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  1. .gitattributes +6 -0
  2. CylinderKnMa/Kn0p26/simulation0530_Kn0p26Ma4p9/output/grid.300000.dat +3 -0
  3. CylinderKnMa/Kn0p26/simulation0531_Kn0p26Ma5p0/output/grid.300000.dat +3 -0
  4. CylinderKnMa/Kn0p26/simulation0532_Kn0p26Ma5p1/output/grid.300000.dat +3 -0
  5. CylinderKnMa/Kn0p26/simulation0533_Kn0p26Ma5p2/output/grid.300000.dat +3 -0
  6. CylinderKnMa/Kn0p26/simulation0534_Kn0p26Ma5p3/output/grid.300000.dat +3 -0
  7. CylinderKnMa/Kn0p26/simulation0535_Kn0p26Ma5p4/output/grid.300000.dat +3 -0
  8. CylinderKnMa/Kn0p28/simulation0577_Kn0p28Ma4p6/Lambda/Lambda_3_300000.vtu +27 -0
  9. CylinderKnMa/Kn0p28/simulation0577_Kn0p28Ma4p6/output/lambdakn.300000.dat +0 -0
  10. CylinderKnMa/Kn0p28/simulation0577_Kn0p28Ma4p6/output/surf.300000.dat +209 -0
  11. CylinderKnMa/Kn0p28/simulation0577_Kn0p28Ma4p6/surf/Surf_300000.vtu +38 -0
  12. CylinderKnMa/Kn0p28/simulation0577_Kn0p28Ma4p6/surf/geom.surf +610 -0
  13. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/Grid.pvd +9 -0
  14. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/Lambda.pvd +9 -0
  15. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/Lambda/Lambda_0_300000.vtu +0 -0
  16. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/Lambda/Lambda_1_300000.vtu +0 -0
  17. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/Lambda/Lambda_2_300000.vtu +0 -0
  18. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/Lambda/Lambda_300000.pvtu +21 -0
  19. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/Lambda/Lambda_3_300000.vtu +27 -0
  20. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/Surf.pvd +9 -0
  21. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/config.txt +78 -0
  22. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/cylinder.surf +410 -0
  23. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/gas.species +14 -0
  24. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/gas.vhs +9 -0
  25. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/grid/Grid_0_300000.vtu +0 -0
  26. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/grid/Grid_1_300000.vtu +0 -0
  27. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/grid/Grid_2_300000.vtu +0 -0
  28. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/grid/Grid_300000.pvtu +29 -0
  29. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/grid/Grid_3_300000.vtu +0 -0
  30. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/grid/final-grid.dat +0 -0
  31. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/log.sparta +319 -0
  32. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/mir.txt +3 -0
  33. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/output/lambdakn.300000.dat +0 -0
  34. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/output/surf.300000.dat +209 -0
  35. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/runmpirun128.sh +18 -0
  36. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/runmpirun64.sh +18 -0
  37. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/slurm-28429259.out +205 -0
  38. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/surf/Surf_300000.vtu +38 -0
  39. CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/surf/geom.surf +610 -0
  40. CylinderKnMa/Kn0p28/simulation0579_Kn0p28Ma4p8/Grid.pvd +9 -0
  41. CylinderKnMa/Kn0p28/simulation0579_Kn0p28Ma4p8/Lambda.pvd +9 -0
  42. CylinderKnMa/Kn0p28/simulation0579_Kn0p28Ma4p8/Lambda/Lambda_0_300000.vtu +0 -0
  43. CylinderKnMa/Kn0p28/simulation0579_Kn0p28Ma4p8/Lambda/Lambda_1_300000.vtu +0 -0
  44. CylinderKnMa/Kn0p28/simulation0579_Kn0p28Ma4p8/Lambda/Lambda_2_300000.vtu +0 -0
  45. CylinderKnMa/Kn0p28/simulation0579_Kn0p28Ma4p8/Lambda/Lambda_300000.pvtu +21 -0
  46. CylinderKnMa/Kn0p28/simulation0579_Kn0p28Ma4p8/Lambda/Lambda_3_300000.vtu +27 -0
  47. CylinderKnMa/Kn0p28/simulation0579_Kn0p28Ma4p8/Surf.pvd +9 -0
  48. CylinderKnMa/Kn0p28/simulation0579_Kn0p28Ma4p8/config.txt +78 -0
  49. CylinderKnMa/Kn0p28/simulation0579_Kn0p28Ma4p8/cylinder.surf +410 -0
  50. CylinderKnMa/Kn0p28/simulation0579_Kn0p28Ma4p8/gas.species +14 -0
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VTLcCrX2T36dvymbsuNviiZbDbBo9FHDyxh3mtvN+mR0yzabT67yuqboqMjanP9NsMEuRPJuU7QvamFtanuLjrs8h0YFHr9dEcBg7eJvD5/YqDpUY359MG2Vu4/fjp6LsuBT1ME6qe4bL2NWXhq4/beGStb/l6nKREmOf2FTpEBisRI0SE19uCXP3OZZ21/GVKZ6dz1tWpEz2Bf6XK815xN0g3GRXy6PcMaX9eV4qFHK+8ZtZpwp99blnkBqtSjVfYmWXUqXE2UNkqJGa66p4tp46ve7qUZOWq1P+scKrxls0aLVtTktykwaNvNpxULCHTw+iVcaL+/nkbjFjNHVUk86G7et0VRRQq/O74VEPAc39NkdAeR+kaakdAuqp4xeuXykk53OH+icihVQW2Gz9+JaQhja7bD8yLiTZI3JsnbTo7ktWFztdi2Zk+dxs1aKw5Hb747oiqgj1220aKiK++exlRHRkXHPg7pCIHnRkTEXYaJPB9c9uFsnalBLrmjv2VJua/WSB8cVkbmQoS0BM2YNJjhuLxNT+4rvvx17x/H10KDWptWZvvA4NuMkeUqtDO8SZHl84kvl7SehHY3hFaK5k/m4SRtfoHJ2jc3S+0M7ljugZPS+OngPmALnoFt3+V90+87RJdwpFn+jz3/Qpd0GH6PDvdmijVx+8wgm9obc/05v87ugKXS2sK/md0Q/6+X0/uyZ1Y9/moJOl3on8juhhqfTQ0HzF5U4s3Bebe2TMcOpzPxZZ8aqWB31iwRGOcIQjHOEIRzjCEY5whCMc4QhHOMIRjnCEIxzhCEc4whGOcIQjHOEIRzjCEY5whCMc4QhHOMIRjnCEIxzhCEc4whGOcITjknX8CZxzjKs=AQAAAACAAAAoUwAAWwIAAA==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AQAAAACAAAAoUwAApDUAAA==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AgAAAACAAACMAgAAZRsAABIBAAA=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AQAAAACAAAAoUwAAzQ0AAA==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AQAAAACAAABlCgAAGgAAAA==eJztwSEBAAAAwyC9/oVf4hIoAAA4G4r2XY4=
26
+ </AppendedData>
27
+ </VTKFile>
CylinderKnMa/Kn0p28/simulation0577_Kn0p28Ma4p6/output/lambdakn.300000.dat ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0577_Kn0p28Ma4p6/output/surf.300000.dat ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ITEM: TIMESTEP
2
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AQAAAACAAABABgAABgYAAA==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AQAAAACAAABABgAAAwYAAA==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AQAAAACAAABABgAAMgYAAA==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AQAAAACAAABABgAANgYAAA==eJwtkHs0FIgex1t59CBDm2IrqfWoQZlBZPhpPBrcSdajmMowS5L1HvLKO1PIINKsx7z1Jpas7vbL3pREKNeaFotiscYjqzbRve05+9f3nO85n3O+n2+X+vZn+XVaILfwaW07sg2CTkU9nWhQBsLztnK77/aA9lmjyTH+bpil1KQxXpmATnF0w7Ywc7CKLlbpX7EGCm3T+I8l9lCV4/SiQMEGnvJXM+NM7WFH7Q9ZLLIDbNbtaR967gQjlk/izcYPwpfJanzWPkdoHlngXag5BEY9va8lVq6wRTM0yDnEBS5dOtI/tdkDGD6GHMtf3EAkI47uUfKEM34xhXnj30DrYCu/ieMFoiNMNxnZG66yCdnDCn7APVN57mY3A4b6OggpJidhtC7IKzaVCaNKGtdPb2aByyr5yvJtFqwVP7ojlwdD/Ggnm70zDAxjRgO4Nz6nS3KxGycc3kKlglJmJNS9fcbMo8XC3bW6qwzbY6GItGBqtC0Omn78vcbZ+CzIm0biX5okwbURxrH9QymwlOd9+bh6Gryitb0jOKTDb0lPCRq0TCg41FybOpEJ/1PKWKV94DwQujS/VfTigLM+W4G3JhcO79E5k3oqFxS9rDK8LuZDnHjp+V5XLkSP2NO09hXCAP8dw8ajCBgO13/iNBaDjmX7UuejyyDT+xTgVlAKFHJL5J2AUlD77efm+ZkySPFzSg0Zvwori+vWz6iUw2o7yCNsrwBVBWKOlqwSnHeaZ+T/UQWlKpO7ozl8GLpt3OMbLIBLt5ZJW3YJ4b5R4jCrVgi76w8aaFuLAJ0M3W6/FwF4ZysHysRwY6aw03tBDJRNkV0L1ZJ//CXAvntaQmiTAGz92vFDhhRab212sO6RQgbXmKlwTwrme3MG41WrYW3U2HTF575lmGez5C+FcM487yhbCp67/iQvNkuAf/0XEwWWBBI67IOWP4rhvbWdX7mZGA5wF3unbopg36lG4p8tQlh56F1p3y8AspSZXz/JB69t0eSBtCowerFSnrFcDl+nK39/oIAH4+xHel/RrkC0RR3RZFcJhPi+L8ie4ILvMLF5kXcJBOcjAgbP5oCD2XZXX2IqWPyRN5vrxoa++eu3d8qPgDSpoveK5AROMzd0fBUVjWEHqj+Nh6bhSY3lCH2b83gjfTxmJi4fiaj6mONYiI1Zyd31viUYW+qbFUgsQ5+UO42BqVexi5blXBtVgXOSOb6MXYVU/8SPMT18/Gls6onBBwHy9L8IDZUJMfhdQt7bDhHetDvKuItiXDlcrB1BlCC1h5LmdE6CuqbWM5c3SNHUKhP9O6SYUqNnZfpaireG7+k9PiPFRI/7/kp/SVHoMEzjt0hxpCnve50QKaafoFfW8aRYP+3CjPnMizqjwjfOSHDATUfE9pKg7Z5Ps5x1EiS96U88HynGqdVPbXJIYiSHh/I/lIvwQiNr6s60EDMHnMqEx4X4mLSiOd8nwNZPdUlva/nYGT+3UaW7CruyDC7oj1WizDbh2DWLCiSbV64ZpZTjsYjedS/f8/A/cxpm+kVlmDP897AydJRokD9SSlFxXM/TTrEEfx70vS+nFuNh55KAAbUipDebFK5/zkWF4AeZVVZcpKuvc+1pz8fSnrbfN7nnI2ly9vOjF1BTmHxw/VoOnvZpVE94lo30X7HuhTgLSeSUh3RuBoa6HvXuVUrH74JeMugTqZgWJu9npZzDk7kdmp79Sei/+xnhSfNZXFW91Uo1Nw41d3a98RiOwRxBIqHaKgaFi266m/yicL2fXDlOEI7u9GLWslMoegzeaxjmhyDJNLjktX8QRoxZEqfrv8WjFF4B4WIgZoepm30ZzERRzY7OY+YnUCsQ/ktiMZCoJpjdeMsHP7rTkq2KvNFrrv3NxYM+GMu3pW/d64kPj7ssdRq6Y/uOF+1bEt3RoP4HUlD3YdRh7TWhPziErw4tvZN2O6OFqYXk9AYaLpepXCGqOyJZ17W4bw0VF5q9qbaVVHyg6toyYUzFEE+dvg/Hqbhk5EiZrLFFF+pEi6/efoxvUNK2ebgflRNGhwSdlnifcNFMpmaBjfT5pmtaZvgvT4Gawi4DXCz/Zt9CwxY0jmQ9Ufn31INwxZCajrYv4P8y/hF+AQAAAACAAABABgAA4QMAAA==eJwtVH9M1GUYT4J04lo6RlKO0DG4Hx7Hl8sQTPlwFnQoS2ASEDA4qYDR7cBTDg3Gjw5PBTw47jRNUmommxndmMOk1jCdPzfxx6ioOZfFGEWyRMfU7Pvyed9/nj2/Ps/zvO/7fE79++Sm86IJ9Smrir/ti8fahaOf258o+CtrMNIVquCU8FfE4607O8JOzjfi7IymcF+zDsv7a8o7rypIGriw/fvbBhywLWn5IUOPe1+e35BoicWRl4y/RZ834FyUGjiiw+7Ukj+urYjF++Ici5H2OGxMFJ5YnExXC8Tp8OmPwmHELedEjHJBg55/VMBaBUH6XeE/T8XDv35v1fiZBATnPm8IFBnw4fijvunrCRDtpd9JxDbv0uDcjtdROeTwLr2bjDn4/hTOtTYV6lSTWT+tR7Uw9FuYH5RO/EgLxmYbKode3YiCsjW3396cBXEtluhsqNNdOhqSjRuZ1hfyknKgogxGhuRDoC4czef9pBdwjp4iFO4bntFEl0h7Ke9zzRb2OVLGPqLK2YfnA8y1Z66gPlgFkziXbbwvqx0HP1HP0Wpki0RfDfPvORj3rAOiXOFoLV4RjdXUEs9ax/iJOjwjzv16PFCfb7i0gX1taMTVK+p53Ei8qSbWiWihXtzCOYY/Zlyri/X6WhmndRPX4Wa9E7s5/4E9rONqYz/2ds7V0ME+pzuI94aHeA89nPMXKXs6aV/cxThbF/UQL/3NXtbf5WX9sG7q33UzzuRjXoaP/igf/eNSzkh51ke8I1L3+akH/MwbkvpBP3Hn+RlX5Cf+cYkfkPUWybhvpP2/bub/2k3/gOxzUvY5K+fp9cp3lHKetNu75HzyHno7mT9fyose+os9fKe7Hbz339sZb25j3Mtt/K9Jeynf3cN3crrl/3Qzf6qV7/iaizihLv6fMy3c++FmaEXgumbiO5vwhfj+EY2Uk/WMX17PuGU7Oc94HfUrtdgp1jR8O/XV24hrdnA/ttbwf+irua+n7axTZeOevSj3YrKCcU/LWc/yHv+rs4z7NVHKuadLiZ9RIve9iP7FxcT/Kh8qKY3N+vOQJ4jsz814rLJJZmUO6322ifygy8bW8s6/P0rJxKb2/bYlXgvSBDEeT6N0p9Gek4oIQUxWM/szriOeNZm8FJcMQVuHv15NXrpmgqCp4AcKFpxYVlA2ZiJ/qjw8V27VShw7pBJiQCd5Us/4XA1Udn2u6ZYO4jp33IyhPVyLwGGVMEO17H9/HPt+qidvnTai90214TANYhVRUQuzoOVDBvLconiMrBAMuBKC/trfUciH940QrDewIIHzBCnkf4MR/wMbDcLRAQAAAACAAABABgAAFQAAAA==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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AQAAAACAAAAoUwAAWwIAAA==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AgAAAACAAACMAgAAZRsAABIBAAA=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AQAAAACAAAAoUwAAzQ0AAA==eJw13KG7OWCYJuCzu3bHzJpdM2tmzazZNTNm1l6XIAiCIAiCIAiCIAiCIAiCIAiCIAgnCIIgCIIgCIIgCIJwgiAIgiAIgrDh3L+v3H/D977P8wa+fl+QIYYZYZQxxplgkimmmWGWOeZZYJEllllhlTXW2WCTLbbZYZc99jngkCOOOeE3p5xxzgWXXHHNDbfccc8DjzzxzB9eeOWNdz745Itvfvj1H34JMMgQw4wwyhjjTDDJFNPMMMsc8yywyBLLrLDKGutssMkW2+ywyx77HHDIEcec8JtTzjjngkuuuOaGW+6454FHnnjmDy+88sY7H3zyxTc//PqPvwQYZIhhRhhljHEmmGSKaWaYZY55FlhkiWVWWGWNdTbYZIttdthlj30OOOSIY074zSlnnHPBJVdcc8Mtd9zzwCNPPPOHF155450PPvnimx9+/adfAgwyxDAjjDLGOBNMMsU0M8wyxzwLLLLEMiusssY6G2yyxTY77LLHPgcccsQxJ/zmlDPOueCSK6654ZY77nngkSee+cMLr7zxzgeffPHND78CYJAhhhlhlDHGmWCSKaaZYZY55llgkSWWWWGVNdbZYJMtttlhlz32OeCQI4454TennHHOBZdccc0Nt9xxzwOPPPHMH1545Y13Pvjki29++PWffwkwyBDDjDDKGONMMMkU08wwyxzzLLDIEsussMoa62ywyRbb7LDLHvsccMgRx5zwm1POOOeCS6645oZb7rjngUeeeOYPL7zyxjsffPLFNz/8+i+/BBhkiGFGGGWMcSaYZIppZphljnkWWGSJZVZYZY11Nthki2122GWPfQ445IhjTvjNKWecc8ElV1xzwy133PPAI08884cXXnnjnQ8++eKbH379xS8BBhlimBFGGWOcCSaZYpoZZpljngUWWWKZFVZZY50NNtlimx122WOfAw454pgTfnPKGedccMkV19xwyx33PPDIE8/84YVX3njng0+++OaHfz78AQYZYpgRRhljnAkmmWKaGWaZY54FFllimRVWWWOdDTbZYpsddtljnwMOOeKYE35zyhnnXHDJFdfccMsd9zzwyBPP/OGFV95454NPvvjm58+g5y9/CTDIEMOMMMoY40wwyRTTzDDLHPMssMgSy6ywyhrrbLDJFtvssMse+xxwyBHHnPCbU84454JLrrjmhlvuuOeBR5545g8vvPLGOx988sU3P/z6q18CDDLEMCOMMsY4E0wyxTQzzDLHPAssssQyK6yyxjobbLLFNjvsssc+BxxyxDEn/OaUM8654JIrrrnhljvueeCRJ575wwuvvPHOB5988c0Pv/7rLwEGGWKYEUYZY5wJJplimhlmmWOeBRZZYpkVVlljnQ022WKbHXbZY58DDjnimBN+c8oZ51xwyRXX3HDLHfc88MgTz/zhhVfeeOeDT7745od/Bv0BBhlimBFGGWOcCSaZYpoZZpljngUWWWKZFVZZY50NNtlimx122WOfAw454pgTfnPKGedccMkV19xwyx33PPDIE8/84YVX3njng0+++Obnz4Lnr38JMMgQw4wwyhjjTDDJFNPMMMsc8yywyBLLrLDKGutssMkW2+ywyx77HHDIEcec8JtTzjjngkuuuOaGW+6454FHnnjmDy+88sY7H3zyxTc//PpvvwQYZIhhRhhljHEmmGSKaWaYZY55FlhkiWVWWGWNdTbYZIttdthlj30OOOSIY074zSlnnHPBJVdcc8Mtd9zzwCNPPPOHF155450PPvnimx9+/fdfAgwyxDAjjDLGOBNMMsU0M8wyxzwLLLLEMiusssY6G2yyxTY77LLHPgcccsQxJ/zmlDPOueCSK6654ZY77nngkSee+cMLr7zxzgeffPHND/8s+AMMMsQwI4wyxjgTTDLFNDPMMsc8CyyyxDIrrLLGOhtsssU2O+yyxz4HHHLEMSf85pQzzrngkiuuueGWO+554JEnnvnDC6+88c4Hn3zxzc+fYMff/BJgkCGGGWGUMcaZYJIppplhljnmWWCRJZZZYZU11tlgky222WGXPfY54JAjjjnhN6eccc4Fl1xxzQ233HHPA4888cwfXnjljXc++OSLb3749be/BBhkiGFGGGWMcSaYZIppZphljnkWWGSJZVZYZY11Nthki2122GWPfQ445IhjTvjNKWecc8ElV1xzwy133PPAI08884cXXnnjnQ8++eKbH379j18CDDLEMCOMMsY4E0wyxTQzzDLHPAssssQyK6yyxjobbLLFNjvsssc+BxxyxDEn/OaUM8654JIrrrnhljvueeCRJ575wwuvvPHOB5988c0P/wT7AgwyxDAjjDLGOBNMMsU0M8wyxzwLLLLEMiusssY6G2yyxTY77LLHPgcccsQxJ/zmlDPOueCSK6654ZY77nngkSee+cMLr7zxzgeffPHNz59A59/9EmCQIYYZYZQxxplgkimmmWGWOeZZYJEllllhlTXW2WCTLbbZYZc99jngkCOOOeE3p5xxzgWXXHHNDbfccc8DjzzxzB9eeOWNdz745Itvfvj1978EGGSIYUYYZYxxJphkimlmmGWOeRZYZIllVlhljXU22GSLbXbYZY99DjjkiGNO+M0pZ5xzwSVXXHPDLXfc88AjTzzzhxdeeeOdDz754psffv3PXwIMMsQwI4wyxjgTTDLFNDPMMsc8CyyyxDIrrLLGOhtsssU2O+yyxz4HHHLEMSf85pQzzrngkiuuueGWO+554JEnnvnDC6+88c4Hn3zxzQ//BPoDDDLEMCOMMsY4E0wyxTQzzDLHPAssssQyK6yyxjobbLLFNjvsssc+BxxyxDEn/OaUM8654JIrrrnhljvueeCRJ575wwuvvPHOB5988c3PnyLHP/wSYJAhhhlhlDHGmWCSKaaZYZY55llgkSWWWWGVNdbZYJMtttlhlz32OeCQI4454TennHHOBZdccc0Nt9xxzwOPPPHMH1545Y13Pvjki29++PWPvwQYZIhhRhhljHEmmGSKaWaYZY55FlhkiWVWWGWNdTbYZIttdthlj30OOOSIY074zSlnnHPBJVdcc8Mtd9zzwCNPPPOHF155450PPvnimx9+/a9fAgwyxDAjjDLGOBNMMsU0M8wyxzwLLLLEMiusssY6G2yyxTY77LLHPgcccsQxJ/zmlDPOueCSK6654ZY77nngkSee+cMLr7zxzgeffPHND/8U+QIMMsQwI4wyxjgTTDLFNDPMMsc8CyyyxDIrrLLGOhtsssU2O+yyxz4HHHLEMSf85pQzzrngkiuuueGWO+554JEnnvnDC6+88c4Hn3zxzc+fAuc//RJgkCGGGWGUMcaZYJIppplhljnmWWCRJZZZYZU11tlgky222WGXPfY54JAjjjnhN6eccc4Fl1xxzQ233HHPA4888cwfXnjljXc++OSLb3749b9/CTDIEMOMMMoY40wwyRTTzDDLHPMssMgSy6ywyhrrbLDJFtvssMse+xxwyBHHnPCbU84454JLrrjmhlvuuOeBR5545g8vvPLGOx988sU3P/z6P78EGGSIYUYYZYxxJphkimlmmGWOeRZYZIllVlhljXU22GSLbXbYZY99DjjkiGNO+M0pZ5xzwSVXXHPDLXfc88AjTzzzhxdeeeOdDz754psf/inwBxhkiGFGGGWMcSaYZIppZphljnkWWGSJZVZYZY11Nthki2122GWPfQ445IhjTvjNKWecc8ElV1xzwy133PPAI08884cXXnnjnQ8++eKbH3798y8BBhlimBFGGWOcCSaZYpoZZpljngUWWWKZFVZZY50NNtlimx122WOfAw454pgTfnPKGedccMkV19xwyx33PPDIE8/84YVX3njng0+++OaHX//yS4BBhhhmhFHGGGeCSaaYZoZZ5phngUWWWGaFVdZYZ4NNtthmh1322OeAQ4445oTfnHLGORdccsU1N9xyxz0PPPLEM3944ZU33vngky+++eHXv/4SYJAhhhlhlDHGmWCSKaaZYZY55llgkSWWWWGVNdbZYJMtttlhlz32OeCQI4454TennHHOBZdccc0Nt9xxzwOPPPHMH1545Y13Pvjki29++OdwT4BBhhhmhFHGGGeCSaaYZoZZ5phngUWWWGaFVdZYZ4NNtthmh1322OeAQ4445oTfnHLGORdccsU1N9xyxz0PPPLEM3944ZU33vngky+++eHXv/0SYJAhhhlhlDHGmWCSKaaZYZY55llgkSWWWWGVNdbZYJMtttlhlz32OeCQI4454TennHHOBZdccc0Nt9xxzwOPPPHMH1545Y13Pvjki29++PXvvwQYZIhhRhhljHEmmGSKaWaYZY55FlhkiWVWWGWNdTbYZIttdthlj30OOOSIY074zSlnnHPBJVdcc8Mtd9zzwCNPPPOHF155450PPvnimx9+/d9fAgwyxDAjjDLGOBNMMsU0M8wyxzwLLLLEMiusssY6G2yyxTY77LLHPgcccsQxJ/zmlDPOueCSK6654ZY77nngkSee+cMLr7zxzgeffPHND/8c7AswyBDDjDDKGONMMMkU08wwyxzzLLDIEsussMoa62ywyRbb7LDLHvsccMgRx5zwm1POOOeCS6645oZb7rjngUeeeOYPL7zyxjsffPLFNz/8+n+/BBhkiGFGGGWMcSaYZIppZphljnkWWGSJZVZYZY11Nthki2122GWPfQ445IhjTvj/AR/r6d4=AQAAAACAAABlCgAAGgAAAA==eJztwSEBAAAAwyC9/oVf4hIoAAA4G4r2XY4=
26
+ </AppendedData>
27
+ </VTKFile>
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/Surf.pvd ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ <?xml version="1.0"?>
2
+ <VTKFile type="Collection" version="0.1"
3
+ byte_order="LittleEndian"
4
+ compressor="vtkZLibDataCompressor">
5
+ <Collection>
6
+ <DataSet timestep="300000" group="" part="0"
7
+ file="Surf/Surf_300000.vtu"/>
8
+ </Collection>
9
+ </VTKFile>
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/config.txt ADDED
@@ -0,0 +1,78 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ variable BZ equal 1.380649E-23
2
+ variable PI equal 3.1415926536
3
+ variable molecular_mass equal 6.63E-26
4
+ variable molecular_diameter equal 4.17E-10
5
+ variable gamma equal 1.666666667
6
+ variable R equal ${BZ}/${molecular_mass}
7
+ variable L equal 1.0
8
+ variable xmin equal -5.0
9
+ variable xmax equal 6.0
10
+ variable ymin equal -5.0
11
+ variable ymax equal 5.0
12
+ variable Kn equal 0.28
13
+ variable Ma equal 4.7
14
+ variable To equal 273.0
15
+ variable Tb equal 273.0
16
+ variable theta equal 0.0
17
+ variable mfp equal ${Kn}*${L}
18
+ variable cpmfp equal 4
19
+ variable nden equal 1.0/sqrt(2.0)/${PI}/${molecular_diameter}/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
20
+ variable sos equal sqrt(${gamma}*${R}*${To})
21
+ variable vo equal ${Ma}*${sos}
22
+ variable vx equal ${vo}*cos(${theta}*2*PI/360)
23
+ variable vy equal ${vo}*sin(${theta}*2*PI/360)
24
+ variable ppc equal 30
25
+ variable xncells equal (${xmax}-${xmin})/${mfp}*${cpmfp}
26
+ variable yncells equal (${ymax}-${ymin})/${mfp}*${cpmfp}
27
+ variable Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
28
+ variable tstep equal (-${xmin}+${xmax})/${vx}/${xncells}/10/4
29
+ variable nave equal 10000
30
+ variable noutput equal 300000
31
+ clear
32
+ shell mkdir output
33
+ shell mkdir grid
34
+ shell mkdir surf
35
+ seed 7
36
+ dimension 2
37
+ global nrho ${nden}
38
+ global fnum ${Fnum}
39
+ timestep ${tstep}
40
+ global gridcut 1.0 particle/reorder 100 comm/sort yes
41
+ region 1 cylinder z 0.0 0.0 3.50 -0.5 0.5
42
+ region 2 cylinder z 0.0 0.0 2.00 -0.5 0.5
43
+ region 3 cylinder z 0.0 0.0 0.80 -0.5 0.5
44
+ boundary o o p
45
+ create_box ${xmin} ${xmax} ${ymin} ${ymax} -0.5 0.5
46
+ create_grid ${xncells} ${yncells} 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
47
+ balance_grid rcb cell
48
+ species gas.species Ar
49
+ mixture air Ar frac 1.0
50
+ mixture air Ar vstream ${vx} ${vy} 0.0 temp ${To}
51
+ collide vss air gas.vhs
52
+ collide_modify vremax 100 yes remain no nearcp yes 10
53
+ read_surf cylinder.surf
54
+ surf_collide 1 diffuse 273.0 1.0
55
+ surf_modify all collide 1
56
+ fix in emit/face air xlo ylo yhi
57
+ balance_grid rcb cell
58
+ create_particles air n 0
59
+ stats 10000
60
+ stats_style step cpu np nattempt ncoll nscoll npave nscollave
61
+ run 200000
62
+ compute 1 grid all air n nrho massrho u v w
63
+ compute 2 grid all air trot
64
+ compute 3 tvib/grid all air
65
+ compute 4 thermal/grid all air press temp
66
+ fix 1 ave/grid all 1 ${nave} ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
67
+ dump 1 grid all ${noutput} output/grid.*.dat id xc yc f_1[*]
68
+ dump_modify 1 format float %12.5g
69
+ compute 5 surf all air n press px py shx shy fx fy etot erot evib
70
+ fix 2 ave/surf all 1 ${nave} ${nave} c_5[*] ave running
71
+ dump 2 surf all ${noutput} output/surf.*.dat id v1x v1y v2x v2y f_2[*]
72
+ dump_modify 2 format float %12.5g
73
+ compute 6 lambda/grid f_1[2] f_1[8] Ar kx
74
+ dump 3 grid all ${noutput} output/lambdakn.*.dat id xc yc c_6[*]
75
+ dump_modify 3 format float %12.5g
76
+ run 100000
77
+ write_grid grid/final-grid.dat
78
+ write_surf surf/geom.surf
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/cylinder.surf ADDED
@@ -0,0 +1,410 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ surf file from Pointwise
2
+
3
+ 200 points
4
+ 200 lines
5
+
6
+ Points
7
+
8
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CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/gas.species ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Species data
2
+
3
+ # species name
4
+ # molecular weight (atomic mass units, e.g. 16 for oxygen)
5
+ # molecular mass (kg)
6
+ # rotational degrees of freedom (integer, unitless)
7
+ # inverse rotational relaxtion number (unitless)
8
+ # vibrational degrees of freedom (integer, unitless)
9
+ # inverse vibrational relaxation number (unitless)
10
+ # vibrational temperature (K)
11
+ # species weight (unitless)
12
+ # multiple of electon charge (1 for a proton)
13
+
14
+ Ar 39.95 6.63E-26 0 0.0 0 0.0 0.0 1.0 0.0
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/gas.vhs ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ # VHS collision model parameters for each species
2
+
3
+ # species name
4
+ # diameter (m)
5
+ # omega (unitless)
6
+ # tref (referenced temperature)
7
+ # alpha (unitless)
8
+
9
+ Ar 4.17e-10 0.81 273 1.0
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/grid/Grid_0_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/grid/Grid_1_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/grid/Grid_2_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/grid/Grid_300000.pvtu ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ <?xml version="1.0"?>
2
+ <VTKFile type="PUnstructuredGrid" version="0.1"
3
+ byte_order="LittleEndian"
4
+ compressor="vtkZLibDataCompressor">
5
+ <PUnstructuredGrid GhostLevel="0">
6
+ <PCellData>
7
+ <PDataArray type="Float64" Name="id"/>
8
+ <PDataArray type="Float64" Name="xc"/>
9
+ <PDataArray type="Float64" Name="yc"/>
10
+ <PDataArray type="Float64" Name="f_1[1]"/>
11
+ <PDataArray type="Float64" Name="f_1[2]"/>
12
+ <PDataArray type="Float64" Name="f_1[3]"/>
13
+ <PDataArray type="Float64" Name="f_1[4]"/>
14
+ <PDataArray type="Float64" Name="f_1[5]"/>
15
+ <PDataArray type="Float64" Name="f_1[6]"/>
16
+ <PDataArray type="Float64" Name="f_1[7]"/>
17
+ <PDataArray type="Float64" Name="f_1[8]"/>
18
+ <PDataArray type="Float64" Name="f_1[9]"/>
19
+ <PDataArray type="Float64" Name="f_1[10]"/>
20
+ </PCellData>
21
+ <PPoints>
22
+ <PDataArray type="Float32" Name="Points" NumberOfComponents="3"/>
23
+ </PPoints>
24
+ <Piece Source="Grid_0_300000.vtu"/>
25
+ <Piece Source="Grid_1_300000.vtu"/>
26
+ <Piece Source="Grid_2_300000.vtu"/>
27
+ <Piece Source="Grid_3_300000.vtu"/>
28
+ </PUnstructuredGrid>
29
+ </VTKFile>
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/grid/Grid_3_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/grid/final-grid.dat ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/log.sparta ADDED
@@ -0,0 +1,319 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ SPARTA (4 Sep 2024)
2
+ Running on 128 MPI task(s)
3
+ variable BZ equal 1.380649E-23
4
+ variable PI equal 3.1415926536
5
+ variable molecular_mass equal 6.63E-26
6
+ variable molecular_diameter equal 4.17E-10
7
+ variable gamma equal 1.666666667
8
+ variable R equal ${BZ}/${molecular_mass}
9
+ variable R equal 1.380649e-23/${molecular_mass}
10
+ variable R equal 1.380649e-23/6.63e-26
11
+ variable L equal 1.0
12
+ variable xmin equal -5.0
13
+ variable xmax equal 6.0
14
+ variable ymin equal -5.0
15
+ variable ymax equal 5.0
16
+ variable Kn equal 0.28
17
+ variable Ma equal 4.7
18
+ variable To equal 273.0
19
+ variable Tb equal 273.0
20
+ variable theta equal 0.0
21
+ variable mfp equal ${Kn}*${L}
22
+ variable mfp equal 0.28*${L}
23
+ variable mfp equal 0.28*1
24
+ variable cpmfp equal 4
25
+ variable nden equal 1.0/sqrt(2.0)/${PI}/${molecular_diameter}/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
26
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/${molecular_diameter}/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
27
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
28
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(${mfp}/${cpmfp}*${Kn})
29
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.28/${cpmfp}*${Kn})
30
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.28/4*${Kn})
31
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.28/4*0.28)
32
+ variable sos equal sqrt(${gamma}*${R}*${To})
33
+ variable sos equal sqrt(1.666666667*${R}*${To})
34
+ variable sos equal sqrt(1.666666667*208.242684766214*${To})
35
+ variable sos equal sqrt(1.666666667*208.242684766214*273)
36
+ variable vo equal ${Ma}*${sos}
37
+ variable vo equal 4.7*${sos}
38
+ variable vo equal 4.7*307.815564238681
39
+ variable vx equal ${vo}*cos(${theta}*2*PI/360)
40
+ variable vx equal 1446.7331519218*cos(${theta}*2*PI/360)
41
+ variable vx equal 1446.7331519218*cos(0*2*PI/360)
42
+ variable vy equal ${vo}*sin(${theta}*2*PI/360)
43
+ variable vy equal 1446.7331519218*sin(${theta}*2*PI/360)
44
+ variable vy equal 1446.7331519218*sin(0*2*PI/360)
45
+ variable ppc equal 30
46
+ variable xncells equal (${xmax}-${xmin})/${mfp}*${cpmfp}
47
+ variable xncells equal (6-${xmin})/${mfp}*${cpmfp}
48
+ variable xncells equal (6--5)/${mfp}*${cpmfp}
49
+ variable xncells equal (6--5)/0.28*${cpmfp}
50
+ variable xncells equal (6--5)/0.28*4
51
+ variable yncells equal (${ymax}-${ymin})/${mfp}*${cpmfp}
52
+ variable yncells equal (5-${ymin})/${mfp}*${cpmfp}
53
+ variable yncells equal (5--5)/${mfp}*${cpmfp}
54
+ variable yncells equal (5--5)/0.28*${cpmfp}
55
+ variable yncells equal (5--5)/0.28*4
56
+ variable Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
57
+ variable Fnum equal 6.60399822965135e+19*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
58
+ variable Fnum equal 6.60399822965135e+19*(6-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
59
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
60
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(5-${ymin})/${ppc}/${xncells}/${yncells}
61
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(5--5)/${ppc}/${xncells}/${yncells}
62
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(5--5)/30/${xncells}/${yncells}
63
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(5--5)/30/157.142857142857/${yncells}
64
+ variable Fnum equal 6.60399822965135e+19*(6--5)*(5--5)/30/157.142857142857/142.857142857143
65
+ variable tstep equal (-${xmin}+${xmax})/${vx}/${xncells}/10/4
66
+ variable tstep equal (--5+${xmax})/${vx}/${xncells}/10/4
67
+ variable tstep equal (--5+6)/${vx}/${xncells}/10/4
68
+ variable tstep equal (--5+6)/1446.7331519218/${xncells}/10/4
69
+ variable tstep equal (--5+6)/1446.7331519218/157.142857142857/10/4
70
+ variable nave equal 10000
71
+ variable noutput equal 300000
72
+ clear
73
+ Running on 128 MPI task(s)
74
+ shell mkdir output
75
+ shell mkdir grid
76
+ shell mkdir surf
77
+ seed 7
78
+ dimension 2
79
+ global nrho ${nden}
80
+ global nrho 6.60399822965135e+19
81
+ global fnum ${Fnum}
82
+ global fnum 1.07865304417639e+16
83
+ timestep ${tstep}
84
+ timestep 1.20962182809964e-06
85
+ global gridcut 1.0 particle/reorder 100 comm/sort yes
86
+ region 1 cylinder z 0.0 0.0 3.50 -0.5 0.5
87
+ region 2 cylinder z 0.0 0.0 2.00 -0.5 0.5
88
+ region 3 cylinder z 0.0 0.0 0.80 -0.5 0.5
89
+ boundary o o p
90
+ create_box ${xmin} ${xmax} ${ymin} ${ymax} -0.5 0.5
91
+ create_box -5 ${xmax} ${ymin} ${ymax} -0.5 0.5
92
+ create_box -5 6 ${ymin} ${ymax} -0.5 0.5
93
+ create_box -5 6 -5 ${ymax} -0.5 0.5
94
+ create_box -5 6 -5 5 -0.5 0.5
95
+ Created orthogonal box = (-5 -5 -0.5) to (6 5 0.5)
96
+ create_grid ${xncells} ${yncells} 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
97
+ create_grid 157.142857142857 ${yncells} 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
98
+ create_grid 157.142857142857 142.857142857143 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
99
+ Created 97600 child grid cells
100
+ CPU time = 0.132391 secs
101
+ create/ghost percent = 0.974015 99.026
102
+ balance_grid rcb cell
103
+ Balance grid migrated 97380 cells
104
+ CPU time = 0.106968 secs
105
+ reassign/sort/migrate/ghost percent = 51.4782 0.0325884 7.98238 40.5068
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 1446.7331519218 ${vy} 0.0 temp ${To}
110
+ mixture air Ar vstream 1446.7331519218 0 0.0 temp ${To}
111
+ mixture air Ar vstream 1446.7331519218 0 0.0 temp 273
112
+ collide vss air gas.vhs
113
+ collide_modify vremax 100 yes remain no nearcp yes 10
114
+ read_surf cylinder.surf
115
+ 200 lines
116
+ -0.5 0.5 xlo xhi
117
+ -0.5 0.5 ylo yhi
118
+ 0 0 zlo zhi
119
+ 0.0157073 min line length
120
+ 456 0 = cells overlapping surfs, overlap cells with unmarked corner pts
121
+ 87188 9956 456 = cells outside/inside/overlapping surfs
122
+ 456 = surf cells with 1,2,etc splits
123
+ 109.215 109.215 = cell-wise and global flow volume
124
+ CPU time = 0.11863 secs
125
+ read/check/sort/surf2grid/ghost/inout/particle percent = 16.972 25.2983 2.19356 19.6535 35.8826 5.38154 0.126257
126
+ surf2grid time = 0.0233149 secs
127
+ map/comm1/comm2/comm3/comm4/split percent = 15.4857 23.7414 5.57564 1.77395 11.3053 6.44186
128
+ surf_collide 1 diffuse 273.0 1.0
129
+ surf_modify all collide 1
130
+ fix in emit/face air xlo ylo yhi
131
+ balance_grid rcb cell
132
+ Balance grid migrated 1938 cells
133
+ CPU time = 0.0530547 secs
134
+ reassign/sort/migrate/ghost percent = 5.60979 0.057863 17.7837 76.5486
135
+ create_particles air n 0
136
+ WARNING: Created unexpected # of particles: 668660 versus 668661 (../create_particles.cpp:346)
137
+ Created 668660 particles
138
+ CPU time = 0.016437 secs
139
+ stats 10000
140
+ stats_style step cpu np nattempt ncoll nscoll npave nscollave
141
+ run 200000
142
+ Memory usage per proc in Mbytes:
143
+ particles (ave,min,max) = 1.79297 0 3.375
144
+ grid (ave,min,max) = 4.297 1.51379 7.13879
145
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
146
+ total (ave,min,max) = 6.11057 3.22189 8.84689
147
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
148
+ 0 0 668660 0 0 0 0 0
149
+ 10000 15.518698 737250 14267 12349 15 696008.8 18.09
150
+ 20000 37.373091 743701 14702 12721 16 719158.57 18.2874
151
+ 30000 60.80238 745322 14520 12625 18 727784.4 18.3951
152
+ 40000 82.365434 744614 14476 12553 21 732198.98 18.432725
153
+ 50000 105.754 744645 14670 12770 18 734611.29 18.44922
154
+ 60000 128.19934 745779 14774 12816 20 736342.1 18.4625
155
+ 70000 150.5533 745109 14439 12488 20 737582.9 18.486743
156
+ 80000 173.02743 744893 14646 12703 15 738554.8 18.505437
157
+ 90000 195.36604 745841 14648 12666 18 739367.14 18.513222
158
+ 100000 217.39197 744549 14607 12726 21 739966.08 18.51582
159
+ 110000 240.82859 745593 14561 12633 21 740407.61 18.520418
160
+ 120000 262.43709 744836 14500 12492 13 740787.49 18.518125
161
+ 130000 284.62565 744439 14636 12658 26 741088.96 18.522577
162
+ 140000 307.59753 744411 14367 12406 18 741341.32 18.524007
163
+ 150000 330.05771 744813 14828 12896 22 741579.04 18.52624
164
+ 160000 351.52234 743548 14590 12683 17 741766.24 18.524794
165
+ 170000 374.1959 744784 14496 12559 24 741947.68 18.5286
166
+ 180000 396.1858 745077 14706 12775 16 742083.15 18.528922
167
+ 190000 419.5196 745223 14596 12725 18 742243.33 18.530311
168
+ 200000 441.10512 744537 14637 12744 22 742383.13 18.539445
169
+ Loop time of 441.106 on 128 procs for 200000 steps with 744537 particles
170
+
171
+ MPI task timing breakdown:
172
+ Section | min time | avg time | max time |%varavg| %total
173
+ ---------------------------------------------------------------
174
+ Move | 0.023189 | 18.409 | 120.43 | 565.6 | 4.17
175
+ Coll | 0.49365 | 19 | 184.02 | 649.1 | 4.31
176
+ Sort | 0.1682 | 3.5216 | 32.202 | 270.5 | 0.80
177
+ Comm | 66.019 | 99.723 | 110.84 | 93.7 | 22.61
178
+ Modify | 0.020454 | 0.15818 | 3.1612 | 111.0 | 0.04
179
+ Output | 0.018176 | 0.026134 | 0.044544 | 4.8 | 0.01
180
+ Other | | 300.3 | | | 68.07
181
+
182
+ Particle moves = 148476625877 (148B)
183
+ Cells touched = 155195777720 (155B)
184
+ Particle comms = 250482171 (250M)
185
+ Boundary collides = 0 (0K)
186
+ Boundary exits = 24448923 (24.4M)
187
+ SurfColl checks = 204046075 (204M)
188
+ SurfColl occurs = 3707889 (3.71M)
189
+ Surf reactions = 0 (0K)
190
+ Collide attempts = 3370039191 (3.37B)
191
+ Collide occurs = 2612301148 (2.61B)
192
+ Reactions = 0 (0K)
193
+ Particles stuck = 0
194
+ Axisymm bad moves = 0
195
+
196
+ Particle-moves/CPUsec/proc: 2.62969e+06
197
+ Particle-moves/step: 742383
198
+ Cell-touches/particle/step: 1.04525
199
+ Particle comm iterations/step: 1
200
+ Particle fraction communicated: 0.00168701
201
+ Particle fraction colliding with boundary: 0
202
+ Particle fraction exiting boundary: 0.000164665
203
+ Surface-checks/particle/step: 0.00137426
204
+ Surface-collisions/particle/step: 2.49729e-05
205
+ Surf-reactions/particle/step: 0
206
+ Collision-attempts/particle/step: 0.0226974
207
+ Collisions/particle/step: 0.017594
208
+ Reactions/particle/step: 0
209
+
210
+ Particles: 5816.7 ave 39914 max 0 min
211
+ Histogram: 84 16 3 12 3 6 0 0 2 2
212
+ Cells: 762.5 ave 763 max 762 min
213
+ Histogram: 64 0 0 0 0 0 0 0 0 64
214
+ GhostCell: 19721.7 ave 36096 max 1099 min
215
+ Histogram: 20 10 12 10 18 2 6 4 16 30
216
+ EmptyCell: 0 ave 0 max 0 min
217
+ Histogram: 128 0 0 0 0 0 0 0 0 0
218
+ Surfs: 200 ave 200 max 200 min
219
+ Histogram: 128 0 0 0 0 0 0 0 0 0
220
+ GhostSurf: 0 ave 0 max 0 min
221
+ Histogram: 128 0 0 0 0 0 0 0 0 0
222
+ compute 1 grid all air n nrho massrho u v w
223
+ compute 2 grid all air trot
224
+ compute 3 tvib/grid all air
225
+ compute 4 thermal/grid all air press temp
226
+ fix 1 ave/grid all 1 ${nave} ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
227
+ fix 1 ave/grid all 1 10000 ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
228
+ fix 1 ave/grid all 1 10000 10000 c_1[*] c_4[*] c_2[*] c_3[*] ave running
229
+ dump 1 grid all ${noutput} output/grid.*.dat id xc yc f_1[*]
230
+ dump 1 grid all 300000 output/grid.*.dat id xc yc f_1[*]
231
+ dump_modify 1 format float %12.5g
232
+ compute 5 surf all air n press px py shx shy fx fy etot erot evib
233
+ fix 2 ave/surf all 1 ${nave} ${nave} c_5[*] ave running
234
+ fix 2 ave/surf all 1 10000 ${nave} c_5[*] ave running
235
+ fix 2 ave/surf all 1 10000 10000 c_5[*] ave running
236
+ dump 2 surf all ${noutput} output/surf.*.dat id v1x v1y v2x v2y f_2[*]
237
+ dump 2 surf all 300000 output/surf.*.dat id v1x v1y v2x v2y f_2[*]
238
+ dump_modify 2 format float %12.5g
239
+ compute 6 lambda/grid f_1[2] f_1[8] Ar kx
240
+ dump 3 grid all ${noutput} output/lambdakn.*.dat id xc yc c_6[*]
241
+ dump 3 grid all 300000 output/lambdakn.*.dat id xc yc c_6[*]
242
+ dump_modify 3 format float %12.5g
243
+ run 100000
244
+ Memory usage per proc in Mbytes:
245
+ particles (ave,min,max) = 1.87207 0 5.0625
246
+ grid (ave,min,max) = 4.297 1.51379 7.13879
247
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
248
+ total (ave,min,max) = 6.4459 3.47786 9.10336
249
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
250
+ 200000 0 744537 14637 12744 0 0 0
251
+ 210000 40.54693 745445 14468 12640 24 745660.76 18.6793
252
+ 220000 79.350735 744580 14611 12632 19 745426.22 18.60465
253
+ 230000 119.04925 746114 14568 12648 19 745364.62 18.6126
254
+ 240000 158.58101 744859 14474 12571 10 745348.99 18.5909
255
+ 250000 197.75804 745118 14484 12598 20 745259.24 18.57424
256
+ 260000 237.69667 744244 14673 12728 23 745232.41 18.584683
257
+ 270000 277.30929 744909 14549 12607 20 745213.68 18.572243
258
+ 280000 316.40515 745215 14618 12672 5 745197.26 18.585863
259
+ 290000 356.17213 744737 14597 12718 17 745125.87 18.580922
260
+ 300000 394.76796 745038 14787 12850 16 745063.64 18.57483
261
+ Loop time of 394.768 on 128 procs for 100000 steps with 745038 particles
262
+
263
+ MPI task timing breakdown:
264
+ Section | min time | avg time | max time |%varavg| %total
265
+ ---------------------------------------------------------------
266
+ Move | 0.012951 | 9.3028 | 60.458 | 400.4 | 2.36
267
+ Coll | 0.24742 | 9.7202 | 99.324 | 474.6 | 2.46
268
+ Sort | 0.098869 | 1.8162 | 13.052 | 187.5 | 0.46
269
+ Comm | 40.322 | 57.245 | 63.469 | 65.1 | 14.50
270
+ Modify | 3.4595 | 25.683 | 157.1 | 614.9 | 6.51
271
+ Output | 0.03913 | 0.040472 | 0.04428 | 0.6 | 0.01
272
+ Other | | 291 | | | 73.70
273
+
274
+ Particle moves = 74506364119 (74.5B)
275
+ Cells touched = 77875135831 (77.9B)
276
+ Particle comms = 125553125 (126M)
277
+ Boundary collides = 0 (0K)
278
+ Boundary exits = 12264264 (12.3M)
279
+ SurfColl checks = 102380086 (102M)
280
+ SurfColl occurs = 1857483 (1.86M)
281
+ Surf reactions = 0 (0K)
282
+ Collide attempts = 1701061843 (1.7B)
283
+ Collide occurs = 1318366870 (1.32B)
284
+ Reactions = 0 (0K)
285
+ Particles stuck = 0
286
+ Axisymm bad moves = 0
287
+
288
+ Particle-moves/CPUsec/proc: 1.47449e+06
289
+ Particle-moves/step: 745064
290
+ Cell-touches/particle/step: 1.04521
291
+ Particle comm iterations/step: 1
292
+ Particle fraction communicated: 0.00168513
293
+ Particle fraction colliding with boundary: 0
294
+ Particle fraction exiting boundary: 0.000164607
295
+ Surface-checks/particle/step: 0.00137411
296
+ Surface-collisions/particle/step: 2.49305e-05
297
+ Surf-reactions/particle/step: 0
298
+ Collision-attempts/particle/step: 0.0228311
299
+ Collisions/particle/step: 0.0176947
300
+ Reactions/particle/step: 0
301
+
302
+ Particles: 5820.61 ave 40308 max 0 min
303
+ Histogram: 84 16 5 11 2 6 0 0 2 2
304
+ Cells: 762.5 ave 763 max 762 min
305
+ Histogram: 64 0 0 0 0 0 0 0 0 64
306
+ GhostCell: 19721.7 ave 36096 max 1099 min
307
+ Histogram: 20 10 12 10 18 2 6 4 16 30
308
+ EmptyCell: 0 ave 0 max 0 min
309
+ Histogram: 128 0 0 0 0 0 0 0 0 0
310
+ Surfs: 200 ave 200 max 200 min
311
+ Histogram: 128 0 0 0 0 0 0 0 0 0
312
+ GhostSurf: 0 ave 0 max 0 min
313
+ Histogram: 128 0 0 0 0 0 0 0 0 0
314
+ write_grid grid/final-grid.dat
315
+ grid cells = 97600
316
+ CPU time = 0.0136899 secs
317
+ write_surf surf/geom.surf
318
+ surf elements = 200
319
+ CPU time = 0.0024412 secs
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/mir.txt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ dimension 2
2
+ create_box -5.0 6.0 -5.0 5.0 -0.5 0.5
3
+ read_grid grid/final-grid.dat
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/output/lambdakn.300000.dat ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/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 0.00415 0.10739 -0.10738 0.0016869 -1.8242e-05 -0.0011612 -0.001687 8.2569e-06 17.762 0 0
11
+ 129 -0.31871 0.38526 -0.30645 0.39508 0.14947 4.1111 2.5704 -3.2084 0.55352 0.44345 0.049069 -0.04343 800.11 0 0
12
+ 2 0.49975 -0.015705 0.49901 -0.031395 0.00415 0.11266 -0.11254 0.0053072 -3.9844e-05 -0.00084489 -0.0017683 7.0091e-05 17.148 0 0
13
+ 130 -0.30645 0.39508 -0.29389 0.40451 0.14026 3.886 2.3332 -3.1076 0.56523 0.42439 0.045527 -0.042146 772.42 0 0
14
+ 3 0.49901 -0.031395 0.49778 -0.047054 0.00391 0.10013 -0.099823 0.0078563 -8.5714e-05 -0.0010891 -0.0015693 0.00010629 15.467 0 0
15
+ 131 -0.29389 0.40451 -0.28104 0.41354 0.13591 3.7357 2.148 -3.0563 0.5789 0.40686 0.042833 -0.041616 720.96 0 0
16
+ 4 0.49778 -0.047054 0.49606 -0.062667 0.00404 0.10662 -0.10597 0.0117 0.00018164 0.0016453 -0.0016617 0.00020961 17.079 0 0
17
+ 132 -0.28104 0.41354 -0.26791 0.42216 0.13011 3.5989 1.9759 -3.008 0.62814 0.41261 0.040902 -0.040767 716.33 0 0
18
+ 5 0.49606 -0.062667 0.49384 -0.078217 0.00403 0.1038 -0.10276 0.014625 -0.00073867 -0.0051901 -0.0016257 0.0001482 17.535 0 0
19
+ 133 -0.26791 0.42216 -0.25452 0.43037 0.12263 3.3597 1.7555 -2.8646 0.59252 0.3631 0.03688 -0.039293 676.84 0 0
20
+ 6 0.49384 -0.078217 0.49114 -0.093691 0.0042 0.11023 -0.10859 0.018951 0.00057473 0.0032931 -0.0016966 0.0003494 17.059 0 0
21
+ 134 -0.25452 0.43037 -0.24088 0.43815 0.11548 3.1919 1.5815 -2.7726 0.59784 0.341 0.034231 -0.038194 647.67 0 0
22
+ 7 0.49114 -0.093691 0.48796 -0.10907 0.00348 0.091035 -0.089143 0.018461 -0.00034814 -0.0016811 -0.0014057 0.00026356 14.31 0 0
23
+ 135 -0.24088 0.43815 -0.227 0.4455 0.10903 3.0165 1.4115 -2.6659 0.59846 0.31687 0.031571 -0.036897 611.93 0 0
24
+ 8 0.48796 -0.10907 0.48429 -0.12434 0.00365 0.094723 -0.092106 0.022113 0.0012065 0.0050254 -0.0014278 0.00042627 16.257 0 0
25
+ 136 -0.227 0.4455 -0.21289 0.45241 0.10313 2.8476 1.2528 -2.5572 0.61938 0.30343 0.029406 -0.035401 576.9 0 0
26
+ 9 0.48429 -0.12434 0.48015 -0.1395 0.00388 0.1021 -0.098483 0.026942 -0.0002385 -0.00087182 -0.0015506 0.00040949 19.596 0 0
27
+ 137 -0.21289 0.45241 -0.19857 0.45888 0.09692 2.6726 1.0998 -2.4358 0.58401 0.26369 0.026448 -0.034118 560.99 0 0
28
+ 10 0.48015 -0.1395 0.47553 -0.15451 0.00339 0.087143 -0.083291 0.025624 0.00074685 0.0024277 -0.0012965 0.00044061 16.248 0 0
29
+ 138 -0.19857 0.45888 -0.18406 0.46489 0.09009 2.4853 0.95107 -2.2961 0.58229 0.24119 0.024085 -0.032277 517.13 0 0
30
+ 11 0.47553 -0.15451 0.47044 -0.16937 0.00325 0.085089 -0.080502 0.027562 0.0020756 0.0060622 -0.0012319 0.00052815 12.913 0 0
31
+ 139 -0.18406 0.46489 -0.16937 0.47044 0.08599 2.3439 0.82853 -2.1926 0.58167 0.21979 0.02215 -0.030988 492.44 0 0
32
+ 12 0.47044 -0.16937 0.46489 -0.18406 0.00334 0.08752 -0.08187 0.030936 0.0036769 0.0097307 -0.0012282 0.00063877 12.293 0 0
33
+ 140 -0.16937 0.47044 -0.15451 0.47553 0.08149 2.2396 0.72543 -2.1188 0.56666 0.19401 0.020295 -0.030233 474.41 0 0
34
+ 13 0.46489 -0.18406 0.45888 -0.19857 0.00341 0.084581 -0.078142 0.032368 0.003 0.0072425 -0.0011803 0.00062217 13.506 0 0
35
+ 141 -0.15451 0.47553 -0.1395 0.48015 0.07649 2.0917 0.61504 -1.9992 0.55702 0.17136 0.01841 -0.028711 433.2 0 0
36
+ 14 0.45888 -0.19857 0.45241 -0.21289 0.00326 0.081623 -0.074392 0.033589 0.0021297 0.0047169 -0.001135 0.00060169 16.445 0 0
37
+ 142 -0.1395 0.48015 -0.12434 0.48429 0.07175 1.9666 0.51893 -1.8969 0.56129 0.15355 0.016968 -0.027383 424.47 0 0
38
+ 15 0.45241 -0.21289 0.4455 -0.227 0.0029 0.072624 -0.065218 0.03195 0.0075614 0.015435 -0.00090564 0.00074429 14.819 0 0
39
+ 143 -0.12434 0.48429 -0.10907 0.48796 0.06651 1.8246 0.42594 -1.7742 0.54848 0.13168 0.015305 -0.025799 400.79 0 0
40
+ 16 0.4455 -0.227 0.43815 -0.24088 0.00283 0.071318 -0.063029 0.033372 0.0046997 0.0088763 -0.00091619 0.00066361 12.491 0 0
41
+ 144 -0.10907 0.48796 -0.093691 0.49114 0.06191 1.6845 0.34159 -1.6495 0.49445 0.1024 0.013132 -0.0243 352.37 0 0
42
+ 17 0.43815 -0.24088 0.43037 -0.25452 0.00309 0.07394 -0.064226 0.036634 0.010566 0.018525 -0.00084285 0.0008664 16.076 0 0
43
+ 145 -0.093691 0.49114 -0.078217 0.49384 0.05734 1.5704 0.27 -1.547 0.51066 0.089125 0.012262 -0.0229 342.98 0 0
44
+ 18 0.43037 -0.25452 0.42216 -0.26791 0.00275 0.067389 -0.057459 0.035211 0.010471 0.017087 -0.00073805 0.00082146 13.018 0 0
45
+ 146 -0.078217 0.49384 -0.062667 0.49606 0.05376 1.4649 0.2064 -1.4503 0.48054 0.068391 0.01079 -0.021705 327.73 0 0
46
+ 19 0.42216 -0.26791 0.41354 -0.28104 0.00287 0.070055 -0.058552 0.038462 0.012996 0.019785 -0.00071556 0.0009149 15.761 0 0
47
+ 147 -0.062667 0.49606 -0.047054 0.49778 0.05091 1.3749 0.15087 -1.3666 0.47928 0.052913 0.009898 -0.020635 299.68 0 0
48
+ 20 0.41354 -0.28104 0.40451 -0.29389 0.00296 0.068291 -0.055873 0.039268 0.013361 0.01901 -0.00066775 0.0009154 14.441 0 0
49
+ 148 -0.047054 0.49778 -0.031395 0.49901 0.04625 1.2436 0.097569 -1.2397 0.4648 0.03658 0.0088332 -0.018898 281.2 0 0
50
+ 21 0.40451 -0.29389 0.39508 -0.30645 0.00297 0.06758 -0.054042 0.040576 0.018122 0.024136 -0.00056421 0.0010165 16.018 0 0
51
+ 149 -0.031395 0.49901 -0.015705 0.49975 0.04285 1.1597 0.054628 -1.1584 0.43625 0.020573 0.0077104 -0.017872 266.36 0 0
52
+ 22 0.39508 -0.30645 0.38526 -0.31871 0.00311 0.074021 -0.057768 0.046281 0.023336 0.029128 -0.00054084 0.0011845 19.582 0 0
53
+ 150 -0.015705 0.49975 0 0.5 0.03932 1.0493 0.016482 -1.0492 0.40918 0.0064279 0.006686 -0.016379 245.9 0 0
54
+ 23 0.38526 -0.31871 0.37506 -0.33066 0.00294 0.069712 -0.053009 0.045274 0.021707 0.025416 -0.00049167 0.0011104 15.845 0 0
55
+ 151 0 0.5 0.015705 0.49975 0.03465 0.9325 -0.014647 -0.93239 0.36799 -0.0057809 0.0055501 -0.014736 221.59 0 0
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+ 24 0.37506 -0.33066 0.36448 -0.34227 0.00368 0.083538 -0.061787 0.056222 0.033194 0.03648 -0.00044912 0.0014561 20.981 0 0
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+ 152 0.015705 0.49975 0.031395 0.49901 0.03351 0.89619 -0.042217 -0.8952 0.37567 -0.017716 0.0052376 -0.014339 208.12 0 0
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+ 25 0.36448 -0.34227 0.35355 -0.35355 0.00406 0.096716 -0.069454 0.067306 0.043309 0.044692 -0.00041067 0.0017592 26.487 0 0
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+ 153 0.031395 0.49901 0.047054 0.49778 0.03072 0.82219 -0.064508 -0.81966 0.32865 -0.025865 0.0041489 -0.013281 187.05 0 0
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+ 26 0.35355 -0.35355 0.34227 -0.36448 0.00376 0.088857 -0.061836 0.06381 0.040506 0.039253 -0.00033505 0.0016188 22.129 0 0
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+ 154 0.047054 0.49778 0.062667 0.49606 0.02834 0.75133 -0.082446 -0.74679 0.32593 -0.035983 0.0038245 -0.012295 180.18 0 0
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+ 27 0.34227 -0.36448 0.33066 -0.37506 0.00491 0.11533 -0.077621 0.085305 0.053866 0.049014 -0.00037313 0.0021098 34.711 0 0
63
+ 155 0.062667 0.49606 0.078217 0.49384 0.02621 0.68681 -0.096773 -0.67996 0.30574 -0.043514 0.0032824 -0.011364 164.58 0 0
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+ 28 0.33066 -0.37506 0.31871 -0.38526 0.00475 0.11051 -0.071768 0.084029 0.06338 0.054132 -0.00013174 0.0021701 28.534 0 0
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+ 29 0.31871 -0.38526 0.30645 -0.39508 0.00536 0.12965 -0.081064 0.10118 0.0687 0.055039 -0.0001942 0.0024538 34.06 0 0
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+ 157 0.093691 0.49114 0.10907 0.48796 0.02114 0.55383 -0.11231 -0.54232 0.27676 -0.057313 0.002583 -0.0094187 140.57 0 0
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+ 30 0.30645 -0.39508 0.29389 -0.40451 0.00564 0.13189 -0.079189 0.10547 0.077179 0.057948 -3.1571e-05 0.0025669 38.953 0 0
69
+ 158 0.10907 0.48796 0.12434 0.48429 0.0189 0.48933 -0.11423 -0.47581 0.24718 -0.059342 0.0020882 -0.0084058 120.22 0 0
70
+ 31 0.29389 -0.40451 0.28104 -0.41354 0.00602 0.14378 -0.082674 0.11763 0.083282 0.058532 9.5559e-06 0.0027671 40.231 0 0
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+ 159 0.12434 0.48429 0.1395 0.48015 0.01748 0.44673 -0.11788 -0.4309 0.21896 -0.059901 0.0015877 -0.0077091 109.43 0 0
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+ 32 0.28104 -0.41354 0.26791 -0.42216 0.00728 0.17505 -0.096107 0.14631 0.10063 0.066102 7.1053e-05 0.0033364 46.497 0 0
73
+ 160 0.1395 0.48015 0.15451 0.47553 0.01615 0.41561 -0.12221 -0.39724 0.21724 -0.066832 0.0014927 -0.0072893 107.76 0 0
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+ 33 0.26791 -0.42216 0.25452 -0.43037 0.00767 0.18686 -0.097632 0.15932 0.10181 0.06239 6.5657e-05 0.0034825 52.638 0 0
75
+ 161 0.15451 0.47553 0.16937 0.47044 0.01471 0.38169 -0.12364 -0.36111 0.20774 -0.071125 0.001321 -0.0067893 105.38 0 0
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+ 34 0.25452 -0.43037 0.24088 -0.43815 0.00828 0.19909 -0.098643 0.17294 0.11245 0.06414 0.00021687 0.0037239 54.013 0 0
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+ 35 0.24088 -0.43815 0.227 -0.4455 0.00894 0.22375 -0.1047 0.19775 0.12119 0.064164 0.00025892 0.0041139 61.08 0 0
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+ 36 0.227 -0.4455 0.21289 -0.45241 0.00968 0.24224 -0.10657 0.21754 0.13533 0.066299 0.00045176 0.0044583 65.638 0 0
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+ 164 0.19857 0.45888 0.21289 0.45241 0.0114 0.28824 -0.11862 -0.2627 0.15785 -0.071272 0.00061628 -0.0052459 74.747 0 0
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+ 37 0.21289 -0.45241 0.19857 -0.45888 0.01054 0.26435 -0.10878 0.24093 0.14825 0.066938 0.00061994 0.0048357 70.233 0 0
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+ 165 0.21289 0.45241 0.227 0.4455 0.01028 0.25247 -0.11107 -0.22672 0.14288 -0.069997 0.00049967 -0.0046607 62.664 0 0
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+ 38 0.19857 -0.45888 0.18406 -0.46489 0.01167 0.29177 -0.11166 0.26956 0.16524 0.068444 0.00084163 0.0053092 77.617 0 0
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+ 166 0.227 0.4455 0.24088 0.43815 0.00947 0.2363 -0.11057 -0.20883 0.13165 -0.069706 0.00033112 -0.0043751 63.021 0 0
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+ 39 0.18406 -0.46489 0.16937 -0.47044 0.01376 0.34779 -0.12293 0.32534 0.1878 0.070964 0.0010189 0.0062248 95.151 0 0
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+ 167 0.24088 0.43815 0.25452 0.43037 0.00825 0.20129 -0.099729 -0.17484 0.11556 -0.065914 0.00024864 -0.0037817 53.234 0 0
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+ 40 0.16937 -0.47044 0.15451 -0.47553 0.01513 0.39077 -0.12658 0.36971 0.19828 0.067887 0.0011263 0.0068734 97.988 0 0
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+ 168 0.25452 0.43037 0.26791 0.42216 0.00786 0.18796 -0.098208 -0.16026 0.10012 -0.061352 2.9999e-05 -0.003481 49.18 0 0
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+ 42 0.1395 -0.48015 0.12434 -0.48429 0.01734 0.44815 -0.11825 0.43226 0.23804 0.06512 0.0018815 0.0078125 118.75 0 0
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+ 127 -0.34227 0.36448 -0.33066 0.37506 0.16332 4.5071 3.0334 -3.3336 0.52713 0.47965 0.055926 -0.044828 874.68 0 0
209
+ 128 -0.33066 0.37506 -0.31871 0.38526 0.15652 4.2992 2.7921 -3.2691 0.59002 0.50392 0.053124 -0.043434 825.04 0 0
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/runmpirun128.sh ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #!/bin/bash
2
+ #SBATCH -J Cylinder——Kn
3
+ #SBATCH -p wzhcnormal
4
+ #SBATCH -N 2
5
+ #SBATCH --ntasks-per-node=64
6
+
7
+
8
+ module purge
9
+ module load compiler/devtoolset/7.3.1
10
+ module load mpi/hpcx/2.11.0/gcc-7.3.1
11
+ export UCX_WARN_UNUSED_ENV_VARS=n
12
+ /public/software/mpi/hpcx/v2.11.0/gcc-7.3.1/bin/mpirun -n 128 ../../../sep2024-sparta/src/spa_mpi <config.txt
13
+
14
+ /work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/grid2paraview.py mir.txt Grid -r ./output/grid.*.dat
15
+
16
+ /work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/grid2paraview.py mir.txt Lambda -r ./output/lambdakn.*.dat
17
+
18
+ /work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/surf2paraview.py ./surf/geom.surf Surf -r ./output/surf.*.dat
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/runmpirun64.sh ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #!/bin/bash
2
+ #SBATCH -J Cylinder——Kn
3
+ #SBATCH -p wzhcnormal
4
+ #SBATCH -N 1
5
+ #SBATCH --ntasks-per-node=64
6
+
7
+
8
+ module purge
9
+ module load compiler/devtoolset/7.3.1
10
+ module load mpi/hpcx/2.11.0/gcc-7.3.1
11
+ export UCX_WARN_UNUSED_ENV_VARS=n
12
+ /public/software/mpi/hpcx/v2.11.0/gcc-7.3.1/bin/mpirun -n 64 ../../../sep2024-sparta/src/spa_mpi <config.txt
13
+
14
+ /work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/grid2paraview.py mir.txt Grid -r ./output/grid.*.dat
15
+
16
+ /work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/grid2paraview.py mir.txt Lambda -r ./output/lambdakn.*.dat
17
+
18
+ /work/home/ackp4pog0w3/WANGXU/ParaView-5.11.1-MPI-Linux-Python3.9-x86_64/bin/pvpython ../../../sep2024-sparta/tools/paraview/surf2paraview.py ./surf/geom.surf Surf -r ./output/surf.*.dat
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/slurm-28429259.out ADDED
@@ -0,0 +1,205 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ SPARTA (4 Sep 2024)
2
+ Running on 128 MPI task(s)
3
+ Running on 128 MPI task(s)
4
+ Created orthogonal box = (-5 -5 -0.5) to (6 5 0.5)
5
+ Created 97600 child grid cells
6
+ CPU time = 0.132391 secs
7
+ create/ghost percent = 0.974015 99.026
8
+ Balance grid migrated 97380 cells
9
+ CPU time = 0.106968 secs
10
+ reassign/sort/migrate/ghost percent = 51.4782 0.0325884 7.98238 40.5068
11
+ Reading surface file ...
12
+ 200 lines
13
+ -0.5 0.5 xlo xhi
14
+ -0.5 0.5 ylo yhi
15
+ 0 0 zlo zhi
16
+ 0.0157073 min line length
17
+ 456 0 = cells overlapping surfs, overlap cells with unmarked corner pts
18
+ 87188 9956 456 = cells outside/inside/overlapping surfs
19
+ 456 = surf cells with 1,2,etc splits
20
+ 109.214731023047 109.214731023047 = cell-wise and global flow volume
21
+ CPU time = 0.11863 secs
22
+ read/check/sort/surf2grid/ghost/inout/particle percent = 16.972 25.2983 2.19356 19.6535 35.8826 5.38154 0.126257
23
+ surf2grid time = 0.0233149 secs
24
+ map/comm1/comm2/comm3/comm4/split percent = 15.4857 23.7414 5.57564 1.77395 11.3053 6.44186
25
+ Balance grid migrated 1938 cells
26
+ CPU time = 0.0530547 secs
27
+ reassign/sort/migrate/ghost percent = 5.60979 0.057863 17.7837 76.5486
28
+ Creating particles ...
29
+ WARNING: Created unexpected # of particles: 668660 versus 668661 (../create_particles.cpp:346)
30
+ Created 668660 particles
31
+ CPU time = 0.016437 secs
32
+ Memory usage per proc in Mbytes:
33
+ particles (ave,min,max) = 1.79297 0 3.375
34
+ grid (ave,min,max) = 4.297 1.51379 7.13879
35
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
36
+ total (ave,min,max) = 6.11057 3.22189 8.84689
37
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
38
+ 0 0 668660 0 0 0 0 0
39
+ 10000 15.518698 737250 14267 12349 15 696008.8 18.09
40
+ 20000 37.373091 743701 14702 12721 16 719158.57 18.2874
41
+ 30000 60.80238 745322 14520 12625 18 727784.4 18.3951
42
+ 40000 82.365434 744614 14476 12553 21 732198.98 18.432725
43
+ 50000 105.754 744645 14670 12770 18 734611.29 18.44922
44
+ 60000 128.19934 745779 14774 12816 20 736342.1 18.4625
45
+ 70000 150.5533 745109 14439 12488 20 737582.9 18.486743
46
+ 80000 173.02743 744893 14646 12703 15 738554.8 18.505437
47
+ 90000 195.36604 745841 14648 12666 18 739367.14 18.513222
48
+ 100000 217.39197 744549 14607 12726 21 739966.08 18.51582
49
+ 110000 240.82859 745593 14561 12633 21 740407.61 18.520418
50
+ 120000 262.43709 744836 14500 12492 13 740787.49 18.518125
51
+ 130000 284.62565 744439 14636 12658 26 741088.96 18.522577
52
+ 140000 307.59753 744411 14367 12406 18 741341.32 18.524007
53
+ 150000 330.05771 744813 14828 12896 22 741579.04 18.52624
54
+ 160000 351.52234 743548 14590 12683 17 741766.24 18.524794
55
+ 170000 374.1959 744784 14496 12559 24 741947.68 18.5286
56
+ 180000 396.1858 745077 14706 12775 16 742083.15 18.528922
57
+ 190000 419.5196 745223 14596 12725 18 742243.33 18.530311
58
+ 200000 441.10512 744537 14637 12744 22 742383.13 18.539445
59
+ Loop time of 441.106 on 128 procs for 200000 steps with 744537 particles
60
+
61
+ MPI task timing breakdown:
62
+ Section | min time | avg time | max time |%varavg| %total
63
+ ---------------------------------------------------------------
64
+ Move | 0.023189 | 18.409 | 120.43 | 565.6 | 4.17
65
+ Coll | 0.49365 | 19 | 184.02 | 649.1 | 4.31
66
+ Sort | 0.1682 | 3.5216 | 32.202 | 270.5 | 0.80
67
+ Comm | 66.019 | 99.723 | 110.84 | 93.7 | 22.61
68
+ Modify | 0.020454 | 0.15818 | 3.1612 | 111.0 | 0.04
69
+ Output | 0.018176 | 0.026134 | 0.044544 | 4.8 | 0.01
70
+ Other | | 300.3 | | | 68.07
71
+
72
+ Particle moves = 148476625877 (148B)
73
+ Cells touched = 155195777720 (155B)
74
+ Particle comms = 250482171 (250M)
75
+ Boundary collides = 0 (0K)
76
+ Boundary exits = 24448923 (24.4M)
77
+ SurfColl checks = 204046075 (204M)
78
+ SurfColl occurs = 3707889 (3.71M)
79
+ Surf reactions = 0 (0K)
80
+ Collide attempts = 3370039191 (3.37B)
81
+ Collide occurs = 2612301148 (2.61B)
82
+ Gas reactions = 0 (0K)
83
+ Particles stuck = 0
84
+ Axisymm bad moves = 0
85
+
86
+ Particle-moves/CPUsec/proc: 2.62969e+06
87
+ Particle-moves/step: 742383
88
+ Cell-touches/particle/step: 1.04525
89
+ Particle comm iterations/step: 1
90
+ Particle fraction communicated: 0.00168701
91
+ Particle fraction colliding with boundary: 0
92
+ Particle fraction exiting boundary: 0.000164665
93
+ Surface-checks/particle/step: 0.00137426
94
+ Surface-collisions/particle/step: 2.49729e-05
95
+ Surface-reactions/particle/step: 0
96
+ Collision-attempts/particle/step: 0.0226974
97
+ Collisions/particle/step: 0.017594
98
+ Gas-reactions/particle/step: 0
99
+
100
+ Particles: 5816.7 ave 39914 max 0 min
101
+ Histogram: 84 16 3 12 3 6 0 0 2 2
102
+ Cells: 762.5 ave 763 max 762 min
103
+ Histogram: 64 0 0 0 0 0 0 0 0 64
104
+ GhostCell: 19721.7 ave 36096 max 1099 min
105
+ Histogram: 20 10 12 10 18 2 6 4 16 30
106
+ EmptyCell: 0 ave 0 max 0 min
107
+ Histogram: 128 0 0 0 0 0 0 0 0 0
108
+ Surfs: 200 ave 200 max 200 min
109
+ Histogram: 128 0 0 0 0 0 0 0 0 0
110
+ GhostSurf: 0 ave 0 max 0 min
111
+ Histogram: 128 0 0 0 0 0 0 0 0 0
112
+ Memory usage per proc in Mbytes:
113
+ particles (ave,min,max) = 1.87207 0 5.0625
114
+ grid (ave,min,max) = 4.297 1.51379 7.13879
115
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
116
+ total (ave,min,max) = 6.4459 3.47786 9.10336
117
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
118
+ 200000 0 744537 14637 12744 0 0 0
119
+ 210000 40.54693 745445 14468 12640 24 745660.76 18.6793
120
+ 220000 79.350735 744580 14611 12632 19 745426.22 18.60465
121
+ 230000 119.04925 746114 14568 12648 19 745364.62 18.6126
122
+ 240000 158.58101 744859 14474 12571 10 745348.99 18.5909
123
+ 250000 197.75804 745118 14484 12598 20 745259.24 18.57424
124
+ 260000 237.69667 744244 14673 12728 23 745232.41 18.584683
125
+ 270000 277.30929 744909 14549 12607 20 745213.68 18.572243
126
+ 280000 316.40515 745215 14618 12672 5 745197.26 18.585863
127
+ 290000 356.17213 744737 14597 12718 17 745125.87 18.580922
128
+ 300000 394.76796 745038 14787 12850 16 745063.64 18.57483
129
+ Loop time of 394.768 on 128 procs for 100000 steps with 745038 particles
130
+
131
+ MPI task timing breakdown:
132
+ Section | min time | avg time | max time |%varavg| %total
133
+ ---------------------------------------------------------------
134
+ Move | 0.012951 | 9.3028 | 60.458 | 400.4 | 2.36
135
+ Coll | 0.24742 | 9.7202 | 99.324 | 474.6 | 2.46
136
+ Sort | 0.098869 | 1.8162 | 13.052 | 187.5 | 0.46
137
+ Comm | 40.322 | 57.245 | 63.469 | 65.1 | 14.50
138
+ Modify | 3.4595 | 25.683 | 157.1 | 614.9 | 6.51
139
+ Output | 0.03913 | 0.040472 | 0.04428 | 0.6 | 0.01
140
+ Other | | 291 | | | 73.70
141
+
142
+ Particle moves = 74506364119 (74.5B)
143
+ Cells touched = 77875135831 (77.9B)
144
+ Particle comms = 125553125 (126M)
145
+ Boundary collides = 0 (0K)
146
+ Boundary exits = 12264264 (12.3M)
147
+ SurfColl checks = 102380086 (102M)
148
+ SurfColl occurs = 1857483 (1.86M)
149
+ Surf reactions = 0 (0K)
150
+ Collide attempts = 1701061843 (1.7B)
151
+ Collide occurs = 1318366870 (1.32B)
152
+ Gas reactions = 0 (0K)
153
+ Particles stuck = 0
154
+ Axisymm bad moves = 0
155
+
156
+ Particle-moves/CPUsec/proc: 1.47449e+06
157
+ Particle-moves/step: 745064
158
+ Cell-touches/particle/step: 1.04521
159
+ Particle comm iterations/step: 1
160
+ Particle fraction communicated: 0.00168513
161
+ Particle fraction colliding with boundary: 0
162
+ Particle fraction exiting boundary: 0.000164607
163
+ Surface-checks/particle/step: 0.00137411
164
+ Surface-collisions/particle/step: 2.49305e-05
165
+ Surface-reactions/particle/step: 0
166
+ Collision-attempts/particle/step: 0.0228311
167
+ Collisions/particle/step: 0.0176947
168
+ Gas-reactions/particle/step: 0
169
+
170
+ Particles: 5820.61 ave 40308 max 0 min
171
+ Histogram: 84 16 5 11 2 6 0 0 2 2
172
+ Cells: 762.5 ave 763 max 762 min
173
+ Histogram: 64 0 0 0 0 0 0 0 0 64
174
+ GhostCell: 19721.7 ave 36096 max 1099 min
175
+ Histogram: 20 10 12 10 18 2 6 4 16 30
176
+ EmptyCell: 0 ave 0 max 0 min
177
+ Histogram: 128 0 0 0 0 0 0 0 0 0
178
+ Surfs: 200 ave 200 max 200 min
179
+ Histogram: 128 0 0 0 0 0 0 0 0 0
180
+ GhostSurf: 0 ave 0 max 0 min
181
+ Histogram: 128 0 0 0 0 0 0 0 0 0
182
+ Writing grid file ...
183
+ grid cells = 97600
184
+ CPU time = 0.0136899 secs
185
+ Writing surface file ...
186
+ surf elements = 200
187
+ CPU time = 0.0024412 secs
188
+ Processing 4 grid chunk(s).
189
+ Completed grid chunk number: 3
190
+ Completed grid chunk number: 2
191
+ Completed grid chunk number: 1
192
+ Completed grid chunk number: 0
193
+
194
+ Done in 0:00:13 (wall clock time)
195
+
196
+ Processing 4 grid chunk(s).
197
+ Completed grid chunk number: 3
198
+ Completed grid chunk number: 2
199
+ Completed grid chunk number: 1
200
+ Completed grid chunk number: 0
201
+
202
+ Done in 0:00:12 (wall clock time)
203
+
204
+ Processing SPARTA surface information.
205
+ Processing dump result file: ['./output/surf.300000.dat']
CylinderKnMa/Kn0p28/simulation0578_Kn0p28Ma4p7/surf/Surf_300000.vtu ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ <?xml version="1.0"?>
2
+ <VTKFile type="UnstructuredGrid" version="0.1" byte_order="LittleEndian" header_type="UInt32" compressor="vtkZLibDataCompressor">
3
+ <UnstructuredGrid>
4
+ <Piece NumberOfPoints="400" NumberOfCells="200" >
5
+ <PointData>
6
+ </PointData>
7
+ <CellData>
8
+ <DataArray type="Float64" Name="id" format="appended" RangeMin="1" RangeMax="200" offset="0" />
9
+ <DataArray type="Float64" Name="v1x" format="appended" RangeMin="-0.5" RangeMax="0.5" offset="432" />
10
+ <DataArray type="Float64" Name="v1y" format="appended" RangeMin="-0.5" RangeMax="0.5" offset="1468" />
11
+ <DataArray type="Float64" Name="v2x" format="appended" RangeMin="-0.5" RangeMax="0.5" offset="2476" />
12
+ <DataArray type="Float64" Name="v2y" format="appended" RangeMin="-0.5" RangeMax="0.5" offset="3508" />
13
+ <DataArray type="Float64" Name="f_2[1]" format="appended" RangeMin="0.00257" RangeMax="0.30409" offset="4512" />
14
+ <DataArray type="Float64" Name="f_2[2]" format="appended" RangeMin="0.06188" RangeMax="8.429" offset="6472" />
15
+ <DataArray type="Float64" Name="f_2[3]" format="appended" RangeMin="-0.1285" RangeMax="8.4196" offset="8536" />
16
+ <DataArray type="Float64" Name="f_2[4]" format="appended" RangeMin="-3.5505" RangeMax="3.4998" offset="10644" />
17
+ <DataArray type="Float64" Name="f_2[5]" format="appended" RangeMin="-0.00093504" RangeMax="0.62839" offset="12716" />
18
+ <DataArray type="Float64" Name="f_2[6]" format="appended" RangeMin="-0.5871" RangeMax="0.57951" offset="14780" />
19
+ <DataArray type="Float64" Name="f_2[7]" format="appended" RangeMin="-0.001856" RangeMax="0.13231" offset="16876" />
20
+ <DataArray type="Float64" Name="f_2[8]" format="appended" RangeMin="-0.04755" RangeMax="0.046143" offset="19016" />
21
+ <DataArray type="Float64" Name="f_2[9]" format="appended" RangeMin="12.293" RangeMax="1582" offset="21152" />
22
+ <DataArray type="Float64" Name="f_2[10]" format="appended" RangeMin="0" RangeMax="0" offset="22508" />
23
+ <DataArray type="Float64" Name="f_2[11]" format="appended" RangeMin="0" RangeMax="0" offset="22560" />
24
+ </CellData>
25
+ <Points>
26
+ <DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="0.49999998503" RangeMax="0.50000001255" offset="22612" />
27
+ </Points>
28
+ <Cells>
29
+ <DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="23940" />
30
+ <DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="24844" />
31
+ <DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="25336" />
32
+ </Cells>
33
+ </Piece>
34
+ </UnstructuredGrid>
35
+ <AppendedData encoding="base64">
36
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AQAAAACAAABABgAA+AUAAA==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AQAAAACAAABABgAAGwYAAA==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AQAAAACAAABABgAA+AUAAA==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AQAAAACAAABABgAAEgYAAA==eJwtlHk8FAoQxwsp3cezaonCqygerXJU5jkqRQop5QhdklLPLS+xpawkIuTIIllr2d2QHI2wRUmOtW72QGpTlLJdej01/87nMzO/7/xmzhGjpp+StcPAK0l+PoWWyB3wMZDpsMHicEsv0fhBSFXZ0LPR1A+vlzOSV37xBM3Fzm5zohyRlXKYQk7whbVjNF3HWCssnu9ANhEdBi+/vpMMbiDMIan9wxwhQ3OB6dPdef/C4Msm0kxbH2h8Ukx1T40BF1lGc4VWOKSSMov0JXEg3oRrTEJjwUa3sf+iaTxYEHTCHANuwI3pGRTF+0kw7p34vaw1DVQNtEU5srfAP/I1I4yRCdtX1uf3CXKgRpuiLFmaDToZCm+dltLAn2JP1rlPh0Q7KffF2vmgU1Zh6ERnwGZJpPTwBAPqgHRlwRsm5Ip0pRPGCiE42jkz+CQTrqTH75h3igl14kfZEgkTBhb1WHSqskD9Qgon6hILJs/rOrI12WDNbemZ7cYCtY7SSefbLBBz9lgX0ZmgJv+YEK7EBOux0lzCIga4hxUO807mQXtNYqRqdg6MvGcsEEdngqnxcGf+l1Rgd33D13WxIL/zjF6sKBDyqkJp9nnBeGxiwI3Ki0dFC4WUfbOpmC47N86YkYcG3T1J6Uwm8nf6e8kIizFIdt73JU4V6Pv66fEg5Sok7Vn2w1hUjecqv4oqPTn40tt0pdT8eix5aOHx7EED1tN95ta5vMAUgwf91DUteFMml3b0ZCsm6W0T53pyUZXYa/LGqg1Feex3FH47Ht46L8dN0oFyteIvM8o7cYP6W9Y4tRudpB3/dFDqQ+oDazWthF6k3daXp+nw8ePOAxEGPD6mDC2/O2zBx59w35G0BWgmVLZUKRMgiTJ4c5+ZEH9xEqL5Ce/RS/VCzGd0HPLfLcQXGdTQ8Cghpo0/HCs+LsBjUyHAO+vMlMRCPnqHyXBidPn4Xv3VrXr9fmT1tHha9HSi/t6rH/SpfUh/mT0RXdiNJhUFh5iKHbitsTrdX9KMCmNpSR/duejHnHzh9rABP83xrynZysGR7ZQ6JuUJHikMCK3YX4nzd2jFW1kz8GJGlr3WqySkkSauj1bGoOLt+skgYhHohphbRapXw+kv91Q0VJ+AbanyJbFNAyyVO2WYKGyEpCpGeVBeM5D1Djf7+nPhV592+MWRB7qtnwrz9XqhdKDUzsihG9rkPFS9AvngvKd//d1nfEg0dCYsSemFmI3XHKJ2CyArzmj6rosC2HV8NTlrQACzphJCeIwvSs+sEECkietgk6oQHJNHLb9XCECKy2UXP+RDXEFyyL3nAlhnQSLsOi6AaaJleuM/61GYglcJ7D4wTP3cprSCD0SbLsUQtx6YGkujG1w3kyMm5bpgTGPaY5JHFzQ4W9bN3NIOp15+pY21tMERB45i8nYu/PYNGCyMm2HFb4KYOwt+SmiEqLOTq/5QbYC/Tlzl2bTVgVSnuFflHQfSLqyqjrhbA4mc2iFRVxVo/b/OjWWgPyWgBIKM9scvDmeBcMYi2gkFOiQpuKqklWX+vqMEaBoKN1ffGwxEzYWXSxgBOHLfP1NdPQ4Di87WHgy5hYsve61w9spECYEXHbA9B6uzotV4Qjrm+mzVWOnAwNCJa8Ql7gUo3TI504FegNcj7IaGFFnoETsSAhvYSCTuljmrzEZaH7FD8xEb+Z3KlQJjNj71bq63FbPwe5V9+t8dLNQ2OuBZ2c9E+wwC+fKJQsyvt9vX+pGJAfK2521H6KhrJopc0UjHWUYH2+Ku5eGgeflsDaDhwoMLDq2i5GJy26ae+fOycOptGGahEotwW8o1Gzvj11Y825qKXoHBP62eiom+8eROmQzUctrnRqpKwB9bAkdaIm4g73R5k9PdWGRQuS7m3bFIl8t8K32dgo6XyD7fZENw+Nbp8x5RF1CvgSi7ZTAcj0YHX9kWcAZrjC2pW3L9kPNM20d+yAOiPrsMl7zyxee97YQOU3X8UBVdvOncDly9PKVVMfsYZEh46zZzz+Hkg4EY7ixrHB1Zu+Pf3vVo1u8mfX+NKTjWPno3OuwK/wGZNEt8AQAAAACAAABABgAAMwYAAA==eJwtk3k4FHgch8fRoTA1pcOxki5SjsY8mvBNZkqODBp3cqbNMWSQjeRIVG4GkSYZmjLDNO6Z/EZbpiyLtVhmKffqkJIiYbfn2c8/79/v87wflXqZ8Nb7bmjZvf/hy3l3tFnaY716rQsirJ5/WXHYDQ0y7ZS4Ja5oZ/dbT8U2N9R9o3V4eo0T8hxKzmb6OqFnI3G4Kn8X5OvkevyNCRVJIjJSvxw8jVqkbGtC1U8jxnhGVIqjA1Io85pPzrdH13+y3Irl2KAC0o716atOoRcnhXmOxVbIrSzkFEHXAklSdM+lXjyB9MkN+CvDZMSeE6EP0cdQ1DZvxfF6MyT7UOZkkOpRZGBJql0MNkFDvx4wmpgioubJkVb8nCFSkK/YrUQ3QmYNlYvhJA1ECCBak+layFvSbu2TikGaXqbjFuvGTLNHRaYnmTiYyRA/0iZshMFfgtVmA3XA5h17+vNXPXD4/Uvg8UITSMKYy9AoJGBdKWUr51iBwV3vm9k8CqTb5F1YT7eHT8UeiYkJzvDDPrfbA5bluou8sN7Ax0t1XnzjC+JNZkXXN52Hno7CG6e3BYDctN1Ly0EahGDvLOj1XoT9Ws06y5hw4L/atZXzPhK49nrbYwSXofxsTB6HEguNXlenXGquAilyRXFxNgEWw7oyPu67BkH0321DVZNhrH/cTb33JtTVt/g/jk2D2UlJPKsxA7Baqy3wcVlAzPR8WFCTAz577HTn8Xmwi+zr/FylAOSJGvTO3UUQmEdQZawuhsUI3MZlMhPcM/OZSbR7UM7Pbrb7VALX3glT29NK4ZcggqN3MQtovj8tJMSVQ3PL3IdvbWwwFytqh6o9AoXR4A0cJQ4cDGvU2UOohN0dczFGFlUQmtrhu2LMg7MkiX6402PY+SyXH3mcD8EGD+VHg6thYAUT0MOtgZvDbzDJglrYu6lunTezDl6sfRAiy64H6jc5/zpGA1zqcso4p9MIdqxz2GppAQy2O6hdPCSEPuum/okWIWhElHVGpT6BpfjBqiC7JnCveNCMl0eQPvZJ/Q8agtu888Qj20WwWnv0lb+7CFpKpt75hojgZ7ZQbbhaBPEj4nwBQwSEKmr882ERHBw5ov/2uQja235MBGHXIhuSP4jAeUTKz4ErAqrNhnD1qyIIyRESxf+xLdYCxaiJYDY06MG2SQTL+/fbWJohUBGQ5npFTSA7eWvfe4UmiJN9nq4f+QT6I8kzKFcIMVFSX7rYAuj7tvPegclGyDZ8o6E82ABf05Q3eR9sgAI/W+nCsHoY89fss9GqA0Gne3kmoxYiWH6lQw41wFVQGv1uUw0GVWmj1y35YBQ3VR2c8Bh4DhXKiQ08OETrCX9QVgVPMIv//JlbCVaYZS1qSQWIP5qzNh56BO7cK4FZ6mzAJe5nUmzLAYv1+o6fZkEcg+up8rEUlppFYR+GS2C6TfbXhqR7YLpWagGnzQR80mGzQtViqOccMNZVKoSCGaslITsf1D8HOsZwGaAo2eJHeJEDNYEcXdxAFrB+puCxnplQP1bvQHROB04J4GfHbkACZUjcpZoC3XeXLDZuTwJG5xmcPzkRkp/Nrt21NR6iBgOfzOTEguZXerjY+zIsqfbc5QsioPaI681V9HAI46wZpC2HwPsfmZ6mQY/X68280QsQxbj8N27zhf//4ge7Ju73klW84NbrgTErGVd4usIL6KU7A5+Hm60opYJt7ZJ0hQoFxBPd80jaGtTuLhoJ9EnQGJe0N+XsUeAH62WR+Ybg76jxKNpKD9qjd+f+Rl8x7RDGMm/fVoOnytQZap8MuhO8c766VQ6VgIojKX0HOrYX06u0sAelTv41EXDEAAU0+Ui2aBLRQiZXkn/tEMqlil9vtTFB+bkCuTtuZohyVGfZ55UJ4lUxPrLKzNEUL+NAisActepVu53QIaEL5hWFQ2ss0EyRYeZ3wxPoy/WBz7QqS+SjHWWN7TyFlNXemszcskPGMv33KKvsETEqU27e0B5tKTbuUt5HRZq3vsXqWTmiymb5vuoiKsoyjjaldTij0eYtghhHFyTxUC0TY1xRdtGZtQnRrmisMjZ1gH8GsV5sqE3zdEHZl/6cfTnuijKaTnYzz3ugfwE9ChMvAQAAAACAAABABgAAMAYAAA==eJwdkXdU04cexRkq4oBKrAyphGpBoFiUxw5+wbCVVXbKjswiMkQIZUMaLDIkhE0CWT8e4HtI65EC5VuZR4YILcU8HpoGpYoW9Cm1EqnPev+559xz//ncW561cm3Z59eTbYVKln0RGpDq2XFaYekgGAjrzYIZJrCgyvAaSToM278brN54aAnu/22pmXY+DmXp1dd563agCxlHdX6xheSvfL6xkFJgbkknN9XLEVr6Kfpn15zgzs6+lcN0J0guaT8fdIMK197caKygu8G/sgne8KAzRKsZzi/Tz8CRcOnqb6se8LEHeWJg0xO4mTtL1/7yhJT6+KoiwgcSUsfMDOP9YEp67wnt+OfQq+WZ5bcYBNeDH7Zw50IhZXqI+gOTBmXbVB2q3aLg3Ovfq1TGoyCNrXJ3S/ssEHMdz01VYmBa0bBApTMWJKZhus/8v4TCLzJf+LOSQN4wX8spTIYcvWDegCQFZLP6k0un0qBILg5ouJ0OKcrLTG3MgCXXWztM8xkQ3h1DdTPMgTJ7dfdSz3xQeK8CqNDpbe8PKgLSfZjab1QMzfLO8dxOJjRLm8QzaqWwLYihFEWUQojcblFgdRn4OY67VbXKwZ9QDvG+WgE6H1pLdqxVQe21tqatwmoYO1CkW2PGhlt2rBP+ozUwKFkZe1nCAWvTrNmgqlowOF/QsC6tgwM/1hQq0xohZis2uu+DJgjsNxBa7GiB75SogTeyuVBBi9oMp7bCxkbOdJqkFej0cFfdnjaY07oq6FDlg5VNztylbQJ43Pes+MU/BeBVb9bI+V0ACluD+S9kQghn1vD85UJ4V/Kb7hLBbifvCeHXYnA48ZGt/boYTE7YklXlYggbaruRlUXADD/TWMol4KCEU3slm4DGdamhWisBms9ODLuEENDnkbkgqSIgbahktiuJAFaiR4+aKwEMu6GEm2ViYHSPJvMCxJAVwdnNyReByZCnCydKCCFLqzaPcwUwqnDJwGeEDzunqOKcnXwo4VkX5N3ngSxjq2ipuwUCzoh4KReboLKi80pYQgP4D+d5d/lxwPeu86yyHhvmp2i73OSVQFI/2pTGZEGDLPKTedNCWBPOBDvfyoCG8+aT/plfgKwuwHxMFo37khRdKHkXcILVmvgysQD7T+l9SqeysG9QXUXVtwJL38fVqBWa7vp2koObeYkDF9j1SHZ8Tp8Ka0JrJmeXcQcXx0mOzSxSK5Yav9G+19WGifHK3Yr7+DhQW6WebSnA10UHNMz6hLjioH79nJYIbTMefktRF+PayXHXMnMxknvcSOsKBMY1dm+dvUzgsma4+/9CCYy4c0rJpY5Aer7EnhHcjtxavd4JUjv+O/tHytkJAr9RfvRqq4lAtmyZ1PNCjE6ifeZyihg571698M65eT6aRjUi/Hyv3P6alwhbDxSzEu4LsSXu6WnLQ0KsK7/92qhCgAY6QqnRAz7em8xN20/mo9/TeN3VzDbsTv8ptvnrVqRoumT79vNwr8Uu99gNLtZ4HalPjG1BduXSdo9dzbj4J4mz98tGHP7JJEZbVo+abj5vtNLr0LBY8GDephYvtzXHB+lz8PHCL95vQ9gYma7GVfWsxqCIsA/bR6tw1rEu5ZFpBY6mZCiMhJXj+HPqO5IyJO+hvDp07BIavR+ChQsil0dxq0wE55FiXY9izCCNRapbFeIDxYNjbHY+DlWOXolezMUiWtyC1sxXaHKe/5x3i4FPfjhlFtyficuxSpXf52Rgl4WNvrZmOrY/7fiD9yQVlQKD+6Y2kzHGRlX0WUkS0v7xZ2D+/USMNfkZTDtjsCvh6FvhEzrKSt8yPwuLxoGQ4lcB30eiX5ywZuxQJIr0G0bUS2i4p/OjxILMIAz0mHmpQQ/BwzbeJnbf+qF28N9Evtjje9yo4ZUfMi+8cWCZe+F28gpjr+dpPBMqDShe80A9jZzFmI/d8Y/eieSbV13w4rB2iv9FKiYvmeXd/Y8Tei+PRqzkOqHXRmj5JbID/kyVKOxjOSLzWK+vsZI1fuDksz/pjD2aehmdY/xlhYriPbp35izQnR9gQUs9hldJFGOBpSWO8ZJv3j7yKW7qddhuVJPxtIs1cVJJA9Msm60IxuTJ/wO2XgiEAQAAAACAAABABgAA5QMAAA==eJwtVHtM01cUdvM5R5jRhpmx+dwYpRR+FWRRZHwFFcEoVASRMkIdk6YuWFBgPCwWLM9ioQ/KNGzB94xxqJshxi2Lmjk3Z7aM6BxRQ8wyDXOQ+Jqiy37X795/Ts7rO+eee+6X1REsnXnegOtXHmfffseAS5Xffv7GaAzWbpqRt0RjgLbAc+5hi7S/ZsBc14hp4LNobJ3Z+N2PRgX1trPbfT1x2GbtuleXrOCpQzX8poVqnT2pOxJZAn+iDusG5rhGyhS8Lgrt12PasTfzi8cjGT9Lwdjh71e/90oUBGyfK5b4w9H4N/v2wb2TFOxbcfr+c38cypKmX9vfH4uUoj9/WTAej7sRhmnH6pYiPPbG21PmJ6DwTHrIy2YjRPtftSzDquEazfGpRixv//iv8epUzO8vt3a9tRy5ofqTvclpEOYvTBmUL62Gim5PaluLlWq5QWsWHjwf/OTubhPvV5LNuEsbINpPrM/DZnHCzJggTv8HOGBXGwwvgmjT3mvhvN7/ELWa42nDZz6CGINprJh9lVgRJ85EG/0NUtpKaa+y42+TmvFqGXGulrOOexvfBRWcx50KnH8YWeC5WQUBm5ZUjZ8vq2dnLfvYuAOPVPe5NfV8h6qdENecPuSU82yAihZZENsIUb7Gtgui3Jx6F+v+7oIwawqa2E94C/HD2mg/2ka8jnbijLqp3+vAnk/F8VA+8bD/ok7qxi7eU+ulnuqlnunjXP/wMV7x07/FTz0+QH9UgHqG1Jd2M+5agHKkm33mdTPuapDyTpDx1iDr3ZD2gR7aHT3MexSkPCrj0qX/WZD4Lmk3y/xSKW0yb4+sHyb1ugDj1f5e6A/81Bv9xHX7aR+T97/so98i5zDopd/hpb+ni3qIlJ2dtK/vZN4pD/ciZDf37Ws39yGnnXv4Qyv3bUIr321hC+Oam7gXm5r4/hEu+pN2MX9uI/GnNnCfmp18b63cq4sO1j20g3Gzark3zTXEDalm3uRK1ttaQVm7Xf6Tcub5yri3B+2839lS+k9u4T9T/82Ld7CUMM61mXW9xfSnFvM/ey3c09BC9mE2s4+xfM4hL598MpSDxYJA9uVA1xx2/cqX68g76zNxaO+Fef0NmfipTzX0ZvCewVVQWS43dE06jqj01XoiBf/UJS8uzDfioqoaZ6TI/7UMU5yB1HZ3ouS/BPy6YOiJwxaP/1R6iTAkSByF/28wWvLdIuqaGOLNi4KgrdHDOvbxjZb6uzryaaKO/3aFXvJmDFTjrcwOPfnUooegSWeOnvycG0PedCpYKNp5psj5L6K/0gAxhsdx8RA0P/uC5OU+Hfs+YcD/fPOznA==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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AQAAAACAAAAoUwAAWwIAAA==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AgAAAACAAACMAgAAZRsAABIBAAA=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AQAAAACAAAAoUwAAzQ0AAA==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AQAAAACAAABlCgAAGgAAAA==eJztwSEBAAAAwyC9/oVf4hIoAAA4G4r2XY4=
26
+ </AppendedData>
27
+ </VTKFile>
CylinderKnMa/Kn0p28/simulation0579_Kn0p28Ma4p8/Surf.pvd ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ <?xml version="1.0"?>
2
+ <VTKFile type="Collection" version="0.1"
3
+ byte_order="LittleEndian"
4
+ compressor="vtkZLibDataCompressor">
5
+ <Collection>
6
+ <DataSet timestep="300000" group="" part="0"
7
+ file="Surf/Surf_300000.vtu"/>
8
+ </Collection>
9
+ </VTKFile>
CylinderKnMa/Kn0p28/simulation0579_Kn0p28Ma4p8/config.txt ADDED
@@ -0,0 +1,78 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ variable BZ equal 1.380649E-23
2
+ variable PI equal 3.1415926536
3
+ variable molecular_mass equal 6.63E-26
4
+ variable molecular_diameter equal 4.17E-10
5
+ variable gamma equal 1.666666667
6
+ variable R equal ${BZ}/${molecular_mass}
7
+ variable L equal 1.0
8
+ variable xmin equal -5.0
9
+ variable xmax equal 6.0
10
+ variable ymin equal -5.0
11
+ variable ymax equal 5.0
12
+ variable Kn equal 0.28
13
+ variable Ma equal 4.800000000000001
14
+ variable To equal 273.0
15
+ variable Tb equal 273.0
16
+ variable theta equal 0.0
17
+ variable mfp equal ${Kn}*${L}
18
+ variable cpmfp equal 4
19
+ variable nden equal 1.0/sqrt(2.0)/${PI}/${molecular_diameter}/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
20
+ variable sos equal sqrt(${gamma}*${R}*${To})
21
+ variable vo equal ${Ma}*${sos}
22
+ variable vx equal ${vo}*cos(${theta}*2*PI/360)
23
+ variable vy equal ${vo}*sin(${theta}*2*PI/360)
24
+ variable ppc equal 30
25
+ variable xncells equal (${xmax}-${xmin})/${mfp}*${cpmfp}
26
+ variable yncells equal (${ymax}-${ymin})/${mfp}*${cpmfp}
27
+ variable Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
28
+ variable tstep equal (-${xmin}+${xmax})/${vx}/${xncells}/10/4
29
+ variable nave equal 10000
30
+ variable noutput equal 300000
31
+ clear
32
+ shell mkdir output
33
+ shell mkdir grid
34
+ shell mkdir surf
35
+ seed 7
36
+ dimension 2
37
+ global nrho ${nden}
38
+ global fnum ${Fnum}
39
+ timestep ${tstep}
40
+ global gridcut 1.0 particle/reorder 100 comm/sort yes
41
+ region 1 cylinder z 0.0 0.0 3.50 -0.5 0.5
42
+ region 2 cylinder z 0.0 0.0 2.00 -0.5 0.5
43
+ region 3 cylinder z 0.0 0.0 0.80 -0.5 0.5
44
+ boundary o o p
45
+ create_box ${xmin} ${xmax} ${ymin} ${ymax} -0.5 0.5
46
+ create_grid ${xncells} ${yncells} 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
47
+ balance_grid rcb cell
48
+ species gas.species Ar
49
+ mixture air Ar frac 1.0
50
+ mixture air Ar vstream ${vx} ${vy} 0.0 temp ${To}
51
+ collide vss air gas.vhs
52
+ collide_modify vremax 100 yes remain no nearcp yes 10
53
+ read_surf cylinder.surf
54
+ surf_collide 1 diffuse 273.0 1.0
55
+ surf_modify all collide 1
56
+ fix in emit/face air xlo ylo yhi
57
+ balance_grid rcb cell
58
+ create_particles air n 0
59
+ stats 10000
60
+ stats_style step cpu np nattempt ncoll nscoll npave nscollave
61
+ run 200000
62
+ compute 1 grid all air n nrho massrho u v w
63
+ compute 2 grid all air trot
64
+ compute 3 tvib/grid all air
65
+ compute 4 thermal/grid all air press temp
66
+ fix 1 ave/grid all 1 ${nave} ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
67
+ dump 1 grid all ${noutput} output/grid.*.dat id xc yc f_1[*]
68
+ dump_modify 1 format float %12.5g
69
+ compute 5 surf all air n press px py shx shy fx fy etot erot evib
70
+ fix 2 ave/surf all 1 ${nave} ${nave} c_5[*] ave running
71
+ dump 2 surf all ${noutput} output/surf.*.dat id v1x v1y v2x v2y f_2[*]
72
+ dump_modify 2 format float %12.5g
73
+ compute 6 lambda/grid f_1[2] f_1[8] Ar kx
74
+ dump 3 grid all ${noutput} output/lambdakn.*.dat id xc yc c_6[*]
75
+ dump_modify 3 format float %12.5g
76
+ run 100000
77
+ write_grid grid/final-grid.dat
78
+ write_surf surf/geom.surf
CylinderKnMa/Kn0p28/simulation0579_Kn0p28Ma4p8/cylinder.surf ADDED
@@ -0,0 +1,410 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ surf file from Pointwise
2
+
3
+ 200 points
4
+ 200 lines
5
+
6
+ Points
7
+
8
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CylinderKnMa/Kn0p28/simulation0579_Kn0p28Ma4p8/gas.species ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Species data
2
+
3
+ # species name
4
+ # molecular weight (atomic mass units, e.g. 16 for oxygen)
5
+ # molecular mass (kg)
6
+ # rotational degrees of freedom (integer, unitless)
7
+ # inverse rotational relaxtion number (unitless)
8
+ # vibrational degrees of freedom (integer, unitless)
9
+ # inverse vibrational relaxation number (unitless)
10
+ # vibrational temperature (K)
11
+ # species weight (unitless)
12
+ # multiple of electon charge (1 for a proton)
13
+
14
+ Ar 39.95 6.63E-26 0 0.0 0 0.0 0.0 1.0 0.0