395 0.47553 -0.15451 0.00351 0.034165 -0.032654 0.010046 9.4666e-05 0.00030772 -0.00051143 0.00016263 1.912 0 0
29
+ 138 -0.19857 0.45888 -0.18406 0.46489 0.055 0.5925 0.22674 -0.5474 0.14743 0.061068 0.0058772 -0.0076389 58.265 0 0
30
+ 11 0.47553 -0.15451 0.47044 -0.16937 0.00306 0.02868 -0.027133 0.0092898 -0.00019071 -0.00055702 -0.00042919 0.00013717 1.6089 0 0
31
+ 139 -0.18406 0.46489 -0.16937 0.47044 0.05293 0.5672 0.20049 -0.53058 0.15034 0.056809 0.0055106 -0.0074417 55.506 0 0
32
+ 12 0.47044 -0.16937 0.46489 -0.18406 0.00326 0.032437 -0.030343 0.011466 0.00025188 0.00066657 -0.00047266 0.00019057 1.0315 0 0
33
+ 140 -0.16937 0.47044 -0.15451 0.47553 0.04882 0.52928 0.17144 -0.50074 0.14788 0.050629 0.0050156 -0.00707 55.146 0 0
34
+ 13 0.46489 -0.18406 0.45888 -0.19857 0.00326 0.031954 -0.029522 0.012228 0.00068893 0.0016632 -0.00045289 0.0002182 1.7625 0 0
35
+ 141 -0.15451 0.47553 -0.1395 0.48015 0.04551 0.4866 0.14308 -0.46509 0.13641 0.041966 0.0043901 -0.0066462 48.686 0 0
36
+ 14 0.45888 -0.19857 0.45241 -0.21289 0.00283 0.026671 -0.024308 0.010976 0.0011275 0.0024971 -0.00036411 0.00021162 1.6343 0 0
37
+ 142 -0.1395 0.48015 -0.12434 0.48429 0.04363 0.46693 0.12321 -0.45038 0.1403 0.038383 0.0041391 -0.0064714 46.645 0 0
38
+ 15 0.45241 -0.21289 0.4455 -0.227 0.00326 0.031495 -0.028283 0.013856 0.0022383 0.004569 -0.0004091 0.00028941 1.7007 0 0
39
+ 143 -0.12434 0.48429 -0.10907 0.48796 0.04098 0.43883 0.10244 -0.42671 0.13962 0.033519 0.0038021 -0.0061759 47.321 0 0
40
+ 16 0.4455 -0.227 0.43815 -0.24088 0.0029 0.026753 -0.023644 0.012519 0.0022806 0.0043074 -0.00033555 0.00026429 1.9979 0 0
41
+ 144 -0.10907 0.48796 -0.093691 0.49114 0.03846 0.40237 0.081595 -0.39401 0.13817 0.028614 0.003452 -0.0057394 43.813 0 0
42
+ 17 0.43815 -0.24088 0.43037 -0.25452 0.00301 0.028929 -0.025128 0.014333 0.002869 0.00503 -0.00034963 0.00030414 1.501 0 0
43
+ 145 -0.093691 0.49114 -0.078217 0.49384 0.03584 0.37679 0.064781 -0.37118 0.12933 0.022572 0.003049 -0.0054757 39.335 0 0
44
+ 18 0.43037 -0.25452 0.42216 -0.26791 0.00289 0.026424 -0.02253 0.013806 0.002706 0.0044158 -0.00031138 0.00028622 1.6769 0 0
45
+ 146 -0.078217 0.49384 -0.062667 0.49606 0.0336 0.35219 0.049624 -0.34868 0.12774 0.01818 0.002786 -0.0051912 37.239 0 0
46
+ 19 0.42216 -0.26791 0.41354 -0.28104 0.00302 0.027195 -0.02273 0.014931 0.004366 0.0066466 -0.00028844 0.00033892 1.4425 0 0
47
+ 147 -0.062667 0.49606 -0.047054 0.49778 0.03263 0.34164 0.03749 -0.33958 0.11963 0.013207 0.0024679 -0.0051264 36.588 0 0
48
+ 20 0.41354 -0.28104 0.40451 -0.29389 0.00306 0.028189 -0.023063 0.016209 0.0046485 0.0066142 -0.00028923 0.00035849 1.1425 0 0
49
+ 148 -0.047054 0.49778 -0.031395 0.49901 0.03053 0.31944 0.025063 -0.31845 0.12078 0.0095059 0.0022909 -0.0048527 34.692 0 0
50
+ 21 0.40451 -0.29389 0.39508 -0.30645 0.00286 0.026425 -0.021132 0.015866 0.0052087 0.0069373 -0.00025011 0.00035818 1.6093 0 0
51
+ 149 -0.031395 0.49901 -0.015705 0.49975 0.02816 0.29383 0.013841 -0.2935 0.11375 0.0053644 0.0020041 -0.0045258 32.253 0 0
52
+ 22 0.39508 -0.30645 0.38526 -0.31871 0.00296 0.027607 -0.021545 0.017261 0.0068426 0.008541 -0.00023094 0.00040528 2.3006 0 0
53
+ 150 -0.015705 0.49975 0 0.5 0.02626 0.27097 0.0042562 -0.27094 0.11276 0.0017713 0.001838 -0.0042278 31.61 0 0
54
+ 23 0.38526 -0.31871 0.37506 -0.33066 0.0029 0.024963 -0.018982 0.016212 0.0069002 0.0080791 -0.00018977 0.00038155 2.1893 0 0
55
+ 151 0 0.5 0.015705 0.49975 0.02403 0.24494 -0.0038473 -0.24491 0.10162 -0.0015963 0.0015357 -0.0038719 25.895 0 0
56
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+ 94 -0.48796 -0.10907 -0.49114 -0.093691 0.14641 1.6211 1.5874 0.32873 0.013019 -0.062865 0.025138 0.0041761 152.36 0 0
176
+ 95 -0.49114 -0.093691 -0.49384 -0.078217 0.1478 1.6377 1.6133 0.28157 0.010044 -0.057551 0.025499 0.0035187 146.87 0 0
177
+ 96 -0.49384 -0.078217 -0.49606 -0.062667 0.15029 1.6527 1.6362 0.23286 0.0086726 -0.060937 0.025836 0.0027005 149.05 0 0
178
+ 97 -0.49606 -0.062667 -0.49778 -0.047054 0.15109 1.6615 1.6515 0.18232 0.0039427 -0.035713 0.026002 0.0023029 149.75 0 0
179
+ 98 -0.49778 -0.047054 -0.49901 -0.031395 0.1521 1.674 1.6689 0.13134 0.0019727 -0.025065 0.026245 0.0016694 159.9 0 0
180
+ 99 -0.49901 -0.031395 -0.49975 -0.015705 0.15039 1.6618 1.6599 0.07828 0.00028979 -0.0061451 0.026078 0.001133 150.88 0 0
181
+ 100 -0.49975 -0.015705 -0.5 0 0.15386 1.6967 1.6965 0.026651 -4.4504e-06 0.0002833 0.026647 0.00042306 158.52 0 0
182
+ 101 -0.5 0 -0.49975 0.015705 0.15391 1.696 1.6958 -0.02664 7.425e-05 0.0047265 0.026638 -0.0003442 154.6 0 0
183
+ 102 -0.49975 0.015705 -0.49901 0.031395 0.15273 1.683 1.6812 -0.079282 0.0012129 0.02572 0.026426 -0.00084132 156.4 0 0
184
+ 103 -0.49901 0.031395 -0.49778 0.047054 0.15029 1.6663 1.6612 -0.13074 0.0024584 0.031237 0.026131 -0.0015629 149.56 0 0
185
+ 104 -0.49778 0.047054 -0.49606 0.062667 0.1508 1.66 1.6499 -0.18216 0.0050008 0.045297 0.025995 -0.0021497 151.94 0 0
186
+ 105 -0.49606 0.062667 -0.49384 0.078217 0.14725 1.6408 1.6244 -0.23119 0.0065198 0.04581 0.025618 -0.0029118 153.23 0 0
187
+ 106 -0.49384 0.078217 -0.49114 0.093691 0.14981 1.6638 1.639 -0.28605 0.0085788 0.049154 0.025879 -0.0037211 159.18 0 0
188
+ 107 -0.49114 0.093691 -0.48796 0.10907 0.14673 1.6293 1.5954 -0.33039 0.013052 0.063027 0.025265 -0.0041996 153.3 0 0
189
+ 108 -0.48796 0.10907 -0.48429 0.12434 0.14513 1.6 1.5558 -0.37351 0.01585 0.066021 0.024686 -0.0048298 142.35 0 0
190
+ 109 -0.48429 0.12434 -0.48015 0.1395 0.14458 1.6 1.5433 -0.42219 0.022924 0.083796 0.0246 -0.0053152 145.56 0 0
191
+ 110 -0.48015 0.1395 -0.47553 0.15451 0.14307 1.5754 1.5058 -0.46324 0.026058 0.084702 0.024061 -0.0059458 141.96 0 0
192
+ 111 -0.47553 0.15451 -0.47044 0.16937 0.13818 1.528 1.4456 -0.49495 0.029412 0.085904 0.023169 -0.0064249 143.78 0 0
193
+ 112 -0.47044 0.16937 -0.46489 0.18406 0.13775 1.5085 1.4111 -0.53321 0.034782 0.092048 0.022711 -0.0069295 136.02 0 0
194
+ 113 -0.46489 0.18406 -0.45888 0.19857 0.13536 1.4926 1.379 -0.57119 0.042313 0.10215 0.022325 -0.0073673 141.36 0 0
195
+ 114 -0.45888 0.19857 -0.45241 0.21289 0.13325 1.4599 1.3305 -0.60076 0.052862 0.11708 0.021729 -0.0075974 137.57 0 0
196
+ 115 -0.45241 0.21289 -0.4455 0.227 0.13073 1.4419 1.2948 -0.63433 0.055714 0.11373 0.021213 -0.0081772 132.87 0 0
197
+ 116 -0.4455 0.227 -0.43815 0.24088 0.12645 1.4017 1.2387 -0.65588 0.061001 0.11521 0.020415 -0.0084924 130.51 0 0
198
+ 117 -0.43815 0.24088 -0.43037 0.25452 0.12457 1.3703 1.1903 -0.67892 0.070735 0.12401 0.019807 -0.0087161 128.35 0 0
199
+ 118 -0.43037 0.25452 -0.42216 0.26791 0.11992 1.3248 1.1296 -0.6922 0.077131 0.12587 0.018954 -0.0088956 126.87 0 0
200
+ 119 -0.42216 0.26791 -0.41354 0.28104 0.1192 1.3099 1.0948 -0.71916 0.083207 0.12667 0.018504 -0.0093065 119.79 0 0
201
+ 120 -0.41354 0.28104 -0.40451 0.29389 0.11565 1.27 1.039 -0.73024 0.082255 0.11704 0.017612 -0.0096318 123.26 0 0
202
+ 121 -0.40451 0.29389 -0.39508 0.30645 0.11205 1.2251 0.97968 -0.73557 0.097261 0.12954 0.016916 -0.0095191 115.58 0 0
203
+ 122 -0.39508 0.30645 -0.38526 0.31871 0.10737 1.1822 0.92265 -0.73918 0.096118 0.11998 0.016002 -0.009726 113.09 0 0
204
+ 123 -0.38526 0.31871 -0.37506 0.33066 0.10557 1.1606 0.88249 -0.75372 0.10559 0.12363 0.01552 -0.009897 110.64 0 0
205
+ 124 -0.37506 0.33066 -0.36448 0.34227 0.10162 1.1127 0.82299 -0.74887 0.11479 0.12615 0.01473 -0.0097811 104.85 0 0
206
+ 125 -0.36448 0.34227 -0.35355 0.35355 0.09788 1.0706 0.76885 -0.74507 0.11822 0.12199 0.013934 -0.0097869 102.85 0 0
207
+ 126 -0.35355 0.35355 -0.34227 0.36448 0.09649 1.0516 0.7318 -0.75516 0.12301 0.11921 0.013427 -0.009989 103.86 0 0
208
+ 127 -0.34227 0.36448 -0.33066 0.37506 0.09261 1.0116 0.68079 -0.74818 0.12426 0.11307 0.012645 -0.0099759 93.467 0 0
209
+ 128 -0.33066 0.37506 -0.31871 0.38526 0.08725 0.95372 0.61939 -0.72521 0.12705 0.10851 0.011725 -0.0096868 90.926 0 0
CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/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/Kn0p34/simulation0706_Kn0p34Ma2p5/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/Kn0p34/simulation0706_Kn0p34Ma2p5/slurm-28429678.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 66372 child grid cells
6
+ CPU time = 0.0982956 secs
7
+ create/ghost percent = 1.21519 98.7848
8
+ Balance grid migrated 66244 cells
9
+ CPU time = 0.0861375 secs
10
+ reassign/sort/migrate/ghost percent = 61.3997 0.0377989 9.09888 29.4637
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
+ 374 0 = cells overlapping surfs, overlap cells with unmarked corner pts
18
+ 59296 6702 374 = cells outside/inside/overlapping surfs
19
+ 374 = surf cells with 1,2,etc splits
20
+ 109.214731023047 109.214731023047 = cell-wise and global flow volume
21
+ CPU time = 0.0952552 secs
22
+ read/check/sort/surf2grid/ghost/inout/particle percent = 22.83 24.4803 2.72069 24.0807 25.8883 6.40251 0.173763
23
+ surf2grid time = 0.0229381 secs
24
+ map/comm1/comm2/comm3/comm4/split percent = 14.0388 24.5667 4.52225 1.69838 11.7944 7.07535
25
+ Balance grid migrated 1906 cells
26
+ CPU time = 0.0354609 secs
27
+ reassign/sort/migrate/ghost percent = 7.74398 0.0805675 26.5331 65.6424
28
+ Creating particles ...
29
+ WARNING: Created unexpected # of particles: 453485 versus 453486 (../create_particles.cpp:346)
30
+ Created 453485 particles
31
+ CPU time = 0.0133089 secs
32
+ Memory usage per proc in Mbytes:
33
+ particles (ave,min,max) = 1.6084 0 1.6875
34
+ grid (ave,min,max) = 3.23499 1.51379 5.26379
35
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
36
+ total (ave,min,max) = 4.86398 3.22189 6.97189
37
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
38
+ 0 0 453485 0 0 0 0 0
39
+ 10000 11.906634 491406 13676 11320 11 471602.5 10.0582
40
+ 20000 26.87002 495723 13995 11671 7 483128.11 10.0969
41
+ 30000 40.655757 496309 13925 11637 10 487573.43 10.122167
42
+ 40000 54.313574 496542 13918 11692 15 489726.69 10.136
43
+ 50000 67.798466 495836 13781 11563 10 491183.44 10.14278
44
+ 60000 82.02411 497277 13962 11649 8 492086.25 10.138383
45
+ 70000 96.752924 496624 13811 11515 4 492779.68 10.141614
46
+ 80000 110.55595 496882 13856 11614 8 493241.43 10.138575
47
+ 90000 123.87613 496883 13831 11592 11 493613.65 10.140322
48
+ 100000 137.74012 496373 13831 11539 8 493952.2 10.14902
49
+ 110000 152.11407 496824 13894 11623 10 494149.91 10.149655
50
+ 120000 165.57008 497583 13829 11539 11 494347.37 10.150583
51
+ 130000 179.25124 496185 13650 11399 7 494492.89 10.147623
52
+ 140000 192.75399 495989 13844 11540 7 494590.86 10.1527
53
+ 150000 206.91762 496537 14034 11768 12 494740.22 10.152027
54
+ 160000 221.6581 496730 13913 11627 14 494871.43 10.153956
55
+ 170000 235.15536 495688 13611 11325 11 494956.8 10.150882
56
+ 180000 248.73162 496719 13781 11466 12 495028.54 10.153061
57
+ 190000 262.89562 496784 13868 11641 13 495125.26 10.154779
58
+ 200000 277.40128 496069 13743 11498 9 495200.84 10.156145
59
+ Loop time of 277.402 on 128 procs for 200000 steps with 496069 particles
60
+
61
+ MPI task timing breakdown:
62
+ Section | min time | avg time | max time |%varavg| %total
63
+ ---------------------------------------------------------------
64
+ Move | 0.023175 | 12.244 | 68.602 | 434.9 | 4.41
65
+ Coll | 0.33926 | 14.442 | 101.75 | 488.9 | 5.21
66
+ Sort | 0.11939 | 2.097 | 12.321 | 182.7 | 0.76
67
+ Comm | 53.883 | 85.466 | 96.18 | 94.7 | 30.81
68
+ Modify | 0.019349 | 0.12795 | 2.318 | 95.9 | 0.05
69
+ Output | 0.0037214 | 0.011704 | 0.013321 | 1.4 | 0.00
70
+ Other | | 163 | | | 58.76
71
+
72
+ Particle moves = 99040167837 (99B)
73
+ Cells touched = 103904497095 (104B)
74
+ Particle comms = 218398579 (218M)
75
+ Boundary collides = 0 (0K)
76
+ Boundary exits = 22400525 (22.4M)
77
+ SurfColl checks = 78511820 (78.5M)
78
+ SurfColl occurs = 2031229 (2.03M)
79
+ Surf reactions = 0 (0K)
80
+ Collide attempts = 3026052562 (3.03B)
81
+ Collide occurs = 2331891575 (2.33B)
82
+ Gas reactions = 0 (0K)
83
+ Particles stuck = 0
84
+ Axisymm bad moves = 0
85
+
86
+ Particle-moves/CPUsec/proc: 2.78928e+06
87
+ Particle-moves/step: 495201
88
+ Cell-touches/particle/step: 1.04911
89
+ Particle comm iterations/step: 1
90
+ Particle fraction communicated: 0.00220515
91
+ Particle fraction colliding with boundary: 0
92
+ Particle fraction exiting boundary: 0.000226176
93
+ Surface-checks/particle/step: 0.000792727
94
+ Surface-collisions/particle/step: 2.05091e-05
95
+ Surface-reactions/particle/step: 0
96
+ Collision-attempts/particle/step: 0.0305538
97
+ Collisions/particle/step: 0.0235449
98
+ Gas-reactions/particle/step: 0
99
+
100
+ Particles: 3875.54 ave 23109 max 0 min
101
+ Histogram: 82 14 8 2 6 6 6 0 2 2
102
+ Cells: 518.531 ave 519 max 518 min
103
+ Histogram: 60 0 0 0 0 0 0 0 0 68
104
+ GhostCell: 13340.3 ave 24514 max 724 min
105
+ Histogram: 22 8 12 10 17 3 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) = 1.67432 0 3.375
114
+ grid (ave,min,max) = 3.23499 1.51379 5.26379
115
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
116
+ total (ave,min,max) = 5.10423 3.39595 7.14645
117
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
118
+ 200000 0 496069 13743 11498 0 0 0
119
+ 210000 23.066268 497112 13947 11688 11 496174.87 10.1592
120
+ 220000 46.542476 496547 13876 11579 9 496614.62 10.169
121
+ 230000 70.112627 496772 13940 11611 10 496577.6 10.161267
122
+ 240000 93.372381 496836 14106 11919 12 496648.82 10.169925
123
+ 250000 117.72865 496129 13850 11555 13 496661.4 10.1642
124
+ 260000 140.46797 496544 13877 11601 7 496562.31 10.167167
125
+ 270000 164.28113 496546 13879 11623 6 496567.42 10.171243
126
+ 280000 188.03417 496120 13874 11596 9 496567.43 10.168038
127
+ 290000 211.27594 496665 13905 11700 7 496541.8 10.161444
128
+ 300000 234.699 497137 13948 11632 14 496608.32 10.16508
129
+ Loop time of 234.699 on 128 procs for 100000 steps with 497137 particles
130
+
131
+ MPI task timing breakdown:
132
+ Section | min time | avg time | max time |%varavg| %total
133
+ ---------------------------------------------------------------
134
+ Move | 0.012657 | 6.17 | 34.568 | 307.4 | 2.63
135
+ Coll | 0.16882 | 7.2731 | 51.298 | 347.2 | 3.10
136
+ Sort | 0.068353 | 1.0662 | 6.176 | 129.0 | 0.45
137
+ Comm | 31.974 | 47.833 | 53.49 | 64.8 | 20.38
138
+ Modify | 2.3785 | 16.998 | 89.851 | 474.1 | 7.24
139
+ Output | 0.035071 | 0.036965 | 0.040998 | 0.6 | 0.02
140
+ Other | | 155.3 | | | 66.18
141
+
142
+ Particle moves = 49660832019 (49.7B)
143
+ Cells touched = 52097861508 (52.1B)
144
+ Particle comms = 109414466 (109M)
145
+ Boundary collides = 0 (0K)
146
+ Boundary exits = 11221878 (11.2M)
147
+ SurfColl checks = 39306897 (39.3M)
148
+ SurfColl occurs = 1016508 (1.02M)
149
+ Surf reactions = 0 (0K)
150
+ Collide attempts = 1523081443 (1.52B)
151
+ Collide occurs = 1173670771 (1.17B)
152
+ Gas reactions = 0 (0K)
153
+ Particles stuck = 0
154
+ Axisymm bad moves = 0
155
+
156
+ Particle-moves/CPUsec/proc: 1.65307e+06
157
+ Particle-moves/step: 496608
158
+ Cell-touches/particle/step: 1.04907
159
+ Particle comm iterations/step: 1
160
+ Particle fraction communicated: 0.00220323
161
+ Particle fraction colliding with boundary: 0
162
+ Particle fraction exiting boundary: 0.00022597
163
+ Surface-checks/particle/step: 0.000791507
164
+ Surface-collisions/particle/step: 2.0469e-05
165
+ Surface-reactions/particle/step: 0
166
+ Collision-attempts/particle/step: 0.0306697
167
+ Collisions/particle/step: 0.0236337
168
+ Gas-reactions/particle/step: 0
169
+
170
+ Particles: 3883.88 ave 23450 max 0 min
171
+ Histogram: 82 14 8 2 6 6 6 0 2 2
172
+ Cells: 518.531 ave 519 max 518 min
173
+ Histogram: 60 0 0 0 0 0 0 0 0 68
174
+ GhostCell: 13340.3 ave 24514 max 724 min
175
+ Histogram: 22 8 12 10 17 3 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 = 66372
184
+ CPU time = 0.0091433 secs
185
+ Writing surface file ...
186
+ surf elements = 200
187
+ CPU time = 0.00147022 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 0:00:10 (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 0:00:09 (wall clock time)
203
+
204
+ Processing SPARTA surface information.
205
+ Processing dump result file: ['./output/surf.300000.dat']
CylinderKnMa/Kn0p34/simulation0706_Kn0p34Ma2p5/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
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11
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AQAAAACAAABABgAAFQYAAA==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AQAAAACAAABABgAANAYAAA==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AQAAAACAAABABgAAPAYAAA==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AQAAAACAAABABgAA0gQAAA==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AQAAAACAAABABgAAFQAAAA==eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAABABgAAFQAAAA==eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAADAEgAA0gMAAA==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AQAAAACAAABABgAAXwEAAA==eJwtxVFEHAAAANBKkpzkJEmSJMlJkiRJkiRJkiQnSXKSJEmSJEmSJEmSZGYmmUmSJEmSJEkyMzOTzCRJkmT20Xs/LybqXazjHO8EB5zoJAed7BSnOs3pznCms5ztHOc6zyHnu8CFLnKxS1zqMpe7wpWucrVrXOs617vBjW5ys1vc6rDb3O4Od7rLEXe7x73uc78HPOghD3vEox7zuCc86SlPe8aznvO8F7zoJS97xate8wd/9Cd/9ro3/MVfvektb3vHu97zvg986CMf+8SnPvO5L3zpK1/7m7/7h3/6l3/7xrf+47++870f/OgnP/vFr37zP0dFvxfjWMc53gkOONFJDjrZKU51mtOd4UxnOds5znWeQ853gQtd5GKXuNRlLneFK13late41nWud4Mb3eRmt7jVYbe53R3udJcj7naPe93nfg940EMe9ohHPeZxT3jSU572jGc95/9sSVRSAQAAAACAAADIAAAADAAAAA==eJxjZh4eAADsVAJZ
37
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38
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_AQAAAACAAACgWgAAmxAAAA==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AQAAAACAAACgWgAAjAIAAA==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AQAAAACAAACgWgAAW0sAAA==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AQAAAACAAACgWgAAZzkAAA==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AgAAAACAAAAIDgAAlxcAANUCAAA=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+ </AppendedData>
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+ </VTKFile>
CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/Lambda/Lambda_2_300000.vtu ADDED
@@ -0,0 +1,27 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ <?xml version="1.0"?>
2
+ <VTKFile type="UnstructuredGrid" version="0.1" byte_order="LittleEndian" header_type="UInt32" compressor="vtkZLibDataCompressor">
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+ <UnstructuredGrid>
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+ <Piece NumberOfPoints="1818" NumberOfCells="1700" >
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+ <PointData>
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+ </PointData>
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+ <CellData>
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+ <DataArray type="Float64" Name="id" format="appended" RangeMin="12901" RangeMax="15064" offset="0" />
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+ <DataArray type="Float64" Name="xc" format="appended" RangeMin="-4.9574" RangeMax="3.4845" offset="2984" />
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+ <DataArray type="Float64" Name="yc" format="appended" RangeMin="3.5897" RangeMax="4.9573" offset="4152" />
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+ <DataArray type="Float64" Name="c_6[1]" format="appended" RangeMin="0.017619" RangeMax="0.029307" offset="4472" />
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+ <DataArray type="Float64" Name="c_6[2]" format="appended" RangeMin="0.20663" RangeMax="0.3437" offset="14780" />
13
+ </CellData>
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+ <Points>
15
+ <DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="3.5471440458" RangeMax="7.0710678119" offset="24500" />
16
+ </Points>
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+ <Cells>
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+ <DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="30656" />
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+ <DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="42960" />
20
+ <DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="46028" />
21
+ </Cells>
22
+ </Piece>
23
+ </UnstructuredGrid>
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+ <AppendedData encoding="base64">
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AQAAAACAAAAgNQAAaBwAAA==eJxtW3VcVV3TxW4sFFSwuwtbx27FR8VuxcAERcRuVGwfO7CxA7tb9J5zC9goioqKjdiJ8c0+3OX297yf/1zv5XLOPrNn1lqzZlPwqsWlzkFBGeuv9w7dK2jvs+1fFvH7m4sXNTx7QFCrNk9eZwwTFDPqjK0Xv5bRckScPinI3its2SqToNLvi79Yd1PQ+sIvGzjtFnSy4cxHEWsEjW2zt4jfEkGV7hVPP2OloFejNr1cul6QeOZb7vNqQR8WdxpXnF9tpeQFBF18Fpzz8jZBJRNmbTLvEfQxz/Z8ITsF5ejd4UFVvu+DPJd+dwkXdMF5Q7WtRwVl3njrdgn+XkD3tiMa8Dp7+ceV8dgnyLjtDkEdElpFeq4Q5FF/6uioUEFvvMvlnsrr69PmRob6vI53FV3fbVyj1tXy6r8tt/J64ipWvzVsu6D6TbfVnbdRULNB3a4VWCtofuT9+Cx8vY5N53qfXSboc8NylQcFcJy6345yniboVL5R/AiCzpTKnuUYr/tIhh4zinA8m+U6t3DAKUFDgwrGbTym4td8bbaqN28IalLbfqAxx/HGsS0DNlwQlGv4uzJO1wW9f+meJvyWIGf+Vvfbgg58ata4p0VQ2IHJq55dElRqeHST6qcFFd3bs36pc4KSe4289ovj4xnZMajuZX6eb62OeUUIynT11fd0ZwSFxE8rF3tYkJ//hSb/bBbU81XI7OMbBCW0f9HvJ8fH2j59i5u83s9JS77s4f3qUONJ5jf+vJ8H0zxbWFqQd3Bc1prxUZR/18JpoX52KtHN3fLD10L/DF8XuGGrRt7J4+oN3mwikWlo0RETTPS+z7GqD1ebSJ9Y5d/cr020dF6ZZU0rafQ+QxrruWCNPviN3OX2TKMAc8L6kaN0WjY1uc4Yi04jitxolKmamdpn6cMpYKbCx+avSPawkFvJTum2LbfQAOMXrfTp1J0FP32s9NPXOYdut9LSKoEVihSykW39gs5uPW20YWuxUz+CbeTWM6N/h8s2oq49D19ItFGBtlfe5qxip6/5XJ1nD7JT1fr952f4105349ZsOnTVTmUOlE0+kDGS6u5Zxxkd+Sev919cKvZvEtRw+4Pzzhy3ugmDT6YKVfuNvEKe/PDsvq3gVkHDOmY+fY7zaWK+a/5tOL6clKOPcz4Um92iQAvO16Dl4zgCgk5vPu/TnvNvrv/W3nP+FZTqs313Ob5+przB1S5wfQQYhSnIEiETRdDOUuXfTef9Ht5vb9qQK4J8Y3v0Lc518f7YkFVpd3GeGgkkaEqQvJKg88FtFtflusiZsHn22uOCnp+9XvEfzpvT7YtVWHlC1fMYyzx+As6HWWeOjL8raLrzhyfpOP8253ELPy0Eyaybxe8PyjS8x3W7MvF2xquCas0u6zmJ82qSsSBBe/p17liK33fSYr4X3SLo/uIxPd5yPPLfa5TYlt+7rJrQMJaf0yiPHSr/EO+N00tenst1P75qrdZ9uA7LT3k+8/sqQRHTEz8lMa5kON76UK0NKv5pphT1Ws448G3WjGf3OR79usvICyowaPmyI4f49/hpPfk1Ja8E/V65suSOzQpvTiQ93e3M+2LKc/9J0fOqzsqXa9e6EccnOKyrqSo/5+G4SN+WcYJWyV/n+OSVMHVEUNKri7WLtea6suw4uScxitbmavWx6gI77XeVFW4hmYVt72rEz7r0ZISJZsvwzjFRppG1Vz/aY6JBBeXKTTQ5+2r3wNaaI980WpjHc83chxrNax6Yo24nnUqv958TeEon79xN72UobKYcB1+5Js4105Ifly6OfWMm+e1iAyw0y3VKumHXLRRdziffo25WSj/oYOC0s1aSWZ8qt41k9pTpaqMvBSvWTvrXRp5l0t3rE2mjlr/6xZ/6YiNXnxo3ihez054pdQpW62CnbcvrpGo3207GcsPtlLX7vZe1X9ipa/jAYjmYLySKeXEcG2gf4pP2KRzZFHnpOzEuTu34OurdGoWL2xqG3ljB+/D0QAneAYXDyHtcFzgPPF4elJA9PX9/qHbKpStff5eTm3Uz59OpiMjgirvUfSbKr00SlKWRc+s1wwRVOZ6DM1/QsvcrfEMXC1pdu3fe3OtV3iE/DDpknHwU8HPmvUMqf0o3vVikM+flnLXHp/nsUPd18niqZeGfT0opEEd8BP08u7vlHL5O72/luZQE+UQ0L9yH8fySuyQk5sfp/RYXvKDqNl/aLs4VwhWOoz7XtpAbovIS6wJfIt419jZghBNUMW3t0v25Hry3X77deCmv3yBgQYUNAuT4adNaXpgiqNDG0++7b1LrRv2/SbP0ztWbilceFRvQurideXh5urbxMbwv/W687GIVxG/u1WM8cI21fOn0mPn5SomIjZGCimdZc3H/GaUbonhXRjN/7ikX+iRojKA8XVdO6ZqW92NtWbeV0VEOvWCn70cKlSl6xULvmj9dRm463XxCjLQmGrm/Uq47/iZHnpqok+11iUV2E+Uu7zxkqqdGYUERZeos16jV9HU9jsdolF3Kg5o6PWzWt9G6wzp1Xvih5pYcZtrYxs87NtDsWK+Zmv6z2SuhlYXqtzo9+L3ZQsF55Q+s1Gf6lHEvTVYqujjAr0A2Gy0oNDCpR2Mb7Vx/tfAhfxvVc0n3vekmG6XAlo1KFpRMaafhLeMGvmhip/A2nUdnG2Gno90lQ9kpyXJnpOs6la+/nJvNaMD64Znn+Pkv96s8d5Plyvj4pJRo4MH49jbsepua8xWvDGfVdG+F4mvwOV5rVZUIIOjf4Dk9os4qHKw3/ETvoYyL2WN+19ZXK7yU1e7G96/y6lqH9kcVDjd/tct3JtfRDEaHCfz9FBxTOs0IH3/PKAve35m1J/64z9dL0QFKtyFvobtQ142kbNqr8nx38NBxGXj9/t+yvzjBcfh4JeNDO+ufyaUGn3MzKd23wsnz2Ahe7+hcsy6a/uIPxMvLKDRBRcbvtAUxT06LrR/UbZfCmc3xA5pl43W1q+qf9/NRVXejjELi/HSWCk7QvWOzJ9sYzwvm9W33gXGitAxXEMdr126f4Vw35LEk366Fin9ut5BMofgJ610zSi5U6bTbn7KMv8K8K1mzO9dHHaMQFU8jLry4K315nz96jTm8NT3rsHy/Gzy+HOV4PjvlurxtUbEYC/2KnvCiZBWd/PaF3B3qpFGhjyO6TDlgoim2I5x5JtqbeKbo1wcmR15qDv7XqLnl8qbxXzWKjg4/dr6lTn0NQapTzC65EWb6Xupkt39mmWnOZHkhMxnhbmahSlIW77CQVNvZ8ljpdYsFNw4tsNKabRFvRn63Ur1Zc39lqmij5KJbKjzraCP3vpMGt5puo1wudD3umI12lG/i/uqRjarPsQxPzGWnHecuuZbspPijbj73EgdZ3xplyTgSdfaxiwfj0OdiUoELB3+xvu8+t1YMv3ct51s525W/8syBW5LtXE+ovIIehv6G/rKJLomVeB/OiLGRyZxvzx7f6VCF79/+1OUzva4qHDMen/etepvUHDLOC0e/JFZa39c7qfAR/QfqE/0U+hH0McDpcXzXW4y/d8MeV0mzUuk8U3zpoADOuzqSnpYofkQfVfTn54B4zrvQ7rk27+R8G/LeXKMm53W2n7l77dul6hH5PuHUvDdXeV2tjQfnvqveybrDT6jfQ78D3gCvQL8Z8nKtwqFqVw9XHMU/3y63/YjCmwrhG9+EcRx/PD7n63NZ4RH2EX2innTzSmOuY8/iSYc/ch1//VG58YSjap/jN+Tk1BC0NUluqOqXgFvAz8lN284vPlHQ0Rvjz4fmZx6vUnjSueQoMmT1NTtxMC5Vz2qlXFVKLH/uo9PdvFLQaHRn33dGHhM9OVIve5LFRCziCzXPqDn0m0Zy14P28PdqDajQIJ1Opapk3OfeQ6dCW+0eV7k/+VrjZ+wSFzMVfHg0vllf7k8iR/fNYDGTr1uDojubWsjvpl/YuEMWMug1g9WhP6xkhPe1ld59bM0ZrOqkDO3+/GKCjfTVrv0KbbRRpgKb+pTRbJRzTEZv38+2P3rekAcbFY5if7CfL5q4Rp/QhaMfYl3A6OdpZv0uZcYJhddnD/Q9VOC44g3kJ/Qz8HtxQ/lNhdPI9/HGBgnSNlQMmW9W/ev5s07Jz6MFHfKeee2hrnAPdcBNVrtTnBfmgPzDdnO+9Fz7ts1Pfs22d0KxD9wHe/hXi5tuVf0E8qpX4UbvBurqOVA3iAN05rq18h/zadrfPW9y/WhDZMELOi7Dx/yzdPPXKk/5+WpnmXTnIdfv0cV7Ss47reoRdQPeg25BfYwKqcpSUFD49Exxp9crn2ThqeGZvvE+DDSEveKTdRYpLNW6odOgC8E3U506rq91SuEUdBQ/dO82N9Q6wSvYN/RTqO9PGz6ef/cXvkHH+iSUTxzG+jvV/dSZFhTiPsfuxP+LpqwZGvOjRNJzWe6LOD9l2Bbpf/p098Yr19W3meh6taHPQ+NNjjrTaHWXJo8KttHohfOAIZk3amTIuEw6sXh5kThIpzQ9pTOgU++HvSs+qmum12tLpPL1NTvibnb01xaacNTvao/JFvpt7c+pwzxybwXvuNWRT1by8G6XI4D7eat8jDY28pIyfayNjh4K8/i1zkYLz8+sPtBu+7Nv0BnYL+h5xA08C96H7l2wOOF9IY73hKT6DOHKb0H9YF9ktc3n63WrLSOh6mhlP79aH/YqXSJZ/Nlf/SX6bvSdfVl1beN+poeE7/2qn4Aex75KlTEtVPkIuA50EPgLzw1+Qb+KPgT9DfoX6L7vwr3wGsbxPB5Saat44XnRb4BPWxgCjddXTxSpeUXlOeKbNJk8+5xWvgb6Nly3i1xmqOIv9PUbwuokDOa6eSJqM8Wr58H3oEvxOfYhS/HSUxeeUvuA/g/XRVzBy8DR//aL8Gcu9Ks5oifrSd9LIZxZjGO1NnwT7tH0/bUkhkjqEDEwfdnHVuovvxark5VVjOipkUic0aXfDRMZ4ddYfx0xL3qRSaONG7MuXt5Vc/hEGjkZ/3S6PFcaCTrl4O40+2qdgvSGPj+SdYffZnboQjP5pWlAC3NYqKWUWTUtdGJ1dZbmFspZcKT74bxWSt1y5KOEqVYy5NMrK61wkwxhI4myZ3rZ6C6rmQezbdSJd3MY82kKLwqSbOiiKf8ROgl5AFyFnocuxXvgL/oA8PKlUbePlz6i9hF1AV8AOhz7ge8fluXM70eEN+cWn/V3Bun4sQ4Y0qtWjuVqX6D3UWeoH+Af7oP9hL8J/Ac+D3MaPSMtx6Fsx/4jitxQfJPC46wzDcHK6w3o7NmI+axQm0KnN5//374BuhP+G3Qr8AT38WqYu/+VKFU30DPALdQPcCVt2rEfv55TfJGCs6pfhO4Cfx5o8XCiywFVL4jT4OFTltlYH+brIjtqpd/gn28ZcuTl2GOqPrEfwEX0/9Dn4NnKlS42qBMgyJBXzCdMXg+2lI4mw3ZqHUm73J6NblzERotKv852vrKZMi6psbhbiEbLj0jgVnySlDEsXaXvJspUbeRvE+suWW2F1zC/uAe2zvBKoxXXhzIF6FTB2Eidnj5/N2n9L51sTW+//dja7NCpZgrPOe/WpywWMmjDy0JMTrxhFkpeJQ0eK10Mj9zuMs7q0CtW+rizaJ7reW0ks+dTM9sf/wbPD92DfI12ntYuZpfqH1AP6Kvxc1wH+Ql9CzwE7+O13PYf2++EKZwEPsHfSvE11FwCujl/yM4jK7ieE7d16tpAU/k1tuI1b58HrPMzvPrt/pTx7Ufwx7u3mEcisna+fgF9pCDv2MBmb/n9ryYS2VR+wy9FXwr9gevn6SidNUE72ssPBB3Lk6wlsb55vCf8zYJ45t2BUoGquqmc645/Rc7/V3KMcUbFp0laqSyUnoWeR78+Zm2UT5XDqk9GvaH+4F/DH0Y9IM7gB/jp4FHwAvzz7iFeqSr/hWPos4AbwEXDLj2p6hb8CR6Hf4I+ET4yeGbO8Q1t/Ly53vfnKu88JJokexReEUnF7VrpVT1tDl/B7OifNHJLnDsypKpGhn2ZXaOxp8uXrFFIo5Hc3R8foDl4S6OVztLQ0SiMkpcVZT7hZq//13k65dld+XiOBJ1+dKTRZTuaHfE20w+3sbdyvTeTjwE4FjLKboWFZNeZJq2VQvfuv913vJUmGnaalVwMYLH96Q+A8/2relcuu1vVCfpBzEOwz5g7YP6GfhP4An2BvhS8gd/H3CrV9hp+/heUDka/iHqEz4VX5DnwGH59fOvxI9I+Up+jv+zstHCIzab8BOw79BTmAy9Xhmf126f6auhJ4DTq7L/rgJ/l/upRjfwXFf7CX8B1odczt6m3eQT3Uy7GYEjQtTSmnb0eCirS/WLaUfeEYx7A+u5Z8u53kWrdjY3GRPlXqB/ECzoLeI7PoQ8QD8Qf/Q34E+sDfyMO6Cvh987kpy8RoeaPS9tL40r5AylzNkFGOV9RfkmPSnLyJShm6UnO8GhK5N3vfzeSWDTWzLPb5riumQININKIxU/w1oYaGe3GDxM98Fq0elQujZKDOi3LPFBz8KtG36rIytbIoEHSKf683ACdxs4JZOWgk1RxaXqaHX2tmWaavn7J52oh0/zxfCcLNTYIyuLon6xkD1rUe+tEK82b3mRXxyPWPzoUvI24Yd/vLvjp8yVB6QrkG/pb5NuhwuZu1TeqOrrSQgK/oCBm83JnFR+jbwQPoE7gu6TMmRiHJOzEMq5ylEJvKJ0CXB+8ueqvKdeV/oGekasjvm4Kviif/7kc23P+NTMaAUED8oweVPCboIJhz1tW/C0odeyre4XeMD7Idpd/Lt165xjG18m9CpS9rnQ88AA8BxyFHkHeIi9PBtT0CrihfA3oV3xe7dvg9QWiVDyQ59Bh1+NkQTA/VN33aJGudBn0Fq6LuEIHHDl2vuVQTfEirgs/C/dPF3JlbV+zyuvHP9pxq6XqEPjRNGQEV6zStdBlTG5Pei1Q/jH2HfoQ/g70BDfBWW/0YT23dSJvaTQ1Tmy75UP+KEpnNOC2Pz5UyvxapxUeBWZM6K3RUBnePJojjzUqyV15bA/NMQ/THP6bRtJdHVldpxLpZ6xsEsJ9ibSho3T6nVYijZmyGwNIM0lVeus28wur7il1LJSm5JhXozZZ6KV16vZ5WVV/Ahz8JG0vzofaUi7aFG/Db0J/jPMcKfWleAZ4CZ8Y+wUd9iVAFrA634B8g24Cj6MPBl6i34WeRt7BB/4zv3P0wbifMX49puoG+iensbGCyGl3uw1xam6G+pfonue+IEmCYzk/3y6Qhg73sb2uBg6IUfkJvITvjDwA3kP/AU/gw22UMjdCzU8QJ/AF5o/1jYMYag4JHIEuxO+DtzDPiHz8pcbPWNUv/XedhY2NUnoM54bQr4G34Sei3rAv2A/c96BFGrvq+aH74FNDn+AV960h26UZjHNfEvpviYkmqYb6j4ii3dulgLXT6rHSibI4/Fbdoes0OuchjV2NDJngqVHOVMEddgzWHPpFI1kVI55pdDubdJR1Ktxcdjg6yVNA7WJYfy1s/TJtdeap2VEzXVnXpehhM8kpUkQZC82fJCvdQi5GI2P5Mx8ELqD/hZ+JfEZc0ZeAF/auzHQh2qrwHPwMfnfRKuyfe1XhOfwt+K3wAaDnU5eTk1Cl06C/UH/gfdQb7pdyMErQslKtbrU9r/IYcy/MPw27Y6HS4dDJmD8gT+ATow5RR8WNxkbQrW1j6mfm/qb7qGEMjYJWeL4skv+ewl+cu8JcCPVpwLFV5S/4BP6AnxFo5TvnM4xL1edAR4JfU+bF6rnRD0IXQR+ATwrk+tLtO9frLk9z3fZ2xU+oN9QDPk/RL8w/cW86uDwX9LqsbBxVPWM/ER+8gpdQb6j3lPmGoOQDGX+d4HzrmN3+3HmAcPi20eSe8WbqkmOiyDgGMsZOhYxGykpta85v1O+JTpPaT3zw9Y5G17+t7zBvujrPldJfaQ4drzl8KdZfLk6P8zGfGG3OMp2qymNaH3UKOtiDEdfsyHMzfX0gA2sha6s3BfpOspBhT8dZ/vhW4dxlpPoLn6Gv8Fw4DwUdDr8E+QpfGL4f/BKcT8L3gOeLkgqP38nxdzc+4PhwF0v3Vd4hzqi/GtKmtSu9Z8ssT8gwLk4/0XAm58s8OU6IUjyDOQPqAHME8D/OSaFvBY7CN4Bvtn+UdP7/91wh8ge6EPm+Ux4/+n/mCzjfBv0J3wnn3aA/0AdCn8CvxnrQx6HPQX2l9JXKTxjU8PPELxFqLoj1gJ9QX8a4WCh+hL+BuEP3+YeNO/SL34culgmgdC10GHAGPid8HOAF+As6ZMspeTCO+c04CCccvMA4J8d1erTjHE4UnfOUEy+7Y51Wytmp6Pw+zc1Uc3G3EK9UOh3yH7rs9WSNjHHucM2Blxr5Bl8oOTxao+XkNiGpvk7ZJWwE67Rz6v3O2y/r5Ju71Je6LmaKir0ZXzrITMaY6IGZRMn2SYGlVZ3g+Z/2WrDXdF7pJ/gU6C9wnshr+YG1k//yaYG3OH8KHTGk1KxtCULl+9c9MuBKf0EPvf4kjUHFyzjnCJ8LegXrw34A78EfmF/jfBjm/TifCB2O58McD+eUUd84RwY/bUF32VgqvwFxQB3Cr8Hn0IX/PX+GPh88DHzHc8LHgC5E/cJ3rSnHxsvU+TTUO/xanG+DT4J5C/QZeAnrxlwW90U8/3uebozxH8ZDJ1lZXNfcbV+ZzLzhdfBfn3nM+/HyoJR6HvTj8MFSfCHWm3I8PolxUsqMOcJxvknhE85zp/hUgmoZABnt6BOiyGjzMkWmyLAiNgf+mum7pJEmumMepVGMTMtAje54SwdBI+NY5H3Vv2dpXiIg9Trd0e/oxDebFlvf7OifzCTV1hQnC1U2BJrlz/wMdQ39Dj8DehG4gLyCfwFcwZwaeYT54JVPpXstYXx9GzfpZMJJ1W9g7g2+kVngHarOeQG3cd4K68O6MOdFXpc6N3ry67UKh5Ev0ImY2+D6+B6ug/4Vehr6EXqgWt52XPLML/KYWbDa54OMFuZF6jw/eAjXxfwauIHzNOiv4ediHgQ/Fu+BU+Bf1Df6ZvQF8FegW+Ez4X7wLcBXu2PTSEr783cAOIdq2MfTuL6MAHIfKo/vrlD9Inw9zNPhT+AVfTzqFnp8oHHQQ/29AM7rQe+i34cv3TJv5Rk9AwWt73E8xjUT89syaYhEk6nzpV3b20dSywtTPGoNsZGcqrbKaqFvX+SBdZ3mDewd1zyN7jh/rDl8GOYTwyjXKeZRJ+4IdZovx/jb9D/zyonSFstipvOf9eVOnmZ6mLTv3vgt5j/+POZhRlpoSmdBT8A/gf8/t3CGEvpf582lq71wg8rDsh77fo9do/IW8cI5pnrnOq4qsljhJM59Xw+TRM24zWxRbqbKP8wBjWMYf8URfhLqFn0lznsg/4CT0PnwsYFb6MOwb7gfdBp4DfMy+MPAW8y3MffHXBL5DB6BLvrvetHP4hwA5pnIa+h59MeYJ+IcAPALcyPkW90aqd+dZtzvMajuA69FSt9B72Buj3nNHaNslJ7FuWCsE/4w4ofnw3we34Ouwrk69KfA300ZAoe8Pq70O3gf9Yu6nPPqn5MFGYeMY7o1OC8NBomm9Gf6392qR9JE42ChjeR0o5HVQpfb3r0QHqmTYXclaw4e0xznYFS/kuK7aw6dzP298YdJmmPur9N4vwLZ4ivo9H9b28/NAQAAAACAAAA4VQAA9xEAAA==eJxF1HuIRmtZh+FdWcREWZQFJmaFWWllFiPlTA6JSU0WjTgUO4tRKkMqZNPBJMWydollTZpleajI0ijKDhB4QiJEQcRERGSyA2KDDCFhJTHlNXA/zwcfXH+utd7fe99zz2ve+uhPfcbJPZ/8/eQTXzm+ftErxj/47peP3/ugl42//d7L8Vte85LxN374xePXPfJF44c++/7xb/7tC8ef+b8vGH/i5583/rfPfs74Xb993/jvvvzHx3/4588c/+o3PWP803//tPHFd3/v+PQDZ+PDH3ry+GH/8aTxwXO/dfyfn348vvr1x47f/sWPGf/Vax81fuXXP2J8/xu/dPzsJz1kfO97vnD8xKd93vjRH/ms8YPv+4zxA27vGX/w8/7rLfkvH/HR8S8e//P4+57yvvHX/ug7x5/6/LeO3/fSvxn/6etfP37+W189fsr7Xjr+yo/+yvi/P+1549//umeOv/3es/HHfulo/Ltv+IrxE64+d/z+z//4m/NXP+sd4+e+7VXj3/mGHx4f/cvnjJ/zhB940z7P7dFu4+Y4f/Mzvutb9twvx5/4+TePX/fI6/Gjrg8en3/hzQ8bf+DycPyYH/nO8a887unjDz3wZ8YP+dgvjZ/0wd8Y3/cPvzd+9V/88fgdr3jD+OMvfNP4y37i7eMnf98/Pn7f/Wr8R1/z7+N3f9F/jv/3U/5v/AUff8DJfueD8cmHHjh+6lMfNH7WOx48fsHjHzZ++V8/fPxnX/XI8dte9ejx+z//cHzzy48bP+D2ZPzg+75t/OiPnI6f+LTvGd/7nvPxs5/0/eP733gxvueT7frln33mnbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cratXs4G2tX1q6sXVm7snZl7cralbUra9c+z+3RbuPmOGvXnvvlWLt2n9dj7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF377ldj7cralbUra9d+54OxdmXtytqVtStrV9aurF17podj7doNn4y1azd/OtauvSPnY+3aO3Ux1q5/+tiP3Vm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXbuHs7F2Ze3K2pW1K2tX1q6sXVm7snbt89we7TZujrN27blfjrVr93k91q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytq173411q6sXVm7snbtdz4Ya1fWrqxdWbuydmXtytq1Z3o41q7d8MlYu3bzp2Pt2jtyPtauvVMXY+167LPuu7N2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu3YPZ2PtytqVtStrV9aurF1Zu7J2Ze3a57k92m3cHGft2nO/HGvX7vN6rF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbVr3/1qrF1Zu7J2Ze3a73ww1q6sXVm7snZl7cralbVrz/RwrF274ZOxdu3mT8fatXfkfKxde6cuxtr1a//6M3fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra9fu4WysXVm7snZl7cralbUra1fWrqxd+zy3R7uNm+OsXXvul2Pt2n1ej7Ura1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J27btfjbUra1fWrqxd+50PxtqVtStrV9aurF1Zu7J27ZkejrVrN3wy1q7d/OlYu/aOnI+1a+/UxVi7Pnzv8+6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q7dw9lYu7J2Ze3K2pW1K2tX1q6sXVm79nluj3YbN8dZu/bcL8fatfu8HmtX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXt2ne/GmtX1q6sXVm79jsfjLUra1fWrqxdWbuydmXt2jM9HGvXbvhkrF27+dOxdu0dOR9r196pi7F2fcn1C+6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q7dw9lYu7J2Ze3K2pW1K2tX1q6sXVm79nluj3YbN8dZu/bcL8fatfu8HmtX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXt2ne/GmtX1q6sXVm79jsfjLUra1fWrqxdWbuydmXt2jM9HGvXbvhkrF27+dOxdu0dOR9r196pi7F2fcdrX3hn7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snbtHs7G2pW1K2tX1q6sXVm7snZl7cratc9ze7TbuDnO2rXnfjnWrt3n9Vi7snZl7cralbUra1fWrqxdWbuydmXtytqVtStr17771Vi7snZl7cratd/5YKxdWbuydmXtytqVtStr157p4Vi7dsMnY+3azZ+OtWvvyPlYu/ZOXYy166eefv+dtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytq1ezgba1fWrqxdWbuydmXtytqVtStr1z7P7dFu4+Y4a9ee++VYu3af12PtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXfvuV2PtytqVtStr137ng7F2Ze3K2pW1K2tX1q6sXXumh2Pt2g2fjLVrN3861q69I+dj7do7dTHWrj946IvurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9au3cPZWLuydmXtytqVtStrV9aurF1Zu/Z5bo92GzfHWbv23C/H2rX7vB5rV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7dp3vxprV9aurF1Zu/Y7H4y1K2tX1q6sXVm7snZl7dozPRxr1274ZKxdu/nTsXbtHTkfa9feqYuxdr3rAy++s3Zl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7dg9nY+3K2pW1K2tX1q6sXVm7snZl7drnuT3abdwcZ+3ac78ca9fu83qsXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtWvf/WqsXVm7snZl7drvfDDWrqxdWbuydmXtytqVtWvP9HCsXbvhk7F27eZPx9q1d+R8rF17py7G2vU/v/WSO2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1a/dwNtaurF1Zu7J2Ze3K2pW1K2tX1q59ntuj3cbNcdauPffLsXbtPq/H2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbv23a/G2pW1K2tX1q79zgdj7cralbUra1fWrqxdWbv2TA/H2rUbPhlr127+dKxde0fOx9q1d+pirF0Pf8rlnbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cratXs4G2tX1q6sXVm7snZl7cralbUra9c+z+3RbuPmOGvXnvvlWLt2n9dj7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF377ldj7cralbUra9d+54OxdmXtytqVtStrV9aurF17podj7doNn4y1azd/OtauvSPnY+3aO3Ux1q7veeDL7qxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrt3D2Vi7snZl7cralbUra1fWrqxdWbv2eW6Pdhs3x1m79twvx9q1+7wea1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3ad78aa1fWrqxdWbv2Ox+MtStrV9aurF1Zu7J2Ze3aMz0ca9du+GSsXbv507F27R05H2vX3qmLsXb93DtffmftytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydu0ezsbalbUra1fWrqxdWbuydmXtytq1z3N7tNu4Oc7ated+Odau3ef1WLuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2vXvvvVWLuydmXtytq13/lgrF1Zu7J2Ze3K2pW1K2vXnunhWLt2wydj7drNn461a+/I+Vi79k5djLXrT+5/xZ21K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2rV7OBtrV9aurF1Zu7J2Ze3K2pW1K2vXPs/t0W7j5jhr15775Vi7dp/XY+3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxd++5XY+3K2pW1K2vXfueDsXZl7cralbUra1fWrqxde6aHY+3aDZ+MtWs3fzrWrr0j52Pt2jt1Mdau9z7hlXfWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra9fu4WysXVm7snZl7cralbUra1fWrqxd+zy3R7uNm+OsXXvul2Pt2n1ej7Ura1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J27btfjbUra1fWrqxd+50PxtqVtStrV9aurF1Zu7J27ZkejrVrN3wy1q7d/OlYu/aOnI+1a+/UxVi7Pvm/s3Zl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtStrV9aurF1Zu7J2Ze3K2pW1K2tX1q6sXVm7dg9nY+3K2pW1K2tX1q6sXVm7snZl7drnuT3abdwcZ+3ac78ca9fu83qsXVm7snZl7cralbUra1fWrqxdWbuydmXtytqVtWvf/WqsXVm7snZl7drvfDDWrqxdWbuydmXtytqVtWvP9HCsXbvhk7F27eZPx9q1d+R8rF17py7G/w92rFXTAgAAAACAAACAVAAAohUAAFQOAAA=eJxd3dUTQFXZRnFP0N3d3d3d3d3dqYAgJYLSoXR3l9LdCkooqXQrLSkd38V3fhfvc26emTXrH1h75uz9s5/9/9cMu+OwOwRvh90pPLwbdufw8H7YXcLDRxh21/DwEYfdLTx8pGF3Dw8fedg9wsNHGXbP8PBRh90rPHy0YfcODx992J+Hh48x7C/Cw8ccdp/w8LGG3Tc8fOxh9wsPH2fYX4aHjzvs/uHh4w17QHj4+MP+Kjx8gmEPDA+fcNiDwsMnGvbg8PCJhz0kPHySYQ8ND5902F+Hh0827GHh4ZMP+5vw8CmGPTw8fMphjwgPn2rY34aHTz3s78LDpxn2yPDwaYc9Kjx8umGPDg+ffthjwsNnGPbY8PAZhz0uPHymYY8PD5952BPCw2cZ9sTw8FmHPSk8fLZhfx8ePvuwfwgPn2PYk8PD5xz2lPDwuYY9NTx87mFPCw+fZ9jTw8PnHfaM8PD5hj0zPHz+Yc8KD19g2LPDwxcc9pzw8IWGPTc8fOFhzwsPX2TY88PDFx32gvDwxYa9MDx88WEvCg9fYtiLw8OXHPaS8PClhr00PHzpYS8LD19m2MvDw5cd9orw8OWGvTI8fPlhrwoPX2HYq8PDVxz2mvDwlYa9Njx85WGvCw9fZdjrw8NXHfaP4eGrDfun8PDVh70hPHyNYW8MD19z2JvCw9ca9ubw8LWHvSU8fJ1hbw0PX3fY28LD1xv29vDw9Ye9Izx8g2HvDA/fcNi7wsM3Gvbu8PCNh70nPHyTYe8ND9902PvCwzcb9v7w8M2HfSA8fIthHwwP33LYh8LDtxr2z+HhWw/7l/DwbYZ9ODx822EfCQ/fbti/hodvP+zfwtMZeuKxYR8NriceDw/XE0+Eh+uJv4eH64l/hIfriSfDw/XEU+HheuLp8HA98Ux4uJ54NjxcTzwXHq4n/hkerif+FR6uJ54PD9cTL4SH64kXw8P1xEvh4Xri5fBwPfFKeLieeDU8XE+8Fh6uJ14PD9cTb4SH64k3w8P1xFvh4Xri7fDww4b9d3i4nvhPeLieeCc8XE+8Gx6uJ94LD9cT74eH64kPwsP1xIfh4Xrio/BwPfHf8HA98XF4uJ74JDxcT3waHq4nPgsP1xOfh4friS/Cw/XE/8LD9cSX4eF64qvwcD3xdXi4nvgmPFxPfBserie+Cw/XE9+Hh+uJH8LD9cSP4eF64qfwcD3hQOyn4HqiaaqH64m2qR6uJ7qmerie6Jvq4RcOO0JTPVxPjNhUD9cTIzXVw/XEyE31cD0xSlM9XE+M2lQP1xOjNdXD9cToTfVwPTFGUz1cT4zZVA/XE2M11cP1xNhN9XA9MU5TPVxPjNtUD9cT4zXVw/XE+E31cD0xQVM9XE9M2FQP1xMTNdXD9cTETfVwPTFJUz1cT0zaVA/XE5M11cP1xORN9XA9MUVTPVxPTNlUD9cTUzXVw/XE1E31cD0xTVM9XE9M21QP1xPTNdXD9cT0TfXw+4edoakeridmbKqH64mZmurhemLmpnq4npilqR6uJ2Ztqofridma6uF6YvameriemKOpHq475myqpzP0xNwDn6upXE/M01QP1xPzNtXD9cR8TfVwPTF/Uz1cTyzQVA/XEws21cP1xEJN9XA9sXBTPVxPLNJUD9cTizbVw/XEYk31cD2xeFM9XE8s0VQP1xNLNtXD9cRSTfVwPbF0Uz1cTyzTVA/XE8s21cP1xHJN9XA9sXxTPfz1YVdoqoe/MeyKTfVwPbFSUz1cT6zcVA/XE6s01cP1xKpN9XA9sVpTPVxPrN5UD9cTazTVw/XEmk31cD2xVlM9XE+s3VQP1xPrNNXD9cS6TfVwPbFeUz1cT6zfVA/XExs01cP1xIZN9XA9sVFTPVxPbNxUD9cTmzTVw/XEpk31cD2xWVM9XE9s3lQP1xNbNNXD9cSWTfVwPbFVUz1cT2zdVA/XE9s01cP1xLZN9XA9sV1TPVxPbN9UD9cTOzTVw/XEjuHhemKn8HA9sXN4uJ7YJTxcT+waHq4ndgsP1xO7h4friT3Cw/XEnuHhemKv8HA9sXd4uJ74eXi4nvhFeLie2Cc8XE/sGx6uJ/YLD9cTvwwP1xP7h4friQPCw/XEr8LD9cSB4eF64qDwcD1xcHi4njgkPFxPHBoerid+HR6uJw4LD9cTvwkP1xOHh4friSPCw/XEb8PD9cTvwsP1xJHh4XriqPBwPXF0eLieOCY8XE8cGx6uJ44LD9cTx4eH64kTwsP1xInh4XripPBwPfH78HA98YfwcD1xcni47jglPJ2hJ04b9tTgeuL08HA9cUZ4uJ44MzxcT5wVHq4nzg4P1xPnhIfriXPDw/XEeeHheuL88HA9cUF4uJ64MDxcT1wUHq4nLg4P1xOXhIfriUvDw/XEZeHheuLy8HA9cUV4uJ64MjxcT1wVHq4nrg4P1xPXhIfriWvDw/XEdeHheuL68HA98cfwcD3xp/BwPXFDeLieuDE8XE/cFB6uJ24OD9cTt4SH64lbw8P1xG3h4Xri9vBwPXFHeLieuDM8XE/cFR6uJ+4OD9cT94SH64l7w8P1xH3h4Xri/vBwPfFAeLieeDA8XE88FB6uJ/4cHq4n/hIericeDg/XE4+Eh+uJv4aH64m/hYfriUfDw/XEY+HheuLx8HA98UR4uJ74e3i4nvhHeLieeDI8XE88FR6uJ54OD9cTz4SH64lnw8P1xHPh4Xrin+HheuJf4eF64vnwcD3xQni4nngxPFxPvBQerideDg/XE6+Eh+uJV8PD9cRr4eF64vXwcD3xRni4nngzPFxPvBUerifeDg/XE/8OD9cT/wkP1xPvhIfriXfDw/XEe+HheuL98HA98UF4uJ74MDxcT3wUHq4n/hseric+Dg/XE5+Eh+uJT8PD9cRn4eF64vPwcD3xRXi4nvhfeLie+DI8XE98FR6uO74OT2foiW+H/Sa4nvguPFxPfB8erid+CA/XEz+Gh+uJn8LD9YQfUn4Krieatnq4nmjb6uF6omurh+uJvq0eridGaKuH64kR2+rhemKktnq4nhi5rR6uJ0Zpq4friVHb6uF6YrS2erieGL2tHq4nxmirh+uJMdvq4XpirLZ6uJ4Yu60erifGaauH64lx2+rhemK8tnq4nhi/rR6uJyZoq4friQnb6uF6YqK2eriemLitHq4nJmmrh+uJSdvq4XpisrZ6uJ6YvK0eriemaKuH64kp2+rhemKqtnq4npi6rR6uJ6Zpq4friWnb6uF6Yrq2eriemL6tHq4nZmirh+uJGdvq4XpiprZ6uJ6Yua0eridmaauH64lZ2+rhemK2tnq4npi9rR6uJ+Zoq4friTnb6uF6Yq62eriemLutHq4n5mmrh+uJedvq4XpivrZ6uJ6Yv60ericWaKuH64kF2+rhemKhtnq4nli4rR6uJxZpq4friUXb6uF6YrG2erieWLytHq4nlmirh+uJJdvq4XpiqbZ6uJ5Yuq0erieWaauH64ll2+rhemK5tnq4nli+rR6uJ1Zoq4friRXb6uF6YqW2erieWLmtHq4nVmmrh+uJVdvq4XpitbZ6uJ5Yva0erifWaKuH64k12+rhemKttnq4nli7rR6uJ9Zpq4friXXb6uF6Yr22erieWL+tHq4nNmirh+uJDdvq4Xpio7Z6uJ7YuK0eric2aauH64lN2+rhemKztnq4nti8rR6uO7Zoq6cz9MRWA9+yrVxPbN1WD9cT27TVw/XEtm31cD2xXVs9XE9s31YP1xM7tNXD9cSO4eF6YqfwcD2xc3i4ntglPFxP7Boerid2Cw/XE7uHh+uJPcLD9cSe4eF6Yq/wcD2xd3i4nvh5eLie+EV4uJ7YJzxcT+wbHq4n9gsP1xO/DA/XE/uHh+uJA8LD9cSvwsP1xIHh4XrioPBwPXFweLieOCQ8XE8cGh6uJ34dHq4nDgsP1xO/CQ/XE4eHh+uJI8LD9cRvw8P1xO/Cw/XEkeHheuKo8HA9cXR4uJ44JjxcTxwbHq4njgsP1xPHh4friRPCw/XEieHheuKk8HA98fvwcD3xh/BwPXFyeLieOCU8XE+cGh6uJ04LD9cTp4eH64kzwsP1xJnh4XrirPBwPXF2eLieOCc8XE+cGx6uJ84LD9cT54eH64kLwsP1xIXh4XriovBwPXFxeLieuCQ8XE9cGh6uJy4LD9cTl4eH64krwsP1xJXh4XriqvBwPXF1eLieuCY8XE9cGx6uJ64LD9cT14eH64k/hofriT+Fh+uJG8LD9cSN4eF64qbwcD1xc3i4nrglPFxP3BoeriduCw/XE7eHh+uJO8LD9cSd4eF64q7wcD1xd3i4nrgnPFxP3BserifuCw/XE/eHh+uJB8LDdceD4ekMPfHnYR8Krif+Eh6uJx4OD9cTj4SH64m/hofrib+Fh+uJR8PD9cRj4eF64vHwcD3xRHi4nvh7eLie+Ed4uJ54MjxcTzwVHq4nng4P1xPPhIfriWfDw/XEc+HheuKf4eF64l/h4Xri+fBwPfFCeLieeDE8XE+8FB6uJ14OD9cTr4SH64lXw8P1xGvh4Xri9fBwPfFGeLieeDM8XE+8FR6uJ94OD9cT/w4P1xP/CQ/XE++Eh+uJd8PD9cR74eF64v3wcD3xQXi4nvgwPFxPfBQerif+Gx6uJz4OD9cTn4SH64lPw8P1xGfh4Xri8/BwPfFFeLie+F94uJ74MjxcT3wVHq4nvg4P1xPfhIfriW/Dw/XEd+HheuL78HA98UN4uJ74MTxcT/wUHq4nXBj5U3A90XTVw/VE21UP1xNdVz1cT/Rd9XA9MUJXPVxPjNhVD9cTI3XVw/XEyF31cD0xSlc9XE+M2lUP1xOjddXD9cToXfVwPTFGVz1cT4zZVQ/XE2N11cP1xNhd9XA9MU5XPVxPjNtVD9cT43XVw/XE+F31cD0xQVc9XE9M2FUP1xMTddXD9cTEXfVwPTFJVz1cT0zaVQ/XE5N11cP1xORd9XA9MUVXPVxPTNlVD9cTU3XVw/XE1F31cD0xTVc9XE9M21UP1xPTddXD9cT0XfVwPTFDVz1cT8zYVQ/XHTN11dMZemKWgc/cVa4nZu2qh+uJ2brq4Xpi9q56uJ6Yo6serifm7KqH64m5uurhemLurnq4npinqx6uJ+btqofrifm66uF6Yv6uerieWKCrHq4nFuyqh+uJhbrq4Xpi4a56uJ5YpKsericW7aqH64nFuurhemLxrnq4nliiqx6uJ5bsqofriaW66uF6YumuerieWKarHq4nlu2qh+uJ5brq4Xpi+a56uJ5YoaseridW7KqH64mVuurhemLlrnq4nlilqx6uJ1btqofridW66uF6YvWuerieWKOrHq4n1uyqh+uJtbrq4Xpi7a56uJ5Yp6serifW7aqH64n1uurhemL9rnq4ntigqx6uJzbsqofriY266uF6YuOuerie2KSrHq4nNu2qh+uJzbrq4Xpi8656uJ7Yoqserie27KqH64mtuurhemLrrnq4ntimqx6uJ7btqofrie266uF6Yvuuerie2KGrHq4ndgwP1xM7hYfriZ3Dw/XELuHhemLX8HA9sVt4uJ7YPTxcT+wRHq4n9gwP1xN7hYfrib3Dw/XEz8PD9cQvwsP1xD7h4Xpi3/BwPbFfeLie+GV4uJ7YPzxcTxwQHq4nfhUericODA/XEweFh+uJg8PD9cQh4eF64tDwcD3x6/BwPXFYeLie+E14uJ44PDxcTxwRHq4nfhserid+Fx6uJ44MD9cTR4WH64mjw8P1xDHh4Xri2PBwPXFceLjuOD48naEnThz2hOB64qTwcD3x+/BwPfGH8HA9cXJ4uJ44JTxcT5waHq4nTgsP1xOnh4friTPCw/XEmeHheuKs8HA9cXZ4uJ44JzxcT5wbHq4nzgsP1xPnh4friQvCw/XEheHheuKi8HA9cXF4uJ64JDxcT1waHq4nLgsP1xOXh4friSvCw/XEleHheuKq8HA9cXV4uJ64JjxcT1wbHq4nrgsP1xPXh4friT+Gh+uJP4WH64kbwsP1xI3h4XripvBwPXFzeLieuCU8XE/cGh6uJ24LD9cTt4eH64k7wsP1xJ3h4XrirvBwPXF3eLieuCc8XE/cGx6uJ+4LD9cT94eH64kHwsP1xIPh4XriofBwPfHn8HA98ZfwcD3xcHi4nngkPFxP/DU8XE/8LTxcTzwaHq4nHgsP1xOPh4friSfCw/XE38PD9cQ/wsP1xJPh4XriqfBwPfF0eLieeCY8XE88Gx6uJ54LD9cT/wwP1xP/Cg/XE8+Hh+uJF8LD9cSL4eF64qXwcD3xcni4nnglPFxPvBoerideCw/XE6+Hh+uJN8LD9cSb4eF64q3wcD3xdni4nvh3eLie+E94uJ54JzxcT7wbHq4n3gsP1xPvh4friQ/Cw/XEh+HheuKj8HA98d/wcD3xcXi4nvgkPFx3fBqeztATnw/7WXA98UV4uJ74X3i4nvgyPFxPfBUerie+Dg/XE9+Eh+uJb8PD9cR34eF64vvwcD3xQ3i4nvgxPFxP/BQeric82PhTcD3R9NXD9UTbVw/XE11fPVxP9H31cD0xQl89XE+M2FcP1xMj9dXD9cTIffVwPTFKXz1cT4zaVw/XE6P11cP1xOh99XA9MUZfPVxPjNlXD9cTY/XVw/XE2H31cD0xTl89XE+M21cP1xPj9dXD9cT4ffVwPTFBXz1cT0zYVw/XExP11cP1xMR99XA9MUlfPVxPTNpXD9cTk/XVw/XE5H31cD0xRV89XE9M2VcP1xNT9dXD9cTUffVwPTFNXz1cT0zbVw/XE9P11cP1xPR99XA9MUNfPVxPzNhXD9cTM/XVw/XEzH31cD0xS189XE/M2lcP1xOz9dXD9cTsffVwPTFHXz1cT8zZVw/XE3P11cP1xNx99XA9MU9fPVxPzNtXD9cT8/XVw/XE/H31cD2xQF89XE8s2FcP1xML9dXD9cTCffVwPbFIXz1cTyzaVw/XE4v11cP1xOJ99XA9sURfPVxPLNlXD9cTS/XVw/XE0n31cD2xTF89XE8s21cP1xPL9dXD9cTyffVwPbFCXz1cT6zYVw/XEyv11cP1xMp99XA9sUpfPVxPrNpXD9cTq/XVw/XE6n31cD2xRl89XE+s2VcP1xNr9dXD9cTaffVwPbFOXz1cT6zbVw/XE+v11cP1xPp99XA9sUFfPVx3bNhXT2foiY0HvlFfuZ7YpK8eric27auH64nN+urhemLzvnq4ntiirx6uJ7bsq4fria366uF6Yuu+erie2KavHq4ntu2rh+uJ7frq4Xpi+756uJ7Yoa8erid2DA/XEzuFh+uJncPD9cQu4eF6YtfwcD2xW3i4ntg9PFxP7BEerif2DA/XE3uF938YiQYReJxd1/cXB2L9hnHF83xk7xmJkL1pIZItlBnK3pSkEpGKSpEGoWSrrFAySrKVvZVZZiEqq4jvOd/zvH543/cv9znXuf6Ba5qppvj/TTv+0+M/FXy68fuFh08//jPh4TOM3z88fMbxnw0Pn2n8AeHhM4//XHj4LOM/Hx4+6/gvhIfPNv7A8PDZx38xPHyO8QeFh885/uDw8LnGfyk8fO7xh4SHzzP+0PDwecd/OTz87eMPCw+fb/xXwsPnH//V8PB3jP9aePgC4w8PD3/n+CPCwxcc//Xw8IXGfyM8/F3jvxkevvD4I8PDFxn/rfDwRcd/Ozz83eOPCg9fbPzR4eGLj/9OePgS448JD19y/HfDw5ca/73w8KXHfz88fJnxPwgPX3b8seHhy40/Ljx8+fE/DA9fYfzx4eErjj8hPHyl8SeGh688/kfh4auM/3F4+HvGnxQe/t7xPwkPf9/4k8PD3z/+lPDwD4w/NTx81fGnhYevNv708PDVx58RHv7B8WeGh68x/qzw8DXH/zQ8/EPjfxYevtb4n4eHf3j82eHha48/Jzx8nfHnhoevO/688PD1xp8fHr7++F+Eh28w/oLw8A3HXxgevtH4i8LDPzL+l+HhG4//VXj4JuMvDg/fdPyvw8M/Ov6S8PCPjb80PHyz8ZeFh28+/vLw8C3G/ya8LcdvNf6K8b8NvvX434WHf3z8leHh24z/fXj4tuOvCg/fbvzV4eGfGH9NePgnx18bHr79+OvCw3cYf314+I7jbwgP32n8jeHhO4//Q3j4LuP/GB6+6/ibwsN3G39zePju428JD99j/K3h4XuOvy08fK/xt4eH7z3+jvDwfcbfGR6+7/i7wsP1xN3h4XrinvBwPXFveLieuC88XE/cHx6uJ/4UHq4n/hwericeCA/XEw+Gh+uJh8LD9cTD4eF64pHwcD3xaHi4nvhLeLie+Gt4uJ54LDxcTzweHq4nnggP1xNPhofriafCw/XE0+HheuJv4eF64u/h4XrimfBwPfFseLieeC48XE/8IzxcTzwfHq4nXggP1xP/DA/XE/8KD9cT/w4P1xMvhofriZfCw/XEy+HheuKV8HA98Wp4uJ74T3i4nvhveLieeC08XE+8Hh6uJ/4XHq4n3ggP1xNvhofriSla9XA98ZZWPVxPvLVVD9cTU7bq4XpiqlY9XE+0Vj1cT/RWPVxPTFr1cD0xdaserife1qqH64lpWvVwPTFtqx6uJ6Zr1cP1xPSteriemKFVD9cTM7bq4XpiplY9XE/M3KqH64lZWvVwPTFrqx6uJ2Zr1cP1xOyteriemKNVD9cTc7bq4XpirlY9XE/M3aqH64l5WvVwPTFvqx6uJ97eqofrifla9XA9MX+rHq4n3tGqh+uOBVr1dIaeWHDwd7bK9cRCrXq4nnhXqx6uJxZu1cP1xCKterieWLRVD9cT727Vw/XEYq16uJ5YvFUP1xNLtOrhemLJVj1cTyzVqofriaVb9XA9sUyrHq4nlm3Vw/XEcq16uJ5YvlUP1xMrtOrhemLFVj1cT6zUqofriZVb9XA9sUqrHq4n3tOqh+uJ97bq4Xrifa16uJ54f6seric+0KqH64lVW/VwPbFaqx6uJ1Zv1cP1xAdb9XA9sUarHq4n1mzVw/XEh1r1cD2xVqseric+3KqH64m1W/VwPbFOqx6uJ9Zt1cP1xHqterieWL9VD9cTG7Tq4Xpiw1Y9XE9s1KqH64mPtOrhemLjVj1cT2zSqofriU1b9XA98dFWPVxPfKxVD9cTm7Xq4Xpi81Y9XE9s0aqH64ktW/VwPbFVqx6uJ7Zu1cP1xMdb9XA9sU2rHq4ntm3Vw/XEdq16uJ74RKseric+2aqH64ntW/VwPbFDqx6uJ3Zs1cP1xE6terie2LlVD9cTu7Tq4Xpi1/BwPbFbeLie2D08XE/sER6uJ/YMD9cTe4WH64m9w8P1xD7h4Xpi3/BwPfGp8HA98enwcD2xX3i4nvhMeLie2D88XE98NjxcTxwQHq4nPhceric+Hx6uJ74QHq4nDgwP1xNfDA/XEweFh+uJg8PD9cSXwsP1xCHh4Xri0PBwPfHl8HA9cVh4uJ74Sni4nvhqeLie+Fp4uO44PDydoSe+Pv6I4HriG+HheuKb4eF64sjwcD3xrfBwPfHt8HA9cVR4uJ44OjxcT3wnPFxPHBMerie+Gx6uJ74XHq4nvh8erid+EB6uJ44ND9cTx4WH64kfhofriePDw/XECeHheuLE8HA98aPwcD3x4/BwPXFSeLie+El4uJ44OTxcT5wSHq4nTg0P1xOnhYfridPDw/XEGeHheuLM8HA9cVZ4uJ74aXi4nvhZeLie+Hl4uJ44OzxcT5wTHq4nzg0P1xPnhYfrifPDw/XEL8LD9cQF4eF64sLwcD1xUXi4nvhleLie+FV4uJ64ODxcT/w6PFxPXBIericuDQ/XE5eFh+uJy8PD9cRvwsP1xG/Dw/XEFeHheuJ34eF64srwcD3x+/BwPXFVeLieuDo8XE9cEx6uJ64ND9cT14WH64nrw8P1xA3h4XrixvBwPfGH8HA98cfwcD1xU3i4nrg5PFxP3BIeriduDQ/XE7eFh+uJ28PD9cQd4eF64s7wcD1xV3i4nrg7PFxP3BMerifuDQ/XE/eFh+uJ+8PD9cSfwsP1xJ/Dw/XEA+HheuLB8HA98VB4uJ54ODxcTzwSHq4nHg0P1xN/CQ/XE38ND9cTj4WH64nHw8P1xBPh4XriyfBwPfFUeLieeDo8XE/8LTxcd/w9PJ2hJ54d/0xwPfFceLie+Ed4uJ54PjxcT7wQHq4n/hkerif+FR6uJ/4dHq4nXgwP1xMvhYfriZfDw/XEK+HheuLV8HA98Z/wcD3x3/BwPfFaeLieeD08XE/8LzxcT7wRHq4n3gwP1xNT9OrheuItvXq4nnhrrx6uJ6bs1cP1xFS9erieaL16uJ7ovXq4npj06uF6YupePVxPvK1XD9cT0/Tq4Xpi2l49XE9M16uH64npe/VwPTFDrx6uJ2bs1cP1xEy9eriemLlXD9cTs/Tq4Xpi1l49XE/M1quH64nZe/VwPTFHrx6uJ+bs1cP1xFy9eriemLtXD9cT8/Tq4Xpi3l49XE+8vVcP1xPz9erhemL+Xj1cT7yjVw/XEwv06uF64p29erieWLBXD9cTC/Xq4XriXb16uJ5YuFcP1xOL9OrhemLRXj1cT7y7Vw/XE4v16uF6YvFePVxPLNGrh+uJJXv1cD2xVK8erieW7tXD9cQyvXq4nli2Vw/XE8v16uF6YvlePVxPrNCrh+uJFXv1cD2xUq8eridW7tXD9cQqvXq4nnhPrx6uJ97bq4friff16uF64v29erie+ECvHq4nVu3Vw/XEar16uJ5YvVcP1xMf7NXD9cQavXq4nlizVw/XEx/q1cP1xFq9erie+HCvHq4n1u7Vw/XEOr16uJ5Yt1cP1xPr9erhemL9Xj1cT2zQq4friQ179XA9sVGvHq4nPtKrh+uOjXv1dIae2HTwTXrleuKjvXq4nvhYrx6uJzbr1cP1xOa9erie2KJXD9cTW/bq4Xpiq149XE9s3auH64mP9+rhemKbXj1cT2zbq4frie169XA98YlePVxPfLJXD9cT2/fq4Xpih149XE/s2KuH64mdevVwPbFzrx6uJ3bp1cP1xK7h4Xpit/BwPbF7eLie2CM8XE/sGR6uJ/YKD9cTe4eH64l9wsP1xL7h4XriU+HheuLT4eF6Yr/wcD3xmfBwPbF/eLie+Gx4uJ44IDxcT3wuPFxPfD48XE98ITxcTxwYHq4nvhgericOCg/XEweHh+uJL4WH64lDwsP1xKHh4Xriy+HheuKw8HA98ZXwcD3x1fBwPfG18HA9cXh4uJ44IjxcT3w9PFxPfCM8XE98MzxcTxwZHq4nvhUerie+HR6uJ44KD9cTR4eH64nvhIfriWPCw/XEd8PD9cT3wsP1xPfDw/XED8LD9cSx4eF64rjwcD3xw/BwPXF8eLieOCE8XE+cGB6uJ34UHq4nfhweridOCg/XEz8JD9cTJ4eH64lTwsP1xKnh4XritPBwPXF6eLieOCM8XE+cGR6uJ84KD9cTPw0P1xM/Cw/XEz8PD9cTZ4eH64lzwsP1xLnh4XrivPBwPXF+eLie+EV4uJ64IDxcT1wYHq4nLgoP1xO/DA/XHb8KT2foiV+Pvzi4nrgkPFxPXBoericuCw/XE5eHh+uJ34SH64nfhofriSvCw/XE78LD9cSV4eF64vfh4XriqvBwPXF1eLieuCY8XE9cGx6uJ64LD9cT14eH64kbwsP1xI3h4XriD+HheuKP4eF64qbwcD1xc3i4nrglPFxP3BoeriduCw/XE7eHh+uJO8LD9cSd4eF64q7wcD1xd3i4nrgnPFxP3BserifuCw/XE/eHh+uJP4WH64k/h4friQfCw/XEg+HheuKh8HA98XB4uJ54JDxcTzwaHq4n/hIerif+Gh6uJx4LD9cTj4eH64knwsP1xJPh4XriqfBwPfF0eLie+Ft4uJ74e3i4nngmPFxPPBserieeCw/XE/8ID9cTz4eH64kXwsP1xD/Dw/XEv8LD9cS/w8P1xIvh4XripfBwPfFyeLieeCU8XE+8Gh6uJ/4THq4n/hserideCw/XE6+Hh+uJ/4WH64k3wsP1xJvh4Xpiikn1cD3xlkn1cD3x1kn1cD0x5aR6uJ6YalI9XE+0SfVwPdEn1cP1xGRSPVxPTD2pHq4n3japHq4npplUD9cT006qh+uJ6SbVw/XE9JPq4Xpihkn1cD0x46R6uJ6YaVI9XE/MPKkeridmmVQP1xOzTqqH64nZJtXD9cTsk+rhemKOSfVwPTHnpHq4nphrUj1cd8w9qd7/AWVOdNc=AQAAAACAAAAgNQAA6ggAAA==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26
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AQAAAACAAABoDwAAxQwAAA==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AQAAAACAAABQGQAA0wQAAA==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AQAAAACAAACgPQAAlgkAAA==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AQAAAACAAADtAQAADgAAAA==eJzj5BwFIwYAALvgEVY=
26
+ </AppendedData>
27
+ </VTKFile>
CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/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/Kn0p34/simulation0707_Kn0p34Ma2p6/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 0.34
13
+ variable Ma equal 2.6
14
+ variable To equal 273.0
15
+ variable Tb equal 273.0
16
+ variable theta equal 0.0
17
+ variable mfp equal ${Kn}*${L}
18
+ variable cpmfp equal 4
19
+ variable nden equal 1.0/sqrt(2.0)/${PI}/${molecular_diameter}/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
20
+ variable sos equal sqrt(${gamma}*${R}*${To})
21
+ variable vo equal ${Ma}*${sos}
22
+ variable vx equal ${vo}*cos(${theta}*2*PI/360)
23
+ variable vy equal ${vo}*sin(${theta}*2*PI/360)
24
+ variable ppc equal 30
25
+ variable xncells equal (${xmax}-${xmin})/${mfp}*${cpmfp}
26
+ variable yncells equal (${ymax}-${ymin})/${mfp}*${cpmfp}
27
+ variable Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
28
+ variable tstep equal (-${xmin}+${xmax})/${vx}/${xncells}/10/4
29
+ variable nave equal 10000
30
+ variable noutput equal 300000
31
+ clear
32
+ shell mkdir output
33
+ shell mkdir grid
34
+ shell mkdir surf
35
+ seed 7
36
+ dimension 2
37
+ global nrho ${nden}
38
+ global fnum ${Fnum}
39
+ timestep ${tstep}
40
+ global gridcut 1.0 particle/reorder 100 comm/sort yes
41
+ region 1 cylinder z 0.0 0.0 3.50 -0.5 0.5
42
+ region 2 cylinder z 0.0 0.0 2.00 -0.5 0.5
43
+ region 3 cylinder z 0.0 0.0 0.80 -0.5 0.5
44
+ boundary o o p
45
+ create_box ${xmin} ${xmax} ${ymin} ${ymax} -0.5 0.5
46
+ create_grid ${xncells} ${yncells} 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
47
+ balance_grid rcb cell
48
+ species gas.species Ar
49
+ mixture air Ar frac 1.0
50
+ mixture air Ar vstream ${vx} ${vy} 0.0 temp ${To}
51
+ collide vss air gas.vhs
52
+ collide_modify vremax 100 yes remain no nearcp yes 10
53
+ read_surf cylinder.surf
54
+ surf_collide 1 diffuse 273.0 1.0
55
+ surf_modify all collide 1
56
+ fix in emit/face air xlo ylo yhi
57
+ balance_grid rcb cell
58
+ create_particles air n 0
59
+ stats 10000
60
+ stats_style step cpu np nattempt ncoll nscoll npave nscollave
61
+ run 200000
62
+ compute 1 grid all air n nrho massrho u v w
63
+ compute 2 grid all air trot
64
+ compute 3 tvib/grid all air
65
+ compute 4 thermal/grid all air press temp
66
+ fix 1 ave/grid all 1 ${nave} ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
67
+ dump 1 grid all ${noutput} output/grid.*.dat id xc yc f_1[*]
68
+ dump_modify 1 format float %12.5g
69
+ compute 5 surf all air n press px py shx shy fx fy etot erot evib
70
+ fix 2 ave/surf all 1 ${nave} ${nave} c_5[*] ave running
71
+ dump 2 surf all ${noutput} output/surf.*.dat id v1x v1y v2x v2y f_2[*]
72
+ dump_modify 2 format float %12.5g
73
+ compute 6 lambda/grid f_1[2] f_1[8] Ar kx
74
+ dump 3 grid all ${noutput} output/lambdakn.*.dat id xc yc c_6[*]
75
+ dump_modify 3 format float %12.5g
76
+ run 100000
77
+ write_grid grid/final-grid.dat
78
+ write_surf surf/geom.surf
CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/cylinder.surf ADDED
@@ -0,0 +1,410 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ surf file from Pointwise
2
+
3
+ 200 points
4
+ 200 lines
5
+
6
+ Points
7
+
8
+ 1 0.5 0.0
9
+ 2 0.499753280182866E+000 -0.157053795390643E-001
10
+ 3 0.499013364214136E+000 -0.313952597646568E-001
11
+ 4 0.497780982301540E+000 -0.470541566592573E-001
12
+ 5 0.496057350657239E+000 -0.626666167821523E-001
13
+ 6 0.493844170297569E+000 -0.782172325201156E-001
14
+ 7 0.491143625364344E+000 -0.936906572928624E-001
15
+ 8 0.487958380969374E+000 -0.109071620698271E+000
16
+ 9 0.484291580564315E+000 -0.124344943582427E+000
17
+ 10 0.480146842838471E+000 -0.139495553019615E+000
18
+ 11 0.475528258147577E+000 -0.154508497187474E+000
19
+ 12 0.470440384477113E+000 -0.169368960122646E+000
20
+ 13 0.464888242944126E+000 -0.184062276342339E+000
21
+ 14 0.458877312841991E+000 -0.198573945317390E+000
22
+ 15 0.452413526233010E+000 -0.212889645782536E+000
23
+ 16 0.445503262094184E+000 -0.226995249869774E+000
24
+ 17 0.438153340021932E+000 -0.240876837050858E+000
25
+ 18 0.430371013501972E+000 -0.254520707875186E+000
26
+ 19 0.422163962751007E+000 -0.267913397489498E+000
27
+ 20 0.413540287137281E+000 -0.281041688926065E+000
28
+ 21 0.404508497187474E+000 -0.293892626146237E+000
29
+ 22 0.395077506187845E+000 -0.306453526826488E+000
30
+ 23 0.385256621387895E+000 -0.318711994874345E+000
31
+ 24 0.375055534815230E+000 -0.330655932661826E+000
32
+ 25 0.364484313710706E+000 -0.342273552964344E+000
33
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CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/grid/Grid_3_300000.vtu ADDED
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AQAAAACAAABoDwAAWg4AAA==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AQAAAACAAABoDwAA3gUAAA==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AQAAAACAAABoDwAAcAgAAA==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AQAAAACAAABoDwAANwYAAA==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AQAAAACAAABoDwAAGwAAAA==eJztwTEBAAAAwqD1T20JT6AAAACAlwEPaAABAQAAAACAAABoDwAAGwAAAA==eJztwTEBAAAAwqD1T20JT6AAAACAlwEPaAABAQAAAACAAABQGQAA0wQAAA==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AQAAAACAAACgPQAAlgkAAA==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AQAAAACAAADtAQAADgAAAA==eJzj5BwFIwYAALvgEVY=
34
+ </AppendedData>
35
+ </VTKFile>
CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/grid/final-grid.dat ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/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 0.34
17
+ variable Ma equal 2.6
18
+ variable To equal 273.0
19
+ variable Tb equal 273.0
20
+ variable theta equal 0.0
21
+ variable mfp equal ${Kn}*${L}
22
+ variable mfp equal 0.34*${L}
23
+ variable mfp equal 0.34*1
24
+ variable cpmfp equal 4
25
+ variable nden equal 1.0/sqrt(2.0)/${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}*${Kn})
29
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.34/${cpmfp}*${Kn})
30
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.34/4*${Kn})
31
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.34/4*0.34)
32
+ variable sos equal sqrt(${gamma}*${R}*${To})
33
+ variable sos equal sqrt(1.666666667*${R}*${To})
34
+ variable sos equal sqrt(1.666666667*208.242684766214*${To})
35
+ variable sos equal sqrt(1.666666667*208.242684766214*273)
36
+ variable vo equal ${Ma}*${sos}
37
+ variable vo equal 2.6*${sos}
38
+ variable vo equal 2.6*307.815564238681
39
+ variable vx equal ${vo}*cos(${theta}*2*PI/360)
40
+ variable vx equal 800.320467020571*cos(${theta}*2*PI/360)
41
+ variable vx equal 800.320467020571*cos(0*2*PI/360)
42
+ variable vy equal ${vo}*sin(${theta}*2*PI/360)
43
+ variable vy equal 800.320467020571*sin(${theta}*2*PI/360)
44
+ variable vy equal 800.320467020571*sin(0*2*PI/360)
45
+ variable ppc equal 30
46
+ variable xncells equal (${xmax}-${xmin})/${mfp}*${cpmfp}
47
+ variable xncells equal (6-${xmin})/${mfp}*${cpmfp}
48
+ variable xncells equal (6--5)/${mfp}*${cpmfp}
49
+ variable xncells equal (6--5)/0.34*${cpmfp}
50
+ variable xncells equal (6--5)/0.34*4
51
+ variable yncells equal (${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)/0.34*${cpmfp}
55
+ variable yncells equal (5--5)/0.34*4
56
+ variable Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
57
+ variable Fnum equal 4.47883616959053e+19*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
58
+ variable Fnum equal 4.47883616959053e+19*(6-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
59
+ variable Fnum equal 4.47883616959053e+19*(6--5)*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
60
+ variable Fnum equal 4.47883616959053e+19*(6--5)*(5-${ymin})/${ppc}/${xncells}/${yncells}
61
+ variable Fnum equal 4.47883616959053e+19*(6--5)*(5--5)/${ppc}/${xncells}/${yncells}
62
+ variable Fnum equal 4.47883616959053e+19*(6--5)*(5--5)/30/${xncells}/${yncells}
63
+ variable Fnum equal 4.47883616959053e+19*(6--5)*(5--5)/30/129.411764705882/${yncells}
64
+ variable Fnum equal 4.47883616959053e+19*(6--5)*(5--5)/30/129.411764705882/117.647058823529
65
+ variable tstep equal (-${xmin}+${xmax})/${vx}/${xncells}/10/4
66
+ variable tstep equal (--5+${xmax})/${vx}/${xncells}/10/4
67
+ variable tstep equal (--5+6)/${vx}/${xncells}/10/4
68
+ variable tstep equal (--5+6)/800.320467020571/${xncells}/10/4
69
+ variable tstep equal (--5+6)/800.320467020571/129.411764705882/10/4
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 4.47883616959053e+19
81
+ global fnum ${Fnum}
82
+ global fnum 1.07865304417639e+16
83
+ timestep ${tstep}
84
+ timestep 2.65518637541652e-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 129.411764705882 ${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 129.411764705882 117.647058823529 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 66372 child grid cells
100
+ CPU time = 0.10195 secs
101
+ create/ghost percent = 1.14993 98.8501
102
+ balance_grid rcb cell
103
+ Balance grid migrated 66244 cells
104
+ CPU time = 0.0904815 secs
105
+ reassign/sort/migrate/ghost percent = 59.0742 0.027641 8.83863 32.0596
106
+ species gas.species Ar
107
+ mixture air Ar frac 1.0
108
+ mixture air Ar vstream ${vx} ${vy} 0.0 temp ${To}
109
+ mixture air Ar vstream 800.320467020571 ${vy} 0.0 temp ${To}
110
+ mixture air Ar vstream 800.320467020571 0 0.0 temp ${To}
111
+ mixture air Ar vstream 800.320467020571 0 0.0 temp 273
112
+ collide vss air gas.vhs
113
+ collide_modify vremax 100 yes remain no nearcp yes 10
114
+ read_surf cylinder.surf
115
+ 200 lines
116
+ -0.5 0.5 xlo xhi
117
+ -0.5 0.5 ylo yhi
118
+ 0 0 zlo zhi
119
+ 0.0157073 min line length
120
+ 374 0 = cells overlapping surfs, overlap cells with unmarked corner pts
121
+ 59296 6702 374 = cells outside/inside/overlapping surfs
122
+ 374 = surf cells with 1,2,etc splits
123
+ 109.215 109.215 = cell-wise and global flow volume
124
+ CPU time = 0.101331 secs
125
+ read/check/sort/surf2grid/ghost/inout/particle percent = 22.5574 22.3147 2.56493 24.9714 27.5916 6.04824 0.140411
126
+ surf2grid time = 0.0253037 secs
127
+ map/comm1/comm2/comm3/comm4/split percent = 12.2213 21.6456 4.31843 1.63489 10.4884 18.1311
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 1906 cells
133
+ CPU time = 0.0387045 secs
134
+ reassign/sort/migrate/ghost percent = 7.3474 0.107972 22.8908 69.6539
135
+ create_particles air n 0
136
+ WARNING: Created unexpected # of particles: 453485 versus 453486 (../create_particles.cpp:346)
137
+ Created 453485 particles
138
+ CPU time = 0.0135319 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) = 1.6084 0 1.6875
144
+ grid (ave,min,max) = 3.23499 1.51379 5.26379
145
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
146
+ total (ave,min,max) = 4.86398 3.22189 6.97189
147
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
148
+ 0 0 453485 0 0 0 0 0
149
+ 10000 12.30638 492661 13421 11310 10 472416.96 10.2624
150
+ 20000 26.589061 496739 13318 11197 7 484128.05 10.31655
151
+ 30000 41.118087 497117 13356 11151 10 488501.33 10.346
152
+ 40000 55.610463 497199 13531 11430 14 490678.66 10.37125
153
+ 50000 70.732991 497264 13432 11243 7 492078.8 10.3689
154
+ 60000 84.962467 497611 13338 11138 12 492941.8 10.3694
155
+ 70000 100.04973 497557 13373 11140 12 493620.25 10.374814
156
+ 80000 114.49951 497371 13424 11236 8 494050.04 10.37155
157
+ 90000 129.26177 497461 13503 11417 10 494425 10.374322
158
+ 100000 143.56677 497432 13435 11257 7 494753.31 10.38501
159
+ 110000 157.67693 497311 13328 11090 17 494939.87 10.382755
160
+ 120000 172.97664 497797 13432 11229 12 495125.97 10.382075
161
+ 130000 187.60116 498032 13348 11192 10 495291.11 10.381362
162
+ 140000 202.09371 496009 13429 11233 9 495414.1 10.377979
163
+ 150000 216.16594 497897 13448 11337 12 495562.55 10.377887
164
+ 160000 231.66858 497137 13408 11208 8 495700.26 10.380681
165
+ 170000 246.39678 497059 13315 11084 13 495788.25 10.381906
166
+ 180000 260.92583 497183 13389 11233 9 495871.56 10.384817
167
+ 190000 274.99917 497158 13484 11307 18 495947.97 10.3876
168
+ 200000 290.34003 497655 13491 11199 10 496018.74 10.38724
169
+ Loop time of 290.341 on 128 procs for 200000 steps with 497655 particles
170
+
171
+ MPI task timing breakdown:
172
+ Section | min time | avg time | max time |%varavg| %total
173
+ ---------------------------------------------------------------
174
+ Move | 0.022616 | 12.292 | 69.648 | 439.0 | 4.23
175
+ Coll | 0.34122 | 14.296 | 104.2 | 495.9 | 4.92
176
+ Sort | 0.11872 | 2.0837 | 12.583 | 184.6 | 0.72
177
+ Comm | 57.397 | 91.453 | 102.36 | 94.0 | 31.50
178
+ Modify | 0.018901 | 0.12695 | 2.3138 | 96.4 | 0.04
179
+ Output | 0.0039565 | 0.012592 | 0.014177 | 1.4 | 0.00
180
+ Other | | 170.1 | | | 58.58
181
+
182
+ Particle moves = 99203747845 (99.2B)
183
+ Cells touched = 104040844921 (104B)
184
+ Particle comms = 217324160 (217M)
185
+ Boundary collides = 0 (0K)
186
+ Boundary exits = 22214808 (22.2M)
187
+ SurfColl checks = 82216301 (82.2M)
188
+ SurfColl occurs = 2077448 (2.08M)
189
+ Surf reactions = 0 (0K)
190
+ Collide attempts = 2934313375 (2.93B)
191
+ Collide occurs = 2263210097 (2.26B)
192
+ Reactions = 0 (0K)
193
+ Particles stuck = 0
194
+ Axisymm bad moves = 0
195
+
196
+ Particle-moves/CPUsec/proc: 2.66938e+06
197
+ Particle-moves/step: 496019
198
+ Cell-touches/particle/step: 1.04876
199
+ Particle comm iterations/step: 1
200
+ Particle fraction communicated: 0.00219068
201
+ Particle fraction colliding with boundary: 0
202
+ Particle fraction exiting boundary: 0.000223931
203
+ Surface-checks/particle/step: 0.000828762
204
+ Surface-collisions/particle/step: 2.09412e-05
205
+ Surf-reactions/particle/step: 0
206
+ Collision-attempts/particle/step: 0.0295787
207
+ Collisions/particle/step: 0.0228138
208
+ Reactions/particle/step: 0
209
+
210
+ Particles: 3887.93 ave 23440 max 0 min
211
+ Histogram: 82 14 8 4 4 8 4 0 2 2
212
+ Cells: 518.531 ave 519 max 518 min
213
+ Histogram: 60 0 0 0 0 0 0 0 0 68
214
+ GhostCell: 13340.3 ave 24514 max 724 min
215
+ Histogram: 22 8 12 10 17 3 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) = 1.6875 0 3.375
246
+ grid (ave,min,max) = 3.23499 1.51379 5.26379
247
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
248
+ total (ave,min,max) = 5.11741 3.39595 7.14645
249
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
250
+ 200000 0 497655 13491 11199 0 0 0
251
+ 210000 24.254987 497187 13364 11200 13 496726.49 10.4259
252
+ 220000 48.882551 497536 13507 11275 12 497213.01 10.45085
253
+ 230000 74.432423 496724 13347 11198 18 497329.47 10.4543
254
+ 240000 98.340519 497647 13406 11196 12 497360.43 10.4464
255
+ 250000 123.59002 497761 13458 11295 14 497554.62 10.45406
256
+ 260000 148.31776 497401 13468 11348 13 497493.43 10.44295
257
+ 270000 172.44706 497353 13531 11289 12 497494.65 10.4303
258
+ 280000 197.65879 496886 13513 11399 14 497461.65 10.424875
259
+ 290000 221.81488 497535 13607 11409 9 497417.92 10.420567
260
+ 300000 246.71967 497533 13480 11298 2 497471.21 10.41499
261
+ Loop time of 246.72 on 128 procs for 100000 steps with 497533 particles
262
+
263
+ MPI task timing breakdown:
264
+ Section | min time | avg time | max time |%varavg| %total
265
+ ---------------------------------------------------------------
266
+ Move | 0.011999 | 6.204 | 35.108 | 310.7 | 2.51
267
+ Coll | 0.17046 | 7.2087 | 52.948 | 352.7 | 2.92
268
+ Sort | 0.067087 | 1.0618 | 6.4033 | 131.1 | 0.43
269
+ Comm | 34.282 | 51.335 | 57.366 | 64.0 | 20.81
270
+ Modify | 2.3917 | 17.081 | 91.942 | 478.6 | 6.92
271
+ Output | 0.041071 | 0.042688 | 0.046147 | 0.5 | 0.02
272
+ Other | | 163.8 | | | 66.39
273
+
274
+ Particle moves = 49747120926 (49.7B)
275
+ Cells touched = 52170801423 (52.2B)
276
+ Particle comms = 108878875 (109M)
277
+ Boundary collides = 0 (0K)
278
+ Boundary exits = 11130689 (11.1M)
279
+ SurfColl checks = 41293222 (41.3M)
280
+ SurfColl occurs = 1041499 (1.04M)
281
+ Surf reactions = 0 (0K)
282
+ Collide attempts = 1478018021 (1.48B)
283
+ Collide occurs = 1139991496 (1.14B)
284
+ Reactions = 0 (0K)
285
+ Particles stuck = 0
286
+ Axisymm bad moves = 0
287
+
288
+ Particle-moves/CPUsec/proc: 1.57527e+06
289
+ Particle-moves/step: 497471
290
+ Cell-touches/particle/step: 1.04872
291
+ Particle comm iterations/step: 1
292
+ Particle fraction communicated: 0.00218865
293
+ Particle fraction colliding with boundary: 0
294
+ Particle fraction exiting boundary: 0.000223745
295
+ Surface-checks/particle/step: 0.000830063
296
+ Surface-collisions/particle/step: 2.09359e-05
297
+ Surf-reactions/particle/step: 0
298
+ Collision-attempts/particle/step: 0.0297106
299
+ Collisions/particle/step: 0.0229157
300
+ Reactions/particle/step: 0
301
+
302
+ Particles: 3886.98 ave 23675 max 0 min
303
+ Histogram: 82 14 8 3 6 7 4 0 2 2
304
+ Cells: 518.531 ave 519 max 518 min
305
+ Histogram: 60 0 0 0 0 0 0 0 0 68
306
+ GhostCell: 13340.3 ave 24514 max 724 min
307
+ Histogram: 22 8 12 10 17 3 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 = 66372
316
+ CPU time = 0.0101058 secs
317
+ write_surf surf/geom.surf
318
+ surf elements = 200
319
+ CPU time = 0.00274789 secs
CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/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/Kn0p34/simulation0707_Kn0p34Ma2p6/output/lambdakn.300000.dat ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/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 0.00414 0.043716 -0.043711 0.00068666 1.4665e-05 0.0009335 -0.00068635 2.5448e-05 2.5283 0 0
11
+ 129 -0.31871 0.38526 -0.30645 0.39508 0.08687 0.98191 0.61393 -0.76631 0.14075 0.11276 0.011854 -0.010265 98.094 0 0
12
+ 2 0.49975 -0.015705 0.49901 -0.031395 0.00395 0.041456 -0.04141 0.0019528 -6.2014e-05 -0.001315 -0.00065141 1.0018e-05 1.7428 0 0
13
+ 130 -0.30645 0.39508 -0.29389 0.40451 0.08125 0.92596 0.55597 -0.74048 0.14385 0.10801 0.010992 -0.0099344 95.219 0 0
14
+ 3 0.49901 -0.031395 0.49778 -0.047054 0.00363 0.038455 -0.038337 0.0030172 6.1333e-05 0.00077931 -0.0006012 5.9632e-05 1.7774 0 0
15
+ 131 -0.29389 0.40451 -0.28104 0.41354 0.07874 0.89048 0.51203 -0.72854 0.15163 0.10656 0.010424 -0.0097696 93.321 0 0
16
+ 4 0.49778 -0.047054 0.49606 -0.062667 0.004 0.043386 -0.043124 0.004761 -0.00010757 -0.00097439 -0.00067906 5.9477e-05 2.9925 0 0
17
+ 132 -0.28104 0.41354 -0.26791 0.42216 0.07615 0.86832 0.47673 -0.72575 0.15795 0.10375 0.0099691 -0.00977 91.897 0 0
18
+ 5 0.49606 -0.062667 0.49384 -0.078217 0.00363 0.038945 -0.038557 0.0054875 2.8609e-05 0.00020102 -0.00060518 8.9351e-05 1.8375 0 0
19
+ 133 -0.26791 0.42216 -0.25452 0.43037 0.0722 0.81655 0.42665 -0.69622 0.15067 0.092332 0.0090681 -0.0094855 82.632 0 0
20
+ 6 0.49384 -0.078217 0.49114 -0.093691 0.00375 0.03747 -0.036912 0.0064422 0.00020346 0.0011658 -0.00057659 0.0001195 1.9189 0 0
21
+ 134 -0.25452 0.43037 -0.24088 0.43815 0.0693 0.78011 0.38651 -0.67763 0.15314 0.087347 0.0084764 -0.0092717 82.445 0 0
22
+ 7 0.49114 -0.093691 0.48796 -0.10907 0.00341 0.037046 -0.036276 0.0075124 0.00030861 0.0014902 -0.00056495 0.00014141 2.1084 0 0
23
+ 135 -0.24088 0.43815 -0.227 0.4455 0.06682 0.75092 0.35138 -0.66364 0.15866 0.084008 0.0080114 -0.0091045 77.616 0 0
24
+ 8 0.48796 -0.10907 0.48429 -0.12434 0.00364 0.037847 -0.036801 0.0088352 0.0003165 0.0013183 -0.00057307 0.00015948 2.0718 0 0
25
+ 136 -0.227 0.4455 -0.21289 0.45241 0.06195 0.6965 0.30642 -0.62548 0.16627 0.081456 0.0074247 -0.0085451 74.799 0 0
26
+ 9 0.48429 -0.12434 0.48015 -0.1395 0.00345 0.036024 -0.034747 0.0095057 -6.4352e-05 -0.00023523 -0.00054679 0.00014561 1.8873 0 0
27
+ 137 -0.21289 0.45241 -0.19857 0.45888 0.05857 0.66205 0.27244 -0.60339 0.15352 0.069316 0.0066907 -0.0083889 66.701 0 0
28
+ 10 0.48015 -0.1395 0.47553 -0.15451 0.00323 0.032746 -0.031298 0.0096286 0.00012584 0.00040905 -0.00048964 0.00015766 2.1479 0 0
29
+ 138 -0.19857 0.45888 -0.18406 0.46489 0.05555 0.62497 0.23917 -0.5774 0.15153 0.062764 0.0061367 -0.0080835 65.692 0 0
30
+ 11 0.47553 -0.15451 0.47044 -0.16937 0.00311 0.032354 -0.03061 0.01048 -9.6102e-05 -0.00028069 -0.00048231 0.00016021 1.3482 0 0
31
+ 139 -0.18406 0.46489 -0.16937 0.47044 0.05378 0.60293 0.21312 -0.56401 0.15333 0.057939 0.005756 -0.007949 63.592 0 0
32
+ 12 0.47044 -0.16937 0.46489 -0.18406 0.00296 0.031078 -0.029072 0.010985 0.00030908 0.00081796 -0.00045179 0.0001854 2.6695 0 0
33
+ 140 -0.16937 0.47044 -0.15451 0.47553 0.04917 0.54647 0.17701 -0.517 0.15003 0.051366 0.0051369 -0.0073139 56.441 0 0
34
+ 13 0.46489 -0.18406 0.45888 -0.19857 0.00318 0.033218 -0.030689 0.012712 0.000758 0.00183 -0.00047014 0.00022841 1.9298 0 0
35
+ 141 -0.15451 0.47553 -0.1395 0.48015 0.04745 0.52816 0.1553 -0.50481 0.1549 0.047654 0.0048724 -0.0071807 56.281 0 0
36
+ 14 0.45888 -0.19857 0.45241 -0.21289 0.00267 0.028791 -0.02624 0.011848 0.0013742 0.0030436 -0.00039058 0.00023391 0.87935 0 0
37
+ 142 -0.1395 0.48015 -0.12434 0.48429 0.0441 0.49469 0.13054 -0.47716 0.15183 0.041536 0.0044352 -0.0068425 52.933 0 0
38
+ 15 0.45241 -0.21289 0.4455 -0.227 0.00294 0.029485 -0.026479 0.012972 0.0010077 0.0020569 -0.00040008 0.00023606 1.6283 0 0
39
+ 143 -0.12434 0.48429 -0.10907 0.48796 0.0403 0.45003 0.10506 -0.43759 0.13917 0.033411 0.0038361 -0.0063486 48.828 0 0
40
+ 16 0.4455 -0.227 0.43815 -0.24088 0.00291 0.028676 -0.025343 0.013418 0.0019937 0.0037655 -0.00036675 0.00026991 1.461 0 0
41
+ 144 -0.10907 0.48796 -0.093691 0.49114 0.03818 0.42371 0.085924 -0.41491 0.14148 0.029298 0.0035718 -0.0060569 48.968 0 0
42
+ 17 0.43815 -0.24088 0.43037 -0.25452 0.00287 0.02888 -0.025086 0.014309 0.0023053 0.0040416 -0.00035783 0.00028824 2.1662 0 0
43
+ 145 -0.093691 0.49114 -0.078217 0.49384 0.03661 0.40359 0.069389 -0.39758 0.12713 0.022189 0.0030869 -0.0058964 42.591 0 0
44
+ 18 0.43037 -0.25452 0.42216 -0.26791 0.00281 0.028343 -0.024166 0.014809 0.0036207 0.0059085 -0.00032272 0.00032542 2.0433 0 0
45
+ 146 -0.078217 0.49384 -0.062667 0.49606 0.03485 0.38585 0.054366 -0.382 0.13528 0.019253 0.0029788 -0.0056977 41.628 0 0
46
+ 19 0.42216 -0.26791 0.41354 -0.28104 0.00255 0.025238 -0.021094 0.013856 0.0032462 0.0049419 -0.00028035 0.00029527 2.3315 0 0
47
+ 147 -0.062667 0.49606 -0.047054 0.49778 0.03289 0.35981 0.039483 -0.35764 0.12942 0.014288 0.002653 -0.0053931 40.173 0 0
48
+ 20 0.41354 -0.28104 0.40451 -0.29389 0.00252 0.025163 -0.020587 0.014469 0.0044358 0.0063114 -0.00025369 0.0003264 1.4019 0 0
49
+ 148 -0.047054 0.49778 -0.031395 0.49901 0.03065 0.32894 0.025808 -0.32793 0.12785 0.010062 0.0024136 -0.0049928 37.285 0 0
50
+ 21 0.40451 -0.29389 0.39508 -0.30645 0.00309 0.029723 -0.023769 0.017846 0.0057607 0.0076726 -0.00028286 0.00040083 2.1177 0 0
51
+ 149 -0.031395 0.49901 -0.015705 0.49975 0.02812 0.30528 0.014381 -0.30494 0.11579 0.0054605 0.0020446 -0.0047041 31.972 0 0
52
+ 22 0.39508 -0.30645 0.38526 -0.31871 0.00319 0.030232 -0.023594 0.018902 0.0063323 0.007904 -0.00027114 0.00042106 1.9227 0 0
53
+ 150 -0.015705 0.49975 0 0.5 0.02631 0.28408 0.0044621 -0.28404 0.10942 0.0017188 0.0017887 -0.0044345 29.486 0 0
54
+ 23 0.38526 -0.31871 0.37506 -0.33066 0.00282 0.026632 -0.020251 0.017296 0.0074941 0.0087745 -0.00020038 0.0004095 2.0993 0 0
55
+ 151 0 0.5 0.015705 0.49975 0.02545 0.27135 -0.0042621 -0.27131 0.11305 -0.0017759 0.0017088 -0.0042895 30.64 0 0
56
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176
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177
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178
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179
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180
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181
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182
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183
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184
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185
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186
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187
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188
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189
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190
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191
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192
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193
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194
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195
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196
+ 115 -0.45241 0.21289 -0.4455 0.227 0.1336 1.5433 1.3859 -0.67895 0.063566 0.12975 0.022767 -0.0086263 147.72 0 0
197
+ 116 -0.4455 0.227 -0.43815 0.24088 0.13213 1.5303 1.3524 -0.71606 0.066718 0.12601 0.02229 -0.0092681 157.39 0 0
198
+ 117 -0.43815 0.24088 -0.43037 0.25452 0.12682 1.4617 1.2696 -0.72419 0.074878 0.13128 0.021119 -0.0093132 147.08 0 0
199
+ 118 -0.43037 0.25452 -0.42216 0.26791 0.1251 1.4461 1.233 -0.75557 0.08066 0.13162 0.020634 -0.0098005 143.65 0 0
200
+ 119 -0.42216 0.26791 -0.41354 0.28104 0.12216 1.4036 1.1731 -0.77058 0.089271 0.1359 0.019828 -0.0099691 136.83 0 0
201
+ 120 -0.41354 0.28104 -0.40451 0.29389 0.11696 1.3441 1.0997 -0.77287 0.093288 0.13274 0.018738 -0.010055 132.79 0 0
202
+ 121 -0.40451 0.29389 -0.39508 0.30645 0.11622 1.3332 1.0661 -0.80046 0.1022 0.13611 0.018351 -0.010435 132.12 0 0
203
+ 122 -0.39508 0.30645 -0.38526 0.31871 0.11104 1.2787 0.99791 -0.79947 0.11292 0.14094 0.017448 -0.010344 127.92 0 0
204
+ 123 -0.38526 0.31871 -0.37506 0.33066 0.10838 1.237 0.94059 -0.80334 0.11199 0.13112 0.016533 -0.010559 120.97 0 0
205
+ 124 -0.37506 0.33066 -0.36448 0.34227 0.10328 1.183 0.87497 -0.79616 0.11755 0.12919 0.01559 -0.010476 119.23 0 0
206
+ 125 -0.36448 0.34227 -0.35355 0.35355 0.10029 1.1472 0.8238 -0.79832 0.12756 0.13163 0.014943 -0.010472 113.59 0 0
207
+ 126 -0.35355 0.35355 -0.34227 0.36448 0.09739 1.1138 0.7751 -0.79984 0.13297 0.12886 0.014263 -0.010539 109.23 0 0
208
+ 127 -0.34227 0.36448 -0.33066 0.37506 0.09359 1.0637 0.71588 -0.78674 0.14014 0.12752 0.013446 -0.010355 105.88 0 0
209
+ 128 -0.33066 0.37506 -0.31871 0.38526 0.08831 1.0085 0.65495 -0.76685 0.13513 0.11541 0.01241 -0.010232 102.54 0 0
CylinderKnMa/Kn0p34/simulation0707_Kn0p34Ma2p6/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