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  1. .gitattributes +5 -0
  2. CylinderKnMa/Kn0p26/simulation0536_Kn0p26Ma5p5/output/grid.300000.dat +3 -0
  3. CylinderKnMa/Kn0p26/simulation0537_Kn0p26Ma5p6/output/grid.300000.dat +3 -0
  4. CylinderKnMa/Kn0p26/simulation0538_Kn0p26Ma5p7/output/grid.300000.dat +3 -0
  5. CylinderKnMa/Kn0p26/simulation0539_Kn0p26Ma5p8/output/grid.300000.dat +3 -0
  6. CylinderKnMa/Kn0p26/simulation0544_Kn0p26Ma6p3/output/grid.300000.dat +3 -0
  7. CylinderKnMa/Kn0p28/simulation0588_Kn0p28Ma5p7/Lambda/Lambda_1_300000.vtu +0 -0
  8. CylinderKnMa/Kn0p28/simulation0588_Kn0p28Ma5p7/Lambda/Lambda_2_300000.vtu +0 -0
  9. CylinderKnMa/Kn0p28/simulation0588_Kn0p28Ma5p7/Lambda/Lambda_300000.pvtu +21 -0
  10. CylinderKnMa/Kn0p28/simulation0588_Kn0p28Ma5p7/Lambda/Lambda_3_300000.vtu +27 -0
  11. CylinderKnMa/Kn0p28/simulation0588_Kn0p28Ma5p7/output/lambdakn.300000.dat +0 -0
  12. CylinderKnMa/Kn0p28/simulation0588_Kn0p28Ma5p7/output/surf.300000.dat +209 -0
  13. CylinderKnMa/Kn0p28/simulation0588_Kn0p28Ma5p7/surf/Surf_300000.vtu +38 -0
  14. CylinderKnMa/Kn0p28/simulation0588_Kn0p28Ma5p7/surf/geom.surf +610 -0
  15. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/Grid.pvd +9 -0
  16. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/Lambda.pvd +9 -0
  17. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/Lambda/Lambda_0_300000.vtu +0 -0
  18. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/Lambda/Lambda_1_300000.vtu +0 -0
  19. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/Lambda/Lambda_2_300000.vtu +0 -0
  20. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/Lambda/Lambda_300000.pvtu +21 -0
  21. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/Lambda/Lambda_3_300000.vtu +27 -0
  22. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/Surf.pvd +9 -0
  23. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/config.txt +78 -0
  24. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/cylinder.surf +410 -0
  25. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/gas.species +14 -0
  26. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/gas.vhs +9 -0
  27. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/grid/Grid_0_300000.vtu +0 -0
  28. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/grid/Grid_1_300000.vtu +0 -0
  29. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/grid/Grid_2_300000.vtu +0 -0
  30. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/grid/Grid_300000.pvtu +29 -0
  31. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/grid/Grid_3_300000.vtu +0 -0
  32. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/grid/final-grid.dat +0 -0
  33. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/log.sparta +319 -0
  34. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/mir.txt +3 -0
  35. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/output/lambdakn.300000.dat +0 -0
  36. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/output/surf.300000.dat +209 -0
  37. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/runmpirun128.sh +18 -0
  38. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/runmpirun64.sh +18 -0
  39. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/slurm-28429294.out +205 -0
  40. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/surf/Surf_300000.vtu +38 -0
  41. CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/surf/geom.surf +610 -0
  42. CylinderKnMa/Kn0p28/simulation0590_Kn0p28Ma5p9/Grid.pvd +9 -0
  43. CylinderKnMa/Kn0p28/simulation0590_Kn0p28Ma5p9/Lambda.pvd +9 -0
  44. CylinderKnMa/Kn0p28/simulation0590_Kn0p28Ma5p9/Lambda/Lambda_0_300000.vtu +0 -0
  45. CylinderKnMa/Kn0p28/simulation0590_Kn0p28Ma5p9/Lambda/Lambda_1_300000.vtu +0 -0
  46. CylinderKnMa/Kn0p28/simulation0590_Kn0p28Ma5p9/Lambda/Lambda_2_300000.vtu +0 -0
  47. CylinderKnMa/Kn0p28/simulation0590_Kn0p28Ma5p9/Lambda/Lambda_300000.pvtu +21 -0
  48. CylinderKnMa/Kn0p28/simulation0590_Kn0p28Ma5p9/Lambda/Lambda_3_300000.vtu +27 -0
  49. CylinderKnMa/Kn0p28/simulation0590_Kn0p28Ma5p9/Surf.pvd +9 -0
  50. CylinderKnMa/Kn0p28/simulation0590_Kn0p28Ma5p9/config.txt +78 -0
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AQAAAACAAAAoUwAAWwIAAA==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AQAAAACAAAAoUwAAzQ0AAA==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AQAAAACAAABlCgAAGgAAAA==eJztwSEBAAAAwyC9/oVf4hIoAAA4G4r2XY4=
26
+ </AppendedData>
27
+ </VTKFile>
CylinderKnMa/Kn0p28/simulation0588_Kn0p28Ma5p7/output/lambdakn.300000.dat ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0588_Kn0p28Ma5p7/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 0.004 0.13689 -0.13687 0.0021501 0.00011715 0.0074573 -0.002148 0.00015091 26.414 0 0
11
+ 129 -0.31871 0.38526 -0.30645 0.39508 0.16863 5.9407 3.7144 -4.6363 0.82506 0.661 0.071303 -0.062442 1499.4 0 0
12
+ 2 0.49975 -0.015705 0.49901 -0.031395 0.00407 0.13764 -0.13749 0.0064838 0.00040469 0.0085815 -0.0021532 0.00023663 30.121 0 0
13
+ 130 -0.30645 0.39508 -0.29389 0.40451 0.15878 5.5681 3.3432 -4.4527 0.87075 0.65378 0.06619 -0.059672 1421.3 0 0
14
+ 3 0.49901 -0.031395 0.49778 -0.047054 0.00339 0.11669 -0.11633 0.0091554 -0.00023423 -0.0029761 -0.0018309 9.706e-05 30.185 0 0
15
+ 131 -0.29389 0.40451 -0.28104 0.41354 0.15548 5.4905 3.1571 -4.4921 0.8489 0.59661 0.062923 -0.061187 1430.2 0 0
16
+ 4 0.49778 -0.047054 0.49606 -0.062667 0.00424 0.14433 -0.14346 0.015838 -0.00064925 -0.0058809 -0.0022636 0.0001564 32.892 0 0
17
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AQAAAACAAABABgAAzwUAAA==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AQAAAACAAABABgAA3QUAAA==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AQAAAACAAABABgAABAYAAA==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AQAAAACAAABABgAAEwYAAA==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AQAAAACAAABABgAAJQYAAA==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AQAAAACAAABABgAANAYAAA==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AQAAAACAAABABgAANgYAAA==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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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AQAAAACAAAAoUwAAWwIAAA==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AgAAAACAAACMAgAAZRsAABIBAAA=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AQAAAACAAAAoUwAAzQ0AAA==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AQAAAACAAABlCgAAGgAAAA==eJztwSEBAAAAwyC9/oVf4hIoAAA4G4r2XY4=
26
+ </AppendedData>
27
+ </VTKFile>
CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/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/simulation0589_Kn0p28Ma5p8/config.txt ADDED
@@ -0,0 +1,78 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ variable BZ equal 1.380649E-23
2
+ variable PI equal 3.1415926536
3
+ variable molecular_mass equal 6.63E-26
4
+ variable molecular_diameter equal 4.17E-10
5
+ variable gamma equal 1.666666667
6
+ variable R equal ${BZ}/${molecular_mass}
7
+ variable L equal 1.0
8
+ variable xmin equal -5.0
9
+ variable xmax equal 6.0
10
+ variable ymin equal -5.0
11
+ variable ymax equal 5.0
12
+ variable Kn equal 0.28
13
+ variable Ma equal 5.800000000000001
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/simulation0589_Kn0p28Ma5p8/cylinder.surf ADDED
@@ -0,0 +1,410 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ surf file from Pointwise
2
+
3
+ 200 points
4
+ 200 lines
5
+
6
+ Points
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+
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CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/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/simulation0589_Kn0p28Ma5p8/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/simulation0589_Kn0p28Ma5p8/grid/Grid_0_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/grid/Grid_1_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/grid/Grid_2_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/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/simulation0589_Kn0p28Ma5p8/grid/Grid_3_300000.vtu ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/grid/final-grid.dat ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/log.sparta ADDED
@@ -0,0 +1,319 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ SPARTA (4 Sep 2024)
2
+ Running on 128 MPI task(s)
3
+ variable BZ equal 1.380649E-23
4
+ variable PI equal 3.1415926536
5
+ variable molecular_mass equal 6.63E-26
6
+ variable molecular_diameter equal 4.17E-10
7
+ variable gamma equal 1.666666667
8
+ variable R equal ${BZ}/${molecular_mass}
9
+ variable R equal 1.380649e-23/${molecular_mass}
10
+ variable R equal 1.380649e-23/6.63e-26
11
+ variable L equal 1.0
12
+ variable xmin equal -5.0
13
+ variable xmax equal 6.0
14
+ variable ymin equal -5.0
15
+ variable ymax equal 5.0
16
+ variable Kn equal 0.28
17
+ variable Ma equal 5.800000000000001
18
+ variable To equal 273.0
19
+ variable Tb equal 273.0
20
+ variable theta equal 0.0
21
+ variable mfp equal ${Kn}*${L}
22
+ variable mfp equal 0.28*${L}
23
+ variable mfp equal 0.28*1
24
+ variable cpmfp equal 4
25
+ variable nden equal 1.0/sqrt(2.0)/${PI}/${molecular_diameter}/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
26
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/${molecular_diameter}/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
27
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
28
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(${mfp}/${cpmfp}*${Kn})
29
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.28/${cpmfp}*${Kn})
30
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.28/4*${Kn})
31
+ variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.28/4*0.28)
32
+ variable sos equal sqrt(${gamma}*${R}*${To})
33
+ variable sos equal sqrt(1.666666667*${R}*${To})
34
+ variable sos equal sqrt(1.666666667*208.242684766214*${To})
35
+ variable sos equal sqrt(1.666666667*208.242684766214*273)
36
+ variable vo equal ${Ma}*${sos}
37
+ variable vo equal 5.8*${sos}
38
+ variable vo equal 5.8*307.815564238681
39
+ variable vx equal ${vo}*cos(${theta}*2*PI/360)
40
+ variable vx equal 1785.33027258435*cos(${theta}*2*PI/360)
41
+ variable vx equal 1785.33027258435*cos(0*2*PI/360)
42
+ variable vy equal ${vo}*sin(${theta}*2*PI/360)
43
+ variable vy equal 1785.33027258435*sin(${theta}*2*PI/360)
44
+ variable vy equal 1785.33027258435*sin(0*2*PI/360)
45
+ variable ppc equal 30
46
+ variable xncells equal (${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}/${xncells}/10/4
68
+ variable tstep equal (--5+6)/1785.33027258435/${xncells}/10/4
69
+ variable tstep equal (--5+6)/1785.33027258435/157.142857142857/10/4
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 9.80210791735915e-07
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 = 0.136839 secs
101
+ create/ghost percent = 0.899184 99.1008
102
+ balance_grid rcb cell
103
+ Balance grid migrated 97380 cells
104
+ CPU time = 0.110024 secs
105
+ reassign/sort/migrate/ghost percent = 51.3402 0.0309559 8.00807 40.6208
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 1785.33027258435 ${vy} 0.0 temp ${To}
110
+ mixture air Ar vstream 1785.33027258435 0 0.0 temp ${To}
111
+ mixture air Ar vstream 1785.33027258435 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 = 0.116411 secs
125
+ read/check/sort/surf2grid/ghost/inout/particle percent = 19.1384 19.0692 3.23161 21.9283 36.6325 6.56717 0.130864
126
+ surf2grid time = 0.025527 secs
127
+ map/comm1/comm2/comm3/comm4/split percent = 14.7032 23.9004 6.38212 2.19465 11.8529 6.54391
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 = 0.0541556 secs
134
+ reassign/sort/migrate/ghost percent = 5.96867 0.109592 16.2252 77.6965
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 = 0.0167998 secs
139
+ stats 10000
140
+ stats_style step cpu np nattempt ncoll nscoll npave nscollave
141
+ run 200000
142
+ Memory usage per proc in Mbytes:
143
+ particles (ave,min,max) = 1.79297 0 3.375
144
+ grid (ave,min,max) = 4.297 1.51379 7.13879
145
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
146
+ total (ave,min,max) = 6.11057 3.22189 8.84689
147
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
148
+ 0 0 668660 0 0 0 0 0
149
+ 10000 17.252868 737904 11938 10438 22 696044.67 20.8439
150
+ 20000 41.567902 746193 12004 10552 22 720099.84 21.09575
151
+ 30000 65.58644 746447 12027 10554 19 728864.25 21.198233
152
+ 40000 89.78262 746207 12019 10586 25 733294.71 21.232675
153
+ 50000 113.98198 746019 12080 10630 20 735822.62 21.25064
154
+ 60000 138.39743 746724 12057 10581 26 737667.2 21.266367
155
+ 70000 162.61819 746402 12165 10673 23 738897.81 21.274257
156
+ 80000 186.25438 745855 12050 10641 25 739845.94 21.282663
157
+ 90000 211.33731 746037 12115 10574 20 740580.2 21.282267
158
+ 100000 235.58057 746029 11965 10520 17 741151.82 21.28863
159
+ 110000 259.96001 746887 12108 10632 21 741631.78 21.299782
160
+ 120000 284.56373 746605 12124 10611 25 742056.54 21.311775
161
+ 130000 308.49703 745638 12215 10776 20 742366.86 21.316115
162
+ 140000 332.49903 746264 12023 10551 25 742645.55 21.317443
163
+ 150000 356.58114 745964 12164 10702 22 742880.33 21.321547
164
+ 160000 380.06231 745943 11927 10559 14 743088.88 21.326319
165
+ 170000 405.34508 746546 11946 10506 22 743290.47 21.327994
166
+ 180000 429.46795 746315 12208 10745 17 743452.82 21.332428
167
+ 190000 453.42335 746554 12179 10682 20 743615.67 21.330768
168
+ 200000 478.26601 746003 12030 10598 19 743748.72 21.33095
169
+ Loop time of 478.267 on 128 procs for 200000 steps with 746003 particles
170
+
171
+ MPI task timing breakdown:
172
+ Section | min time | avg time | max time |%varavg| %total
173
+ ---------------------------------------------------------------
174
+ Move | 0.024566 | 18.406 | 124.42 | 567.8 | 3.85
175
+ Coll | 0.49336 | 17.743 | 182.43 | 645.1 | 3.71
176
+ Sort | 0.16754 | 3.6386 | 35.869 | 289.0 | 0.76
177
+ Comm | 88.941 | 129.08 | 144.09 | 100.3 | 26.99
178
+ Modify | 0.020308 | 0.15253 | 2.8192 | 106.9 | 0.03
179
+ Output | 0.0048571 | 0.01888 | 0.021223 | 1.6 | 0.00
180
+ Other | | 309.2 | | | 64.66
181
+
182
+ Particle moves = 148749744881 (149B)
183
+ Cells touched = 155372900796 (155B)
184
+ Particle comms = 247741659 (248M)
185
+ Boundary collides = 0 (0K)
186
+ Boundary exits = 23859678 (23.9M)
187
+ SurfColl checks = 255699936 (256M)
188
+ SurfColl occurs = 4266190 (4.27M)
189
+ Surf reactions = 0 (0K)
190
+ Collide attempts = 2871819622 (2.87B)
191
+ Collide occurs = 2233751648 (2.23B)
192
+ Reactions = 0 (0K)
193
+ Particles stuck = 0
194
+ Axisymm bad moves = 0
195
+
196
+ Particle-moves/CPUsec/proc: 2.42983e+06
197
+ Particle-moves/step: 743749
198
+ Cell-touches/particle/step: 1.04453
199
+ Particle comm iterations/step: 1
200
+ Particle fraction communicated: 0.00166549
201
+ Particle fraction colliding with boundary: 0
202
+ Particle fraction exiting boundary: 0.000160401
203
+ Surface-checks/particle/step: 0.00171899
204
+ Surface-collisions/particle/step: 2.86803e-05
205
+ Surf-reactions/particle/step: 0
206
+ Collision-attempts/particle/step: 0.0193064
207
+ Collisions/particle/step: 0.0150168
208
+ Reactions/particle/step: 0
209
+
210
+ Particles: 5828.15 ave 41360 max 0 min
211
+ Histogram: 84 16 6 10 2 6 0 2 0 2
212
+ Cells: 762.5 ave 763 max 762 min
213
+ Histogram: 64 0 0 0 0 0 0 0 0 64
214
+ GhostCell: 19721.7 ave 36096 max 1099 min
215
+ Histogram: 20 10 12 10 18 2 6 4 16 30
216
+ EmptyCell: 0 ave 0 max 0 min
217
+ Histogram: 128 0 0 0 0 0 0 0 0 0
218
+ Surfs: 200 ave 200 max 200 min
219
+ Histogram: 128 0 0 0 0 0 0 0 0 0
220
+ GhostSurf: 0 ave 0 max 0 min
221
+ Histogram: 128 0 0 0 0 0 0 0 0 0
222
+ compute 1 grid all air n nrho massrho u v w
223
+ compute 2 grid all air trot
224
+ compute 3 tvib/grid all air
225
+ compute 4 thermal/grid all air press temp
226
+ fix 1 ave/grid all 1 ${nave} ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
227
+ fix 1 ave/grid all 1 10000 ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
228
+ fix 1 ave/grid all 1 10000 10000 c_1[*] c_4[*] c_2[*] c_3[*] ave running
229
+ dump 1 grid all ${noutput} output/grid.*.dat id xc yc f_1[*]
230
+ dump 1 grid all 300000 output/grid.*.dat id xc yc f_1[*]
231
+ dump_modify 1 format float %12.5g
232
+ compute 5 surf all air n press px py shx shy fx fy etot erot evib
233
+ fix 2 ave/surf all 1 ${nave} ${nave} c_5[*] ave running
234
+ fix 2 ave/surf all 1 10000 ${nave} c_5[*] ave running
235
+ fix 2 ave/surf all 1 10000 10000 c_5[*] ave running
236
+ dump 2 surf all ${noutput} output/surf.*.dat id v1x v1y v2x v2y f_2[*]
237
+ dump 2 surf all 300000 output/surf.*.dat id v1x v1y v2x v2y f_2[*]
238
+ dump_modify 2 format float %12.5g
239
+ compute 6 lambda/grid f_1[2] f_1[8] Ar kx
240
+ dump 3 grid all ${noutput} output/lambdakn.*.dat id xc yc c_6[*]
241
+ dump 3 grid all 300000 output/lambdakn.*.dat id xc yc c_6[*]
242
+ dump_modify 3 format float %12.5g
243
+ run 100000
244
+ Memory usage per proc in Mbytes:
245
+ particles (ave,min,max) = 1.85889 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) = 6.43271 3.47786 9.10336
249
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
250
+ 200000 0 746003 12030 10598 0 0 0
251
+ 210000 41.248329 745318 12179 10726 20 745920.97 21.3983
252
+ 220000 82.221901 746589 12063 10656 18 746090.42 21.3723
253
+ 230000 124.33338 746421 12303 10827 26 746256.94 21.369433
254
+ 240000 165.75124 746360 12001 10537 18 746329.96 21.36155
255
+ 250000 208.10692 746152 11992 10601 17 746376.96 21.35918
256
+ 260000 249.20809 746576 12154 10718 17 746313.69 21.355233
257
+ 270000 290.65016 747057 12048 10561 15 746397.89 21.366286
258
+ 280000 333.02106 745932 12216 10726 24 746433.22 21.370262
259
+ 290000 374.60701 746241 12208 10727 25 746416.76 21.3705
260
+ 300000 417.33183 746784 12216 10745 19 746392.18 21.35821
261
+ Loop time of 417.332 on 128 procs for 100000 steps with 746784 particles
262
+
263
+ MPI task timing breakdown:
264
+ Section | min time | avg time | max time |%varavg| %total
265
+ ---------------------------------------------------------------
266
+ Move | 0.01236 | 9.3042 | 61.821 | 401.6 | 2.23
267
+ Coll | 0.24673 | 9.1146 | 99.671 | 474.3 | 2.18
268
+ Sort | 0.096639 | 1.872 | 15.835 | 199.8 | 0.45
269
+ Comm | 48.632 | 68.989 | 76.929 | 71.7 | 16.53
270
+ Modify | 3.4481 | 25.577 | 163.16 | 618.2 | 6.13
271
+ Output | 0.04293 | 0.045054 | 0.049477 | 0.6 | 0.01
272
+ Other | | 302.4 | | | 72.47
273
+
274
+ Particle moves = 74639218440 (74.6B)
275
+ Cells touched = 77959781378 (78B)
276
+ Particle comms = 124183799 (124M)
277
+ Boundary collides = 0 (0K)
278
+ Boundary exits = 11970578 (12M)
279
+ SurfColl checks = 128230101 (128M)
280
+ SurfColl occurs = 2135821 (2.14M)
281
+ Surf reactions = 0 (0K)
282
+ Collide attempts = 1449918929 (1.45B)
283
+ Collide occurs = 1127545071 (1.13B)
284
+ Reactions = 0 (0K)
285
+ Particles stuck = 0
286
+ Axisymm bad moves = 0
287
+
288
+ Particle-moves/CPUsec/proc: 1.39725e+06
289
+ Particle-moves/step: 746392
290
+ Cell-touches/particle/step: 1.04449
291
+ Particle comm iterations/step: 1
292
+ Particle fraction communicated: 0.00166379
293
+ Particle fraction colliding with boundary: 0
294
+ Particle fraction exiting boundary: 0.000160379
295
+ Surface-checks/particle/step: 0.001718
296
+ Surface-collisions/particle/step: 2.86153e-05
297
+ Surf-reactions/particle/step: 0
298
+ Collision-attempts/particle/step: 0.0194257
299
+ Collisions/particle/step: 0.0151066
300
+ Reactions/particle/step: 0
301
+
302
+ Particles: 5834.25 ave 41303 max 0 min
303
+ Histogram: 84 16 6 10 2 6 0 2 0 2
304
+ Cells: 762.5 ave 763 max 762 min
305
+ Histogram: 64 0 0 0 0 0 0 0 0 64
306
+ GhostCell: 19721.7 ave 36096 max 1099 min
307
+ Histogram: 20 10 12 10 18 2 6 4 16 30
308
+ EmptyCell: 0 ave 0 max 0 min
309
+ Histogram: 128 0 0 0 0 0 0 0 0 0
310
+ Surfs: 200 ave 200 max 200 min
311
+ Histogram: 128 0 0 0 0 0 0 0 0 0
312
+ GhostSurf: 0 ave 0 max 0 min
313
+ Histogram: 128 0 0 0 0 0 0 0 0 0
314
+ write_grid grid/final-grid.dat
315
+ grid cells = 97600
316
+ CPU time = 0.0137576 secs
317
+ write_surf surf/geom.surf
318
+ surf elements = 200
319
+ CPU time = 0.00174861 secs
CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/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/simulation0589_Kn0p28Ma5p8/output/lambdakn.300000.dat ADDED
The diff for this file is too large to render. See raw diff
 
CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/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 0.00384 0.13263 -0.13261 0.0020832 -5.3591e-06 -0.00034114 -0.002083 2.7363e-05 30.136 0 0
11
+ 129 -0.31871 0.38526 -0.30645 0.39508 0.17301 6.2232 3.891 -4.8568 0.8799 0.70493 0.074938 -0.065214 1601.9 0 0
12
+ 2 0.49975 -0.015705 0.49901 -0.031395 0.00384 0.13349 -0.13335 0.0062884 -0.00031183 -0.0066122 -0.0020994 -5.086e-06 30.731 0 0
13
+ 130 -0.30645 0.39508 -0.29389 0.40451 0.16442 5.9635 3.5806 -4.7689 0.89785 0.67412 0.070344 -0.064318 1553.6 0 0
14
+ 3 0.49901 -0.031395 0.49778 -0.047054 0.0039 0.13083 -0.13043 0.010265 -0.00026482 -0.0033648 -0.0020528 0.00010838 28.634 0 0
15
+ 131 -0.29389 0.40451 -0.28104 0.41354 0.15371 5.5523 3.1926 -4.5426 0.90377 0.63518 0.064343 -0.061375 1435.9 0 0
16
+ 4 0.49778 -0.047054 0.49606 -0.062667 0.00414 0.14075 -0.1399 0.015445 0.00011706 0.0010603 -0.0021956 0.00025926 32.266 0 0
17
+ 132 -0.28104 0.41354 -0.26791 0.42216 0.1487 5.3731 2.95 -4.4909 0.91368 0.60018 0.060687 -0.061112 1422.3 0 0
18
+ 5 0.49606 -0.062667 0.49384 -0.078217 0.00394 0.13405 -0.13272 0.018888 0.00043396 0.0030492 -0.0020778 0.00034458 34.367 0 0
19
+ 133 -0.26791 0.42216 -0.25452 0.43037 0.13925 4.9847 2.6045 -4.2502 0.90063 0.55191 0.055056 -0.058089 1307.2 0 0
20
+ 6 0.49384 -0.078217 0.49114 -0.093691 0.00367 0.12188 -0.12006 0.020954 0.0010314 0.0059096 -0.0018696 0.00042196 30.645 0 0
21
+ 134 -0.25452 0.43037 -0.24088 0.43815 0.13007 4.6777 2.3176 -4.0632 0.92729 0.52892 0.050969 -0.055514 1265.7 0 0
22
+ 7 0.49114 -0.093691 0.48796 -0.10907 0.0036 0.12239 -0.11985 0.024819 0.00075089 0.0036259 -0.0018707 0.0004468 27.879 0 0
23
+ 135 -0.24088 0.43815 -0.227 0.4455 0.12292 4.4221 2.0692 -3.9081 0.90405 0.47867 0.046702 -0.053867 1167.2 0 0
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+ 8 0.48796 -0.10907 0.48429 -0.12434 0.00358 0.12418 -0.12075 0.02899 -0.0012955 -0.0053962 -0.001917 0.00037059 29.622 0 0
25
+ 136 -0.227 0.4455 -0.21289 0.45241 0.117 4.1992 1.8474 -3.771 0.89465 0.43829 0.04307 -0.052348 1146.3 0 0
26
+ 9 0.48429 -0.12434 0.48015 -0.1395 0.00344 0.11217 -0.10819 0.029598 0.0022861 0.0083566 -0.0016635 0.00059616 23.423 0 0
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+ 137 -0.21289 0.45241 -0.19857 0.45888 0.10909 3.9076 1.608 -3.5614 0.89077 0.4022 0.03925 -0.049623 1048.1 0 0
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+ 10 0.48015 -0.1395 0.47553 -0.15451 0.00348 0.11437 -0.10931 0.033629 0.0019174 0.0062325 -0.0016869 0.00062612 31.006 0 0
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+ 138 -0.19857 0.45888 -0.18406 0.46489 0.10321 3.7097 1.4197 -3.4274 0.86956 0.36018 0.035957 -0.048177 998.97 0 0
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+ 11 0.47553 -0.15451 0.47044 -0.16937 0.00324 0.10709 -0.10131 0.034688 0.0025504 0.0074492 -0.0015513 0.00066186 24.682 0 0
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+ 139 -0.18406 0.46489 -0.16937 0.47044 0.09753 3.5196 1.2441 -3.2924 0.89768 0.3392 0.033641 -0.046386 990.3 0 0
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+ 12 0.47044 -0.16937 0.46489 -0.18406 0.00331 0.11208 -0.10484 0.039616 0.0023972 0.0063441 -0.0016091 0.00072191 28.409 0 0
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+ 140 -0.16937 0.47044 -0.15451 0.47553 0.08989 3.2219 1.0436 -3.0482 0.85255 0.29189 0.029784 -0.043294 913.08 0 0
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+ 13 0.46489 -0.18406 0.45888 -0.19857 0.00313 0.10634 -0.098249 0.040696 0.006788 0.016388 -0.0014366 0.00089663 26.494 0 0
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+ 141 -0.15451 0.47553 -0.1395 0.48015 0.08541 3.056 0.89858 -2.9209 0.88444 0.27209 0.028006 -0.041605 870.79 0 0
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+ 14 0.45888 -0.19857 0.45241 -0.21289 0.00317 0.10525 -0.095923 0.043311 0.011657 0.025818 -0.0013236 0.0010858 30.584 0 0
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+ 142 -0.1395 0.48015 -0.12434 0.48429 0.07911 2.8548 0.75332 -2.7537 0.80872 0.22124 0.024535 -0.039778 807.16 0 0
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+ 15 0.45241 -0.21289 0.4455 -0.227 0.00283 0.090392 -0.081175 0.039767 0.0078177 0.015958 -0.0011522 0.00087529 24.035 0 0
39
+ 143 -0.12434 0.48429 -0.10907 0.48796 0.07277 2.6245 0.61269 -2.552 0.80709 0.19377 0.022301 -0.037042 757.67 0 0
40
+ 16 0.4455 -0.227 0.43815 -0.24088 0.00258 0.080817 -0.071423 0.037816 0.00941 0.017772 -0.00097406 0.00087315 22.342 0 0
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+ 144 -0.10907 0.48796 -0.093691 0.49114 0.06846 2.4451 0.49583 -2.3943 0.76522 0.15847 0.019808 -0.035118 719.98 0 0
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+ 17 0.43815 -0.24088 0.43037 -0.25452 0.00305 0.098656 -0.085695 0.04888 0.014522 0.025459 -0.0011179 0.0011677 26.206 0 0
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+ 145 -0.093691 0.49114 -0.078217 0.49384 0.06436 2.2917 0.39402 -2.2576 0.77784 0.13575 0.018407 -0.033329 679.18 0 0
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+ 18 0.43037 -0.25452 0.42216 -0.26791 0.00303 0.09438 -0.080472 0.049313 0.018251 0.029783 -0.00097733 0.0012424 28.492 0 0
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+ 146 -0.078217 0.49384 -0.062667 0.49606 0.05873 2.0884 0.29426 -2.0676 0.71237 0.10139 0.015811 -0.030883 623.27 0 0
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+ 19 0.42216 -0.26791 0.41354 -0.28104 0.00285 0.087665 -0.073271 0.04813 0.021171 0.032229 -0.00081836 0.0012622 30.046 0 0
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+ 147 -0.062667 0.49606 -0.047054 0.49778 0.05465 1.9476 0.21372 -1.9358 0.6993 0.077204 0.014341 -0.029194 583.28 0 0
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+ 20 0.41354 -0.28104 0.40451 -0.29389 0.00313 0.095276 -0.07795 0.054784 0.026707 0.038001 -0.00080489 0.0014574 29.473 0 0
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+ 148 -0.047054 0.49778 -0.031395 0.49901 0.04912 1.7321 0.1359 -1.7268 0.62332 0.049057 0.011925 -0.026353 504.28 0 0
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+ 21 0.40451 -0.29389 0.39508 -0.30645 0.00309 0.091621 -0.073268 0.055011 0.029574 0.039388 -0.00068632 0.0014828 30.813 0 0
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+ 149 -0.031395 0.49901 -0.015705 0.49975 0.04638 1.6489 0.077672 -1.647 0.62797 0.029615 0.011084 -0.025405 500.65 0 0
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+ 22 0.39508 -0.30645 0.38526 -0.31871 0.00294 0.090105 -0.070321 0.056337 0.031838 0.03974 -0.00060446 0.0015091 29.798 0 0
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+ 150 -0.015705 0.49975 0 0.5 0.04318 1.5324 0.02407 -1.5322 0.59665 0.009373 0.0097499 -0.02392 454.01 0 0
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+ 23 0.38526 -0.31871 0.37506 -0.33066 0.00314 0.097454 -0.074105 0.063291 0.037157 0.043506 -0.00058035 0.0016775 32.465 0 0
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+ 151 0 0.5 0.015705 0.49975 0.04078 1.4267 -0.022409 -1.4265 0.58746 -0.0092286 0.0088755 -0.022551 441.98 0 0
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+ 24 0.37506 -0.33066 0.36448 -0.34227 0.00412 0.12636 -0.09346 0.085042 0.050634 0.055646 -0.00067268 0.0022098 44.232 0 0
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+ 152 0.015705 0.49975 0.031395 0.49901 0.03574 1.276 -0.060109 -1.2746 0.55514 -0.02618 0.0077756 -0.020432 417.91 0 0
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+ 25 0.36448 -0.34227 0.35355 -0.35355 0.00421 0.13173 -0.0946 0.091674 0.057416 0.059249 -0.00058406 0.0023706 45.849 0 0
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+ 153 0.031395 0.49901 0.047054 0.49778 0.03322 1.173 -0.092034 -1.1694 0.52004 -0.040928 0.0067228 -0.019011 382.84 0 0
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CylinderKnMa/Kn0p28/simulation0589_Kn0p28Ma5p8/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/simulation0589_Kn0p28Ma5p8/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/simulation0589_Kn0p28Ma5p8/slurm-28429294.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 = 0.136839 secs
7
+ create/ghost percent = 0.899184 99.1008
8
+ Balance grid migrated 97380 cells
9
+ CPU time = 0.110024 secs
10
+ reassign/sort/migrate/ghost percent = 51.3402 0.0309559 8.00807 40.6208
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 = 0.116411 secs
22
+ read/check/sort/surf2grid/ghost/inout/particle percent = 19.1384 19.0692 3.23161 21.9283 36.6325 6.56717 0.130864
23
+ surf2grid time = 0.025527 secs
24
+ map/comm1/comm2/comm3/comm4/split percent = 14.7032 23.9004 6.38212 2.19465 11.8529 6.54391
25
+ Balance grid migrated 1938 cells
26
+ CPU time = 0.0541556 secs
27
+ reassign/sort/migrate/ghost percent = 5.96867 0.109592 16.2252 77.6965
28
+ Creating particles ...
29
+ WARNING: Created unexpected # of particles: 668660 versus 668661 (../create_particles.cpp:346)
30
+ Created 668660 particles
31
+ CPU time = 0.0167998 secs
32
+ Memory usage per proc in Mbytes:
33
+ particles (ave,min,max) = 1.79297 0 3.375
34
+ grid (ave,min,max) = 4.297 1.51379 7.13879
35
+ surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
36
+ total (ave,min,max) = 6.11057 3.22189 8.84689
37
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
38
+ 0 0 668660 0 0 0 0 0
39
+ 10000 17.252868 737904 11938 10438 22 696044.67 20.8439
40
+ 20000 41.567902 746193 12004 10552 22 720099.84 21.09575
41
+ 30000 65.58644 746447 12027 10554 19 728864.25 21.198233
42
+ 40000 89.78262 746207 12019 10586 25 733294.71 21.232675
43
+ 50000 113.98198 746019 12080 10630 20 735822.62 21.25064
44
+ 60000 138.39743 746724 12057 10581 26 737667.2 21.266367
45
+ 70000 162.61819 746402 12165 10673 23 738897.81 21.274257
46
+ 80000 186.25438 745855 12050 10641 25 739845.94 21.282663
47
+ 90000 211.33731 746037 12115 10574 20 740580.2 21.282267
48
+ 100000 235.58057 746029 11965 10520 17 741151.82 21.28863
49
+ 110000 259.96001 746887 12108 10632 21 741631.78 21.299782
50
+ 120000 284.56373 746605 12124 10611 25 742056.54 21.311775
51
+ 130000 308.49703 745638 12215 10776 20 742366.86 21.316115
52
+ 140000 332.49903 746264 12023 10551 25 742645.55 21.317443
53
+ 150000 356.58114 745964 12164 10702 22 742880.33 21.321547
54
+ 160000 380.06231 745943 11927 10559 14 743088.88 21.326319
55
+ 170000 405.34508 746546 11946 10506 22 743290.47 21.327994
56
+ 180000 429.46795 746315 12208 10745 17 743452.82 21.332428
57
+ 190000 453.42335 746554 12179 10682 20 743615.67 21.330768
58
+ 200000 478.26601 746003 12030 10598 19 743748.72 21.33095
59
+ Loop time of 478.267 on 128 procs for 200000 steps with 746003 particles
60
+
61
+ MPI task timing breakdown:
62
+ Section | min time | avg time | max time |%varavg| %total
63
+ ---------------------------------------------------------------
64
+ Move | 0.024566 | 18.406 | 124.42 | 567.8 | 3.85
65
+ Coll | 0.49336 | 17.743 | 182.43 | 645.1 | 3.71
66
+ Sort | 0.16754 | 3.6386 | 35.869 | 289.0 | 0.76
67
+ Comm | 88.941 | 129.08 | 144.09 | 100.3 | 26.99
68
+ Modify | 0.020308 | 0.15253 | 2.8192 | 106.9 | 0.03
69
+ Output | 0.0048571 | 0.01888 | 0.021223 | 1.6 | 0.00
70
+ Other | | 309.2 | | | 64.66
71
+
72
+ Particle moves = 148749744881 (149B)
73
+ Cells touched = 155372900796 (155B)
74
+ Particle comms = 247741659 (248M)
75
+ Boundary collides = 0 (0K)
76
+ Boundary exits = 23859678 (23.9M)
77
+ SurfColl checks = 255699936 (256M)
78
+ SurfColl occurs = 4266190 (4.27M)
79
+ Surf reactions = 0 (0K)
80
+ Collide attempts = 2871819622 (2.87B)
81
+ Collide occurs = 2233751648 (2.23B)
82
+ Gas reactions = 0 (0K)
83
+ Particles stuck = 0
84
+ Axisymm bad moves = 0
85
+
86
+ Particle-moves/CPUsec/proc: 2.42983e+06
87
+ Particle-moves/step: 743749
88
+ Cell-touches/particle/step: 1.04453
89
+ Particle comm iterations/step: 1
90
+ Particle fraction communicated: 0.00166549
91
+ Particle fraction colliding with boundary: 0
92
+ Particle fraction exiting boundary: 0.000160401
93
+ Surface-checks/particle/step: 0.00171899
94
+ Surface-collisions/particle/step: 2.86803e-05
95
+ Surface-reactions/particle/step: 0
96
+ Collision-attempts/particle/step: 0.0193064
97
+ Collisions/particle/step: 0.0150168
98
+ Gas-reactions/particle/step: 0
99
+
100
+ Particles: 5828.15 ave 41360 max 0 min
101
+ Histogram: 84 16 6 10 2 6 0 2 0 2
102
+ Cells: 762.5 ave 763 max 762 min
103
+ Histogram: 64 0 0 0 0 0 0 0 0 64
104
+ GhostCell: 19721.7 ave 36096 max 1099 min
105
+ Histogram: 20 10 12 10 18 2 6 4 16 30
106
+ EmptyCell: 0 ave 0 max 0 min
107
+ Histogram: 128 0 0 0 0 0 0 0 0 0
108
+ Surfs: 200 ave 200 max 200 min
109
+ Histogram: 128 0 0 0 0 0 0 0 0 0
110
+ GhostSurf: 0 ave 0 max 0 min
111
+ Histogram: 128 0 0 0 0 0 0 0 0 0
112
+ Memory usage per proc in Mbytes:
113
+ particles (ave,min,max) = 1.85889 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) = 6.43271 3.47786 9.10336
117
+ Step CPU Np Natt Ncoll Nscoll Npave Nscollave
118
+ 200000 0 746003 12030 10598 0 0 0
119
+ 210000 41.248329 745318 12179 10726 20 745920.97 21.3983
120
+ 220000 82.221901 746589 12063 10656 18 746090.42 21.3723
121
+ 230000 124.33338 746421 12303 10827 26 746256.94 21.369433
122
+ 240000 165.75124 746360 12001 10537 18 746329.96 21.36155
123
+ 250000 208.10692 746152 11992 10601 17 746376.96 21.35918
124
+ 260000 249.20809 746576 12154 10718 17 746313.69 21.355233
125
+ 270000 290.65016 747057 12048 10561 15 746397.89 21.366286
126
+ 280000 333.02106 745932 12216 10726 24 746433.22 21.370262
127
+ 290000 374.60701 746241 12208 10727 25 746416.76 21.3705
128
+ 300000 417.33183 746784 12216 10745 19 746392.18 21.35821
129
+ Loop time of 417.332 on 128 procs for 100000 steps with 746784 particles
130
+
131
+ MPI task timing breakdown:
132
+ Section | min time | avg time | max time |%varavg| %total
133
+ ---------------------------------------------------------------
134
+ Move | 0.01236 | 9.3042 | 61.821 | 401.6 | 2.23
135
+ Coll | 0.24673 | 9.1146 | 99.671 | 474.3 | 2.18
136
+ Sort | 0.096639 | 1.872 | 15.835 | 199.8 | 0.45
137
+ Comm | 48.632 | 68.989 | 76.929 | 71.7 | 16.53
138
+ Modify | 3.4481 | 25.577 | 163.16 | 618.2 | 6.13
139
+ Output | 0.04293 | 0.045054 | 0.049477 | 0.6 | 0.01
140
+ Other | | 302.4 | | | 72.47
141
+
142
+ Particle moves = 74639218440 (74.6B)
143
+ Cells touched = 77959781378 (78B)
144
+ Particle comms = 124183799 (124M)
145
+ Boundary collides = 0 (0K)
146
+ Boundary exits = 11970578 (12M)
147
+ SurfColl checks = 128230101 (128M)
148
+ SurfColl occurs = 2135821 (2.14M)
149
+ Surf reactions = 0 (0K)
150
+ Collide attempts = 1449918929 (1.45B)
151
+ Collide occurs = 1127545071 (1.13B)
152
+ Gas reactions = 0 (0K)
153
+ Particles stuck = 0
154
+ Axisymm bad moves = 0
155
+
156
+ Particle-moves/CPUsec/proc: 1.39725e+06
157
+ Particle-moves/step: 746392
158
+ Cell-touches/particle/step: 1.04449
159
+ Particle comm iterations/step: 1
160
+ Particle fraction communicated: 0.00166379
161
+ Particle fraction colliding with boundary: 0
162
+ Particle fraction exiting boundary: 0.000160379
163
+ Surface-checks/particle/step: 0.001718
164
+ Surface-collisions/particle/step: 2.86153e-05
165
+ Surface-reactions/particle/step: 0
166
+ Collision-attempts/particle/step: 0.0194257
167
+ Collisions/particle/step: 0.0151066
168
+ Gas-reactions/particle/step: 0
169
+
170
+ Particles: 5834.25 ave 41303 max 0 min
171
+ Histogram: 84 16 6 10 2 6 0 2 0 2
172
+ Cells: 762.5 ave 763 max 762 min
173
+ Histogram: 64 0 0 0 0 0 0 0 0 64
174
+ GhostCell: 19721.7 ave 36096 max 1099 min
175
+ Histogram: 20 10 12 10 18 2 6 4 16 30
176
+ EmptyCell: 0 ave 0 max 0 min
177
+ Histogram: 128 0 0 0 0 0 0 0 0 0
178
+ Surfs: 200 ave 200 max 200 min
179
+ Histogram: 128 0 0 0 0 0 0 0 0 0
180
+ GhostSurf: 0 ave 0 max 0 min
181
+ Histogram: 128 0 0 0 0 0 0 0 0 0
182
+ Writing grid file ...
183
+ grid cells = 97600
184
+ CPU time = 0.0137576 secs
185
+ Writing surface file ...
186
+ surf elements = 200
187
+ CPU time = 0.00174861 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/simulation0589_Kn0p28Ma5p8/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="0.00258" RangeMax="0.35374" offset="4512" />
14
+ <DataArray type="Float64" Name="f_2[2]" format="appended" RangeMin="0.080817" RangeMax="12.696" offset="6496" />
15
+ <DataArray type="Float64" Name="f_2[3]" format="appended" RangeMin="-0.18026" RangeMax="12.68" offset="8508" />
16
+ <DataArray type="Float64" Name="f_2[4]" format="appended" RangeMin="-5.2769" RangeMax="5.3197" offset="10548" />
17
+ <DataArray type="Float64" Name="f_2[5]" format="appended" RangeMin="-0.0012955" RangeMax="0.9564" offset="12612" />
18
+ <DataArray type="Float64" Name="f_2[6]" format="appended" RangeMin="-0.90779" RangeMax="0.87352" offset="14692" />
19
+ <DataArray type="Float64" Name="f_2[7]" format="appended" RangeMin="-0.0022934" RangeMax="0.19927" offset="16812" />
20
+ <DataArray type="Float64" Name="f_2[8]" format="appended" RangeMin="-0.070022" RangeMax="0.069983" offset="18952" />
21
+ <DataArray type="Float64" Name="f_2[9]" format="appended" RangeMin="22.342" RangeMax="3110.4" offset="21104" />
22
+ <DataArray type="Float64" Name="f_2[10]" format="appended" RangeMin="0" RangeMax="0" offset="22428" />
23
+ <DataArray type="Float64" Name="f_2[11]" format="appended" RangeMin="0" RangeMax="0" offset="22480" />
24
+ </CellData>
25
+ <Points>
26
+ <DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="0.49999998503" RangeMax="0.50000001255" offset="22532" />
27
+ </Points>
28
+ <Cells>
29
+ <DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="23860" />
30
+ <DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="24764" />
31
+ <DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="25256" />
32
+ </Cells>
33
+ </Piece>
34
+ </UnstructuredGrid>
35
+ <AppendedData encoding="base64">
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AQAAAACAAABABgAA0QUAAA==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AQAAAACAAABABgAA5gUAAA==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AQAAAACAAABABgAA+AUAAA==eJwtlHs41GkUx8dtGpFh5udSKF3IrW21pFLOi91uW7rYVFIoaVcrskpWKJIIm0RJQibXSRJNlnpftzS5K2rKLcmlXCdEWq0Zvf+8z/s85zznfM/38x53rzZfvqITJOedDW4p9gHW5z1f6mSCIZ2mVpuU/A/4FmqvdtwdDXu4bxd99ooBFdUN73Vc4yCrm/M54m4CfE1T1x2yvglbR52n6k2T4VSs1uKkkmTIFVY6hm/kAG94qb56Ewc8V2pKNBumwvbQj2q77TlgOxLictM+BQqd3tyqomeAnmxoXgRkAOb11vpz0kFXL4eWKs+FSoOXb1z0ueDF0JA1fsWFhZcXVjT9lAM3bPi07eX5kF3UGSD05kHCqF6F83EeXGuJDgm2K4Rti5fF8BYXAW+gK0OhoBjSMw4f9Ysqg8Du1lLtinIw63R5KJFYASm9fc4eV6qAzdSN9wyuhTxJK1ve3w3g1tHpH3LrBfSEKJWkRLyER+EHC243voaCCPqQysZmOCKsXmma2g5Wl4JYLq/fwmOOkd2GXZ3wdSe46+/shvxSh2iTDz3ge2G9t6LZR/jxpoXVN+kBUBXUfLZ5NwQeNRcaWtuHIcC1yCtabQSqzazro+zH4KjB2NWW6HEoUdWxkUn5AlUBG7Gf5n/AlMtP9an4BqbzyD4tCxpamOP5e1S/BNogdUpuSbokuh4nOtKoybZveWGaDHriZnyGh+hIujtct38OA72Z8J+uJIui+k+DyQE5tPVTpI0XR/57nAIyCFER1HgzZ/KXKiJ3VhB59lYRKWy7e+XwUyXEouBJ8wkWMmvbFnF1gIU0+e+B48BGvIMBgnUFbET6bq41pCi059mKsnsDFJrpn0JdwGl7rKA8E79AGX1a0ODusEEZsW4/KlbtopBI9VQphaoG+KWWdyh0TNSOJYUGRc9eNrLXshg+tIU9E5/KQvvdyqdyC5WQ+vKWJXQJJVRmeeeP1mEm2qvKq6e1zkGMdfG7ErPkUMWvpqEWjrLIp1fHiMGlI+9lCxeM9EkhmvtZ6XKmBIrv0kzr2fgVZCeSjtz/MAqeUzrUovZBaEuFyahF76Bm7o7X6qf5IIiz7DY5ycfZ+pPZjKkObA7hivPdBrG4nOQYVg7f/EHa+CuG3fvu4T4aMYrTV4t5IUXE9pymk0gRLnUMciJaTdo2Uo7M+D6H+OxJN6kuZJIBO0vzHoEi8Q1aviU1TIkIHE5umx/LIhKtkrJhDmwitKh1aUxjk8zAHZsSEEUsAjsqrvlSRMxLM0WW5SYMptGVyfRUfIVDFLkvf5x7UV2ZNJ4SCVcmW8UNKpOYwxcO7b9BEa6GnbOZA0X86u7vHZ1gkx4B94u9G5u0ir4Nm03E8zNgkZE/bf2yx5TI6qZyN2OaEpnhRJGoTFYO8K2Y5MC/m+QlDRTI5UoRoPLkvq8wZ/tROZJYnVnbaDubuE2nPzjIIGJfDswiYqxn0Un9IhGJ0iThjE7J+aVS5Om1wthLTEliNW3j8TAa8Q8vOCo7MYXFV9IkXjrtnobdF7yiK1u7M2gcu3VPZgw3jOFbeabjJc4jWMxlvhDXiMr2DeFMg8T3Ph6DuLjDo2v3Xx/x+VUiAb14fK6qwjnnbpz39OTjxHmd2CPu+WGjex14KKw9wEDQjhneR/ofyLVgxyzpi6VxAqwnNrwJZ/LoDzbnvMAZHGvEdnqOB9bZezbr1ePGmFrh2oeVWGmu7fD6Lj7uj9OWcHUtx3Tnu94BRaV4djBj1Tn9YmxdUFJoX4bxGcfI+ZhXgLW9X/3s8sNDrC5etPn4hZx5Nf9iHj4fqflbx5pcDFxT1+DeLKzhb9qSa8XFofnjFO1dBt6FGyaGDDO+67+Ndxk3TdWMpeNH7c9vFD3l4OkdncZNTcEy28MN4w4l40w9/hqN/bdx0KQEU16Lg/O6V5jItibhUXbNsWXRydh2VGi21eUG1tC+W2OkFY+lRGvP+jqOhTYVw8YYvDdl/q16zSu4mVXQLj8Vid8FvjIP9TqHfebk/FJseRpv0repsqhzwv8DwoQfAg==AQAAAACAAABABgAABAYAAA==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AQAAAACAAABABgAAJAYAAA==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AQAAAACAAABABgAAzgMAAA==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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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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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AQAAAACAAAAoUwAA/DQAAA==eJxlXGV0G0m3TDbMzMzMjJUNMzMzM3OyYWZmZmYmsSxZmhFaYEvGMDO+7tad6Dvn7R+vHVsaTV+oqlt3enwekO3npDjkPpZv7YmrcYj3dK4WGROL812ySE8zx2HSgeeb9gbjsOpOliZjc8SjZdqNtTf0jsP5PM3qSRfYz/eXmz5wWDx+j/gSP+RwPNg3O09Fx8Gg7+O2ZY7H/bichQwJ8dhdPu92e7oE/Lvn8uj6DeIx+9oUdd/58ahfou28pVUSUG3QwMULpidg28rlfW334jGnxAd9kYwJ2Lkpy9zaZxPw8ev9Dos+J2DOxb6737ZLwLpKKeuVHZKAOyPfm2vXSUTe2a8b9Z+aiPEpY2f8WpKAb54a7f6xJ4C/evsTiTCO39SmZWQivo3cW8CWIxFRTTctzT4yEXPPNJu4okASPlZfk7CjZxKeRqtK6fYn4pzmZLK8lkQce+Jmv8l+fk9bucv9JGiDpouJyZJQedqdiqVrJ8F6a3LRkhmeIkPGPv7n9Z7CWF19ufLEJIwbfDblWlUSmooP+hQPB9cZ32/bU3R1pOzyJflT2DoMzdqb/f77jPm/l7nlxu7/jF+/5ItCnV9RG3NujsLCuHGWiuk8uNVg3M0Boz3Y+/tlqzV6D7ZOunG7WiMvcn++phq01YtifR6lnOj3otYwafrM6j4YLq2pU32jD/wU8rt96GSaW21bDj8WfS7RYnhvP7p3LXNo9SU/Uj2anTrTLz9KShFld/SLhlMzoebim9FoeHzpp0WZY5A7x96N45rF4Ha+iY+SVsbgXMG+wxvExGDgnTYZ/6kQQAv3249t+wSw50VNueucAExNRvz8sS6AjhkGfsx1LICHmffVOHItgO9Xi5Qrrgpg2QHzGYsjgFynq97IGh/A4ARrce+3AAb4WqaYnSGILkvH5G1cPIjll5cXTVMqiFeZHlTdXT6IG8486SbUC2LKxuNZBnQOYvSOlKdOjwjizrh03w6NCqJ0zPhpw+YG8f5S53F7ZgWxKefmIbkmBfE8XbuGh8YHkfxxwUYL2fcHz553D5oZiw7eh1fkY7HolurolvrJYxGxbNDzpA6xaDA5cpUcHYvM/G3zxiGv5dDhRUti8SEhlbvVyVjU/fpk+JnBcTicNfnKzsfjkKbplcXpfLG4VHffN0fBOOyvvHa1WReHAq145MTj5rX82b+wPLFa8VizJg4fuq/0ZawTD1OGSxs7DohHpSv735zUxsFRrI4q09c48Oh8ciAe5t419+9ncT9EZaswIl88Okqb+/9uFk/vn4A3RWeesM5JwJkKBxPmTI7/my/XAy0G/buH5cWDJTWHSQl4m7t15595E3DhxtBFUY0SkLbo9dVbfyQg4/N+idP7JGLbj0Jr/lmQANvKyqcm7U6Atcz7ks/2JKJ0vnoZ5nkSMULXsuhAVwK69e/BKgT7np1uhjRJ6NUstnC7IknYtSJYYmjbRHQvNLWGb3EiblTiGZaETgO+VbSwfPH83r699PFENH9UrPvpqETsbzelR9QsF5qs/Pb+n5cu6M2TUzSGGz06ZJ1RZLEbvx4/mvYm6Kb8jsKLgimuuO5GoVz/jU8+lfXgR6q7Q7xHPJhybq13dDIvWLF4bhzlxdST0y/9tnghLreKD9UTL5SKX+rDWpYFPx/7IN4+hR8FbTl2zG7ix8k5unL1t/hxsGFF+55EP1w139Rt0Soa22+W2Jf7XjRWZzw7u8SHaNhbt0t4lTYGxcfPnnu8Ygzy8Ns5LQYtd2eqbtDHwFN3aKXGqVjcL2r9cEGhAPipfqsYAPsw9tId2fcF+B0J4J1r+Pq5qwIQl3UggGG3jzs23Qog8EGVNigFcPLq1sdd3gfQW1Ngd6vfAXy5eK5muVRB7FvTPW+/tEFU1vQYEZMriJtlr/5bOl8QKba/e1OjchATTuVNmtQ0iPWLDk4JNgmiUXrX0cmNgmg3k1fAIFawLDJdCyJ3dELxBzmC0H1cVqowy59+pXoXjPwZxGEn/+CxaCoOPEj5GqS4ikWj5kcbrNofC+uQB/eS/Qhi9Rv1uTzNYlG/SdVWG1l/WLynL0tNlgeXayyPHBeLYjws18eiU+/Y5CO6xYFnV4dlccjszT2itp79XeEanfP9icVgcWPiMHFie/arcUj9qRKrpHH4NApdm6+Iw8cTxXNpc8djyakfyY7VjkfWBt1Y6Y1DM03dRTnSx1PdicezzENHpd8fjy2i8sfjT7rKPe2D2c+b5bHfNMVTHiYAhTbmO7UuHqnWqnYPMrPfS5mnwtiqCWDF95p+ZgLY4TYr+CKe6noCUp5/tMlxPgGpxmiPPHuZgB876g3InSMBOyzvG95qkAD9856WNm8caFfkzqEHI5yUb05k61Z89cCWLkQ35BntQo+xn5tUqOpG6wmx8QtXunFqHT8oNzrOjfnqqRGFtdULDN/C6rwoO4EoDFhz1vigggdXPh7O8LyfB8e/rL/Y6KoHoyruieyY2gvHlesPWo/24lPbPivqOr3Y7Z7fv0B5H/VNH3JNn9dm2DUfyveavXPtVx9OsGoZU92PU12vpun7nx8X5+9Ieuz34/vezqsWN4tG+xPpW5aaEY2JY2qVfH05GlvX7Vve6FU0KuRYePpgnRikSZv49N28GLT+1uZ6J10MxSWr1zV4Bw2gtmhEAYjLa8W+15csMWoI+/cJmt9X5gWQLWZ1nyorApgy9WGzLocCyJ4TWt/1AFgzKB+tD2D+wrzFGnoCeLbHUMfrCyDN7uHxFV8GEHU52yrXpwDmiIYSwDgRCAGU7zpkfDH2d1/5bSkZgDie4QGc/96fvSPLwwHt9GlY/OtcB/pkZ+83JHD7y2RDABn+zdx215ggvi8ce2/61iB6smx6/CeAeatazsraIIiX33lhCaLl/DIj7+eNBQtu70fWVzKwu/PPniCszXnAxSImkGHradYPHm1/6U6rDmKm6kaL3ZlisblMG1f7B7GY+rt0zuKBWLCk+1WhQizcdxF9tmcsmjN08fZbLDSJcQxZxWEgv8y9sZjTJGpbhXuxeDb410HVfIaXEnAs5kEceJY0jouFSHPWV3hXmMn6Q+2G97vuKBb/tw8llHE0LrQxDm3fFBg0b2Q8JmVf+sjI8NfZpGMscuJwZ6l7d9OkOAQe8MS241T9+JG3kjuwMndU5JduDnSoPpVBCAd02ca9K5fMiZ+n38kdhjoR1y3ZulFWJwYJoOaCaINrXeidlHfT/WgXjrDvctVy49ym91vHHnRT3kShdO0irhVrougco7Ch99pOyat6UPlPsV+fZ3iwZ9a+IyVue8C78/DCXiwbnjzHrRle/FOBX5EXBT5lXf+6qA/neJvu5EPUrBZvH273EW7woXZC+jdTs/kRU/1kxNChfgRfn/PPPOzHj83Fq5+L9cMy0pE0tkI0LjY1djqzIBpxx/eqi16Kxk6Nmt35aPDqWS9DDDhaMneLwX8pNRurzYpBuR39+mZaHYP0+13uUmdicJ2hqlrPY1C9R9Xyp3MEKI8D+HC2Hqt8AWRkUdClDYtzAegC6Mph8tAAHOlGs1YRAEdnQ1YHMPrq82nXc8XgIIvGEzti8Mnr+m9ay2icZqis/ONozOa342cM9j1Mtzxt3QD+K3a2X6MyMdiwpRe70zGU7wHMHupce3hfANv3NLKmz6jEbQCXffLY1ixvGvef6itXKAhxGaMCqJpJ1Uq9LYAlPQezUhUEPy3Wq+F4+R/7SQAdHkQlaj8GsIm3KwvDU/3rZt2SKhYvzv93PnvFIO6+73MgDcNRDz6btiSrFQtX9vf/WkbGYpCc9/zRM0F41/xiSJ/1naG8kcUiGzu1mSdYXW+4dMXvdLGI7s4Rcyw+z/2im+eIRf9zpx7XzBiHnE9zzNkyPRZ1uq/7UOdwLJw9X1a5W8aGFJb7K9ttsGHp0XhHvdR2wvV2tGzaL/L4LTuKiUB3oMjoVCvOTXSgsDoyZ/2LDvAuNjazEw95+Z3uxNmXd4t/jXFi2ujNr+bDhZnV67YduN8FG7tLw565qD+6Eclhxzo3tuV4Vf7YT4a7ebiOiUK3OQ2ejHkcBfGyWT0QZW+YBxdnLbrX67wHyU532Od748GLtctu7Gvnpdf34ve7gderB72YLfXaNLKiD/wU70/ywT+Q3zAfjh1/P3OZzYf4LKkPzMviR+vg3JwXWvkRf2jZ7huL/LhSeeLR5Pf8eMWqyovvfrDizpB4NG5y2DYnGhMEMIyGZyMHtjFUj2LofsbAn4YDuxj8rNXnaOEjMRDw/UMM9f0AnnZoUX5dJVYP86/YuKpcAAnN76YvBxavLFs+7/RDPX9O8s+SH1331r0dc9iH+qadeQYX8VNcRiNh4cojTQ5Go5Jl6d2rM/34Vo0jGT+dawyKvunBWkYMXvHb3zYa7Ga1/3o8GnvmXzWvfxaD7vV7/0li+dMjesPkvm+jkThn8iznxBgMT10+LobF64W3lfO82x/AsZ/HPCfjYhAcUDm2AesrBzfoMnbXBnC7G3+BAOGMcD50+LCh2/SSQcq/IKYtHryh8MMAPkunGYJheWqekX/M6SBYErNbFsTwElkvvsgTRIHy2m97GQ7i6BLREpbxMllLRh8OuzfIWM5QUu0EGRUex05O7GVDCVZd1ptseDuBMxk75gsiZkdawz+lJ7+wg//Vll4O5Pf/+7L9YQe6dLx2dtN7B/oy9ruogxMFMgUqbTrkxPyKC54u+e5E+fpbIha1doFX4bjjLoh//urCnN6napkbuPF6Vtn0H1e78e7OwscT3W7ce1qhdY3cUWAkiwVoFMSfP4zCOYYWlvyJovfxUD32QNBfvwcH9VuPjSvtRSsB5Lyox063rNWLkUvbs8rvw4/ihysldfWBkcHgM1Zn0avf5Ycv2df6MxKuNmRxwdBS8iV+qs9+yu9o4mXRKCIATzTxqWiIMh+IxnPLwmOrWFxocy8puK0qq2+5+SeIwTZ2NTHjY3AxslrRefcZrg5kPWN/GYO6o5qPmfTWC5Y8DEn40EPoEV7Ym9VkLcyLPnluSsmifXji73P3VVM/GNl7kj2LD/p5DuOyQT68mMgFCj9e/CmYGJEhGiMmb7tXX+fD/CG8gvthXD0zV9eFDN/0Eg0M/UQC+8HAPCttfsLVMRA0o38MJg9KE5mvSzRE+bdGowqnddfZdYoGEMA2htafF4zBqUK/95zrEoPxgoCy+BZCAesH7F9TXInBmq2cYAWQ6cSQr6t2WfFudNyq61+teMhO7fxwCSr2bhufSLAd/NU6Wz4ZGxrwzJVRlsOJKBn3CwWvBVrY0C3C+b34YRvKlvH0aP3Nhj38WOrZIS53ox3aGqOfHgzYcfrzs9mmJg4U58ewz4H4apwpOFD6zM3UN9o6Kb6d4KpFEZcTo4Z0avCzlguNdzSe/u8CF9U/F7qLxunG5SOpbVXnu7HyNwfWbpx82pq18ii6T1Hg1an3KdbnSzhjuyXzQMCPFh6Mmc4z1UN1ywNTWd5gvdS3vXi+/UrGKee8mMVOpesrL6oc7c0gqA+zKhUr8nG8DxU6tP335k4fChf4b/aAhz6knTXq1Y0MfmT3TGVUyI+Xj+qVaDvPj6NNeIT7MXn+q92lkkejpWiI0ahtbsAoM8MBnG6Zo9G9V+OIDywu0whCHA3Ozl7P8kDQTrsHJZa1YlQhCimT1pV9lcmDnFcHZkxozuLx0FdW6bx0HzxUhzxYPt96tc8nL0ZzutLDB1uUIVB2jheGhu/TpGA8NDWnqSaWV/xYe/rRVDRuHx504AqMD0OXvWWR4Cce4Ye8rgV7CR/ucnmtjB8R3mwdM7C8CukB7Os4znz8qPd6W2bnHz+ePuaJEAlBo49aqF9YccmQnyEoK1ZxOSDOCiEvtJMwjlf5rRLYxbxrmSiha/o7949Vk+k+y5ieUT/wzW8ZAuYMt1F9sUHQrWx2VHy3+Eq5XnaUXi/VP7PHDlGGX9pJ73JgxdQjA5Zvc+DZu3msMjqIXzjRXxRaJ85N42/gBO8ypyu4qI65EPezQ9nmj1yYn37xu4z53RDwb6Yb6lK6/fJjNwSN/eWm/hFFukcUOt5+cre/OorwggcrEuuvv9bdgy6iIbL468URgwdfa3MhzYuthXggeXGiDP8kXtIRvSgpCpMP/QaVvJbQ34dyorD5SIfwof34xhcy5fIjsKxpyoKs7jR+GnXue38/BE1jdTGxP/8/P9qLxPVj1/c53Tanj8LnDJwZRIE1+50FZ7nh+s4LrZv6cxT+a8YZmYfqSBTpjlFgxZABNA+2j1g1bIDPg9I8fM9EYU3DNndGvo+Cr13+ozO6e1FNCKlefGmQM9X35h4IOe2QB0J2ze9DIuv6Vwf60IvDqyxepDp1esS4BV5s3htMPX+hCW85ja9npjg2IwXrYhMPRCJdjQl/jG0tePju+qgdKa34wKKrWy8rlmyqOPifm1biwRJyP/7T88owifQCCVM4nMoqY8iJV4P6jJGxfudEVgpkJI/+J92aIjZkZ2wuw0wbdvEfG22IOcEhux17ti2ZWGWMHUd2dql48xqLL9520zvQi2VFgUEOZBMAyQGuto3M4gRHdbUGOlEmJ+8cTty7OtO7PNGJMfUb5CtYyoWv+fJkXjbcRfnsQs3KBVmLdhOOc0P82kU3ZnNa8dKNnuICojBDALkoWBiLNZyNwoOxI55U+cT4+RRO6DxIKwCqBwxkn/szLczL6wqA7KX+5gVnNd+WevEmxSaP2uDFhIKXcx/8x4fOZxbUL1zDh1otX5wau8RH/MoHAWc/+fCw9eiI2zlZXDG2PPWIC4dUHJC5EGDdusx7J5b6L03oMtJFdcGNTV/ObE/30I3MgkC5cHUXFwLcGNGNI6koMPLf0TQ3CiPFf278ysGRmhs5IyqdX8HyJtQnPXhk4cJ1FDoLYhWFxOl9WMgbkcTTKdoIrqbkXxGBds9T1sxW2wQBGz6bsCSJC+Rm8KpsnhEJIV9ksKCiKCgW/LbPfla6mhUCbm62QsgTz62kj0kUDxIaC8Ajob3qbbZqpWTiT6zvrePEQsYaPReybcRfbBCyg80GzsrTFrAT/rAT7rFjcqkGtf95ZyedygF+V3ttd+D1ZS6oOMDR+rAmTtRPPZxBeiemdn7S3vvQSbzKRbqjCyV5O1vHeC+Hu14XrnH5urwbqz5yAufGHy7DX3IjowBGrF6lDUrabFFgoPaulfXFLuM4043Cih73Ns+Jj8KWzVcvnSzkIX7mwZM8pbulOuohXuDBM95Wf7H42n/dW7mml17Hi7HiF7z4GXefRaSXdFgfuEphXO2keYATmhTGE/2DDnAWr63hxHGGoqulcCGZAPIuiLTe6oSgC2YnhjfhzMwFN2O7N1O7ka0wj1RXSCZb5CKdWo9d7XOta/tcDzEW2mqAaBc1jVg9kHdaI9XBCHD2kiq7CbXKpWKUx0T6hhliHFE3EjLrGkWfR6LFcK5wWjCGw6CcVnzhcGWEFXMni08Mrt66M0n4wOnnKAnJj9WeMvWhhDIdOSKW8XkoR0CsX5W7UP7HBRlcdbZksWE5Y2NTetgg4M0WG81DbBDtvbQd2+08sOwQbfe6Hbmr/tdv1gc7xj5e+2BJTQfpgw6c7M+ZB8NLP7tiUnknhKw8xInLfKywj/WzWfzOOHFlNK8kLjw4Vq1vqx4sT0dxAu0iHuiifuz+m3+JvTgzcePFtOu5fkS4IWgo6xO2Yzmnz2sThWCT1uySomB1cEIcBVbk7rTJ6EGVLvdrXerB8AiXzZZ5SD/zoLIAJh7S+TyI5+FRxYHVPA23OojH2cFAZ/Y2H9nn5nQwwYHaz4sxiuLE13FXWjZq7iD+56C41OLAv83+pMyjA1clr17SYTanve31SF6V/4sehwJDW2Q6YUAZ0XiNePTyQMOKdiPNuyIgxkk5TDj8YETHnRoTyoqGYIZR1fT8mGjWb3gb3R5JurOF8J+F5htW6k9W3GzBBXYrnn7eoh1dSIJmaruzxaZImLzbNqLaZYnqswTWnBmEkCHk1SMynnznkEgmvGBD8U5bLuyeb6N6ZUOzgi9ia+e3o5kQgO3gXX/NWTvsexILnXxqx/1JHEg6kJSMD4wcEG1E48DwGVxRc7CY4AKkk/qAEwcGlovIqnPSnMWFKqcmsSt04cYoPqByYT2XU9+68C1nsrh8LB7yCSLiRjmB1N2oyrpzhutu9OXh/spNvDsK4uM0iSKcGAVRPo1R6LV9Qa+UjO8t5nJ/aw/p/mqIsdkJNUaKgYsGJy9woVcDRjZZx9YiJW9Hv7RoKwZ9OsycwhmpnnixHgWq+Eum/s9AddWIfRy+nTLCHL93wsT2ETiybzRDVBGkI5rQbmtX66tSZtJXzRQ/kTRXiMSWOVzpsGDbWM7graTnWeHj8tc2K8qJQZOVeKYEjiKfLZAI10lUL2V0EURVpvmoTP1QRvPvr148qmdDlrJ7py6fZcPgPmMYpLUhRxmOiOzE7+1483s2q+h2NOfjgGfhvpBsElf+HMS/HMQDHaQPOMFA7+S0PZzo8WN6w5GMt7/u25RBPyfxHxf8XHYb5kKL7LxTudBHCOguwgtucHana+nGOu9o9lZubJzc9+0RhjtCeMVN+nC4X4TyRk1zYTU6fD2+MLq7mnisGgI+dNYQftfQvEaLCtF6xjh0yOL8U8+0M3yuJYfyk9Zjn7ropamjDfT5DCjEuv6ljUaIsXWRCNKxI9BIDJhNSH/kNUMuJnCW9mGKGf/euzDoUoFIiHatisSfK/PeX+psQZVHjdnJWXCfj8NrWTGY09G5VmSY5wleZHkbwiES4VWJ+odEfUoC4p78t6miDNaMWITJqDXvUK68V2TkEgFuwzgu1zWzUR4yvJiLA04b3WcbtuZN2TNzJTuEfPCfHY04PDbbqY+x/O3KG6UDZURCO7DyZC9WohzEF5yYYMwVnVDciY+rObB2Ulw7YTbx/5zEG1w47595+HZHF+EgF8TtuOEifZv1Vd5+SrjRUgjlboi210MHfpr9z6mJf6sg6M13FeF7NfVhNaa/CW6J66iBqws/eA26Ty+5888mLek2OmxNVuv6+PM6TBYEVI9FVd/65t3S098Z8D09Z44G7P/4gCF2I/5Y+KAugvhYuB6L8L9igpCXOppp7mmm+W84b1uLxmjBVFHgLPB95AM5KxpwOLjBilvsVXa5rVjJx74lJazjMiiry6F5g4QswiggoW/5Sa3qVmJ8Ugh0MpbPur3qjVrG/jtcWGb8cu7P6BOwYaq6L6N+NgiZ5rSNdHwbxNixnB2uMRwA2anf27FEwwcNdkzh6VTUgSvtuk/KNN6BX/dOt15+meGfzFlNUpyD4stJc24nhl3bcKb0Kid6pcu9sgbDe6F5ppP6iwvbPqcetKu9i/RUF+WfleaDRprbaMnHoUYPDo8CKlQSA2M16QlqhGiFmvqeBgNObt5h9GrwrzhQLaqV2vJ0RE4d/mUse8ZZHdZxmF5ND1a8m2e/r0c12+eL52oacHgUHxwYiHcYCSca8foFFz4iqB9EwLqXD4hN5Kcw0fzFjAWbrTumlYukOWYk+Uos4NXy9ioL9Lvu7tiUxQoxRmKfs6W4AVbCFVasGs0FHAmPrsgMoUhIqjVz9fPzEs1FJMyrxpVzGWK8x+ozA83sCGTSD2U8W8CNKza8l7nBxQbRPtfbwKNitmSjOslwSaZOF7eNsOM2t8/ssmO2IC52DBeDPAfFiYPqvAMzA/uyHb/Pzp2PBzM4kd53Z+/J+k7iDU6w5Dt49ryTfBxO5BRCuUz8WSJ9MZJ0Dz3S2KrOb95eQzxNjXJzZmxIHqXCLy5LFFNDjGdWqlFoVts0L/6o8THAB04aqkMaql9aVMnzbv+uT1rCwzr81PIBpP7v+9TKyJmK4S9+Cs1tjXg2gjMyIzIKQT4Co+cUZhQgguqqCcJmcceEA1zGqWPG6XtcEDRjyfnsFTOzfjsxD3feRBJPskDAiBsWvEk8nfl2PlaXi/CMs+Los5fDJ7O+G9IhrDT/lsBAycdOkyXsX1z6yYqTEumwEuncMqq6M3lzj5CxwtD98aljMnrenNtxbgz7nstLOW2EI23wFOWTYxt68XGTxUb41Y5izxsnO93Bjg6VuOJqx8g23DFgR02R2HYIW0BJBxbwsXQfB04l444bB+71V88a6nRApFNaJ4TMPjGMA9JNqLcz9owMYTPKJyHDMD7hNWE+l1va6iDe7oYaNzktYOepfJW4DSe/mvC0mvRANYTctUBDOE9DPE9LfgUt5gkjlw7CBpdaT3MvPWbmH8OOxIB3fHyxy0D90ggGCu/cWm+k/hyBHVzuXBsBYXdLb8KW4mKgQPfRjLwLuNPAjGINuaMkEpUZS2+0I5Lm1JEopv83XY0JFgzZUPjhzWcW4jVWbFzfhL2jFQK2HbDS+VgJR0ooWXbhutvjJNzWySsrn5LQWTcsdfk4CUKuzymTj0Km+JCx+GaTJbE6dn87c8VZxvfmB0oOqGGj+Z8Nl09ywZvl8ad9rOPYqA7YEeRhPcROcw47Ni/8UX9ypB1CBk3tQHXGknIwvnGYy6mM59cRhgAZ4s9ZXN348Ms++5mMxgwsD18vk2/Gil15eAQbyZ+mhZGHYUc1hI1NowJHDXccKiRpubFFjSYi0NSkF2vAu/bGVRp86f3dmuqTBm8MnIhosXjE8TblnmoxVRjodORn0SG7KNB6ZH1282KKJD023Y/+9W6gAQuEgcqAGlyma2Yk346R8FAEtmfmACwCz+zbLe8bsj7L7S8XTKQvmXF+Ir9hZjjPH9gaXScSVUQCRKLpy/aHP+S3YPmLLrcKL7cQTmDnKwQsK+Imc+ZoJX3MCjFe+mBFDpb9C2tJ5HOUINLnrgQ+bbF9DudvSB9heStuhIwPWzkgl4kPsHO/WNTcu6YNA4TRz4Y0N9peqrvPBjHOtdpIJ7KjsjBO2hHNZaildsIHEj5zWplKJt4gY5AQDGRseMaNdzK4a/GCTQZXQbKklrFQJJSFcIiB4l6DG185QVJT/VJB0HezCtmFkVBN+FJN+pMaISKmQYdRnIlqyPejJT+elnCbDmW5nc2gwxQxuNFj0tvlrJLpya9iAJ8KvD5nwHhhLGJ1WNwwI4TtI20E2IuUqLQ9gnifiT6/ieY6ZvJFmsHdG3OSR1J8RYK7bk5GRJKeb8GDle02NDhugbCHZLUSb7WSjmOFkKGuWGHxTGAV3Ypjq7gBTUJeURAkCJp4QsItbk97KpEvUIawfbSRkefgP4MbLmXfczvEbflv3xNjsrI2wsM2eLkstN0GcZsYXxomiI0EAdffScQTJJQQgyGJ8KOMf+6lyp4TLG7+9DNsYPnJUdGDgzIM3N67SIKwpWwwky9ET3M3Dc0DVKRjh/O1HrdLFg3XYc62xv7PubYSQpAGnDU87qIFn86vfKiluYyOfMo68onqIewY+/WI5sdewoA9u/l/BrT45HzUM50RHj6emWEkn5eRfBURpNdEoFcIeEDQyPsm8kua8bsZJ5pmNBWCQSRaJW5G3tmRqCQKZCTloQWjuP34hAWpuK2kkBXcbfSjlxWjuM14hxVFjkiF1JFWbOG09rcV40VBl+g6JBw/5GVMSUKgLZ94SOBRMTOXTPVERtFdR3VvGE8K8WeGtw5cUqcwymDNmzMDzOdjUIbLtvTnVyxB2J1+SOQ7YvzrTDrG7GRwN6yRvW4Iz8oQdr0BMni3XXtYRmp3q5MX5sso+PbbkGVvreRrNdF8QkefQ43M1bmzW0X6vwrmEpyZqLD5Fm80aooTNbjafeqHGrW4vXKqBuLtozXIy23jTbXIz+HHZS1e+ou86VFBRzxAh2y8fbI+G/Jzh+txJt7+exuwbhR31LK++5Eb4YykxxphzcILZwTKc3lmVwSec3nxZwQWdXCeWjnaRL52EwrzseogM9V1M83dI9H37qum0/ZHEj6JhLgNoy3kd7BgBEPLXctYyZ/C8BS3Je+0Yh63uRitePCYC7sSsh+/z/5PormThIzCKCYhjSioEvF8GZwND6gsQ8gNY2WINumXUCfUYMgPIYEV0dbtEiSM7MidTBKeHF1fwsnixMfHAR/D8xdhq2PxInP7wxwZFX5cSPv7pgw+5e/fg9VnMSC1kl4fAa6ifTihRRKHixPVxLNV5NdTYZ4wKqqQVhigGP6tw53PamQQApYa3L1Vp5OGfO4s30tXS3uuoBZefpuXaclvpsPFF3lerpigI7+FDoKWtddjEJfP7ujxidtSaxtIvzRgRQqu4BqxqyYfmBhp3mgkn0UEGvEx6/0IxK03scgzkU/MhLndNqcflsGMzc35RNkMTwpOgMxYyqrD4tKREPRoSiTxqUiar1swm9PTcxbkvNAqODenFdZXpdZL9a2kP1nJz2KlvQYr8SkJQkbuLqGNANASuEq58biEpsLYLoG7U11uifzPEtoHnP6GDonmGBJSC0FXgjU9H6RKNA+WIOyY7FxDewUyDhbhGxcy8WEZ3PWX71Q4n4VdwWNBQVF4jTSv0GKWAOhqxOk44VORz0oFMZ6PVJEvSI3x/bZFFd2qxgBR8NSk22jIZ6WBWJ9IrwVHUZUYLg75rLQQ7b21DsmEsKQjPqxHe07Lt+txKD8XFg24mYEbcQy4KsqugfwLRpQXN9SIf4WxPIL8gBGoKgyYESh7q3eXpWNMNC8zoUkO3vnMpN+ZIcpekplwRyT6cZnuXCSOzOURyXCGAGAWCHu6xYKO+3xvOrPzvZTIhSUrvb6V5iNh/UrI3SlZXvXgkRU+D6U/7h/GBygShH32Hxn5kiY1Lca+CrrK6m5ovixhRsORh6r/lsiHLJNfVP7r9wj55BiP2fXo/F2Wr0J2YHg45L+XwF1yWZOz/sJp2XIDpgkjuIZwNMO5fA1nrQq6xS8/vd6oos+pIr+8GrO8yxPrrw/jJgGj+2rQTxB2DflJtVjIbfRzWN7ydRm7Fo2vlmRQWke+SB35T3XgVabwBD2E/GLWk35iwJ+kqoMGLjYgoi0Xhg24N50rdEbSt42YLRpvBESZXBZBvscIej0T+X9N6M/ebV5FM3g0F5hvpvmbmfIxEi24be10JIZ+mDLhVF4L7WdYaL8oXJ9D/MIK8XILGH7msqZaQhSn3VoJl3pwJYnhK4ZGpsnhn2cXAzSJ5rfsfB2bWEdjPPnMlTdrAhLpnix/hUAqoXutf+0L2LkebmsuPJrh4GQXhutaFpXJZyjjyFDuoJNJd5Vxrc+n2541Eh4c5IkRifXc9hHQEy7TkI9GTXoj66d8rMnylU+NXhtUpDeqaU6iRr7Y3nluSmqk4jbWShq852P7Uxq6Di2EjDZdS3MaLVrXyM0gsw7NBFHUEZ/UYY4QLPVoI4iGHnu5rT+dgfQ1A/k0DBDpkteICeerZPdMNeISt4P7jTjUKb6NXCuCdIQIXLzM/9BEcw6Gm7fyBRUT9vMxQhkz6X4MP/9cyZi2GWIs3SgSQr49GImd07jgF4kJPXmHttBcwII2wkgskb9OQk4uo8ZLSCYGXuHzCeERCUsnVhmzzikhVsiVEjLxtQ69RHs6jA9zm/UThqtZF5vBfl5ZGGwk0vfY64r/ZOprMsQ4k/Gb+1xuZOca4gMyVvApz3AJQs4/aSZ/ov6vXlSa21m+q2jOqEJ8R+H4putXgbsSIqup8ZSn0QI16aVqCJqWWUN7FBry3WpoTq8lf6kW419md/RLoSNfmQ5JHN5F6shXpUcVIQjr0WoW36TQ076TAabXnLAYsNPIjQVGqPmYbooRC7gt5LaR9v0Yv61wL6LF/AiIMU1cBPmYTLBw++JeE4ZyOfWpifYBzPj8euOXM9vNaCaEQzPaiMFFJJoIgTcSi7idVB/mrcKmeU8iniz9zddfY7mgK1EdkGj/TCJfe1iPVHCScm7c1XuM1c+Qb1MiX5Yk2MZ8K8NffP2N4StBdxk+DuEDGbfXp36bu7UMvo31s6pMviUr7RGZsPo5N0jrqQ9p6HpUELapGayfrszGoJmK/JIq0jnVOMFt6FPV5GdTg0+5vbk1EDL5bA3tq2gwdc2G+PdFtOSr0BLP0OLkjvOfWjTVoadYzNARz9eRz0dP+zR60pMMSCkG4AbCIQYI22ZlI/kLjfiSnG+kGLGZr1U2jsBObuvZGwELt2X+iEC1y99u1e5uwgG+1rnTBN4V838y0ZzdjL1FubBnRgWxqCFRXEjk5wzz1JCeL0GO+1L7F8M/gq4z/CPW8Wxh/0dIbwifs+LLDfl4JTQQDU4CO4RH0xg+GiUG1xL5ZiXUEosqEkwSfyOW76n5ZokMAQf/lWmvIcxjFT4WwlMm8sHrEMs/ZlYN0gpjiAq/M7f4r/FmFQRd3aUiP7IKdYXgroaQs3upyY+kRgl+HBk1SMftIOM0tC+qgbDNp9P+5bN8O+7u1fC83fuNL6boqP/oiEfpIeDlSj0MfBwUo4cou5UN4C6XOwsNWMXX9mwGpBGLNEaqn0aqn0aaR0VAyHXXI0hPNUGsPXYw0dzcRH6jMJ9Q6qwY/7P7K+wX7OeX+VrpTwmiDbN/D+2PSuBbtB6Gc0L+xPA5KLq7uzw3UksQdI7V5ZC+KxFekehzSPhve7O141le863Oq8/D5x3iAzLpnjLpvTK6ax9abk2WaR+O4TB+m49YIdZJS5qQqxDfqNGhTh3u/FPj7PZ0D+2WcF8V46A9KnQSCa1CcBGP6PC5hvYN1eDRevCXGt3EgWpIj9HQ3owWT2py5UiLV7zN7tHSPE2L51e4MUtHPFmH7yyr1n3QQb2tNeu0etKz9fjn5uvE05kNuLGMG/IM9PoG8ucYyfdmxAMuRzI8lazXlWElskb81TGU8w3pUPLf8wjh6DAe5Vso5z9JNL+UqD5LtBcmER8O10nu/mvM+GpItwnn+R8+Vme4OOR7DH9V9AZFhwztcbF8Nx5ucYPhpYHc1v9CQotWU79lecb6rRCmJPLdyhDrYHVliJcZIuNdSy64yNgZywGYlfRIE8QYfLMOB7dG13nAcG2ob6to7zScr6KcyirCI2qItZluaqwuxxmimvY81TD+4oke1otDcaqhfWQt7v/gBiwtGFkunkurhZAXqugg5JIdOtrD0UHYbsrqMVMAQz30GXmE6mG+yAmHAeszcIXSANa0iuX3G1BdBK4RYm1vgxFi/ONl5+3gQrGEp2I9I/xVwTOhvdxwHil8c/V1LqSGdaDpAjiG63II74X7n3LeObi8z863Nrensn4b0l8lhGRSifwkEvnDJfLFMBzL2749zGOr8/bB3l/IECzvhZyRRqa9LJanAnjKEO2R8adQ/lpRUgDBCNqb0qEjp6UpNX/ncaE9xHB/HSMIoIr8JWoI+tY1zGPF+uF7Ne2Pav7Od0L8U0N7tVra09US79JiiBDmdMgmDKc6FBeLPDrkEUZLPfm99RDr4YzfCvvMWz0EOm9qoH08A80HDRB2PVYvQ74ddr+FIVrC1jgOAMN9TMmDEH+SIGzV7JxC82MJuz9x45tE+xBhXSHkA5Yozhme2l76+CH2+4IeJYX93kr95VXjIsu/0DwkXNdDezrh/A7tZ0vkG5PIpyWhoTBqScSjZZwtzRGiTP4RGU+4nTmFTH4IK+2bKHqcDoX5ukSWMG4K4cowflp3my/0qyDW5n6oCL+qIca0q9UQY/MkNaYKw5yG+qCG9no1NBfWogc73amdw/V47zn+IAst0oo31hHe0YGreCde6WjfQU8+QT3NwfQQ601FDMjF7VvsPgn5l+WTgJmsnoX2taS/59xYCPthvt+B2ydZ3wrVLRlcLU6TVv6r67wexBVnmfZqZIozmXRr+a9+kJWPEb6Ez0up5z0z8ycIMB4rBr3hPqzMZ5T8V3Qlhbce5WNt9johXiKBuyvS/g7r/aHnUsikc8rgbvSW7Fzr8XUAlq9DhdE5Asc78sap++s7U/T+EM9XwVmPG21VyCoGIiqUT8Y3VVTIK260Gl8nG6acnK6muZQag8QgXEPzCg3KCuFMQ/1KQ7xaS/PVsF7RiNtZCulwnK8XTdORD1lH8zQd+e/0f3XUQkJQlyhPJYhyyOJ//PbBU+p+COMWJT+V+YhyHxV8JGyL38P5/TWGC/jy3/xW+jF3Rx5NHtaHlD6p9E0h738Pn7NyfdFTeGZLeL+LC47h/FPyjKusTVOG4yS0xynTnFr+qwsr/upQvQvPE4RtLI9M+2xW2vczkb9SB/Gx+mmQUQzWwnrTIjGgCs91QnVHRf5KNfi0pvQ4NWoII6kaw/h4+KsamkZ80UiDC9y+wPI2pLtoaO9XS76GMD4O+cF0KJ187NiovjrY+TbdKd3f+ZRy/5WvSl685ONUVudC8RjWV0N+bInmPhLh/HD/ZDevfYD1U4XXKLxFqauhPf0wLrW/4wcj0R5FGBcr16Ocd6ieMR46hTuKJfIpsn4oEj/sZ1VeT4mbYeJAZHoOjEy+CpaXbbkhX6bnTsg4KZgW67M56zOoI9PzVGR84rawHVbc3XuyfvxIE8oK4ZjxxZmdCuceqyE/OeOnXA5foqL8UdHcUwWxHq5S0eupMV0YhdS01xPWi4tmbPilcGUN8U4NzWc0hOu0eN102v6WfbVgRb/T+p1aei6N9u88RNiiIsL6eIHsvENJNH8I+wZDz4sI4xiF//8T9cJf5E0Ydyq6jaLPKueh8BdFr1XySambCs9Q8iqE78PnFKon4ddR6gLfUj7zMoxvFX0ij1jwlCDa5dPwdZcSRoUw31Lyu6RYVJDRPwVnEKwfiMVPGcf4uKeb/PffH3J7tdpKfnQThEw7T4+6y8rXmndI81dP+sMfv8L6aT3xYB/WT7nNl51raJ9ARXVd/ddHLOymi1n+clvCXTWErZfVY6E+d9fQXrqG/PUawq+sv3LbFcMjYj0/RiIfXri+Kngj5IcM9yFFT1d4poKPlPut5ImSD4qPIDQfDNdThV8o9TTUnyTiWxL5sMPfK31b+arEidLnlH6t5JsSByGfmIxOM/iTa8JfFV6lvK9St5W5gaCZ7PcMRXiiyDS3ZPktFihl8q/ItL9ihXi8zSQzxNria/3fefhQYehX/53PhZ7ToiKdXgVhc7yjwh0Oo9OokUsIt2p04mtN09Q0N1JjAx+bvVVD2I0a/4++OEEYymi/N1xnFJzyQ2wcyjjNx7rsfih4R9HBlXMqLIzSEm6f4YOiMG5ScKZSf0O+m/B8U+GjSj4rdbu1ICDhv1N4z7WGWV5HesL8SKkPoX2fcB9VrkO5PgXvKHGknKsSX6HnHMn0fJ8wPgvpODIivn7JlyezjGg+tmZ4KT+3gbD7FHpOhEy+2TCeC/mRFN5tRmYxMDDgJX9sVgMt7ZeqcYzDgKsq2vdU0V6uCmIseUFFcycV+YHVWGPWXT88VI2h3Ga1W43IblxRUUPYa6Sw3hbCXeGvYrzE7qOQS9i5hHBwuF8q/EHhk8rXhUJoC5+jUseU81Je71IKXvglFP629L+k/+Gxyvxa+X0lX5XXUfzDoeeMSOQXCPOe0Dw3rEuE9g8YX+GPUWHfH53BIzHMa0N5E77+0B6DhLai8YR/rnz+kF9Agnh7ht9Cc0+Znk8k0/6MjF3cjpVfhlj3qCZBrB+PjYSgqy8MEPLRJi1GiwdHqbE6zbYOt1m9Dc1dVLT/piK/o4quSwWOcgaVVCPg5QGkRsHdrX4PDoR9IYouqvA0BY/w6Xh2dl/E2rkr/PkVXUfBPcrrKPdT2AFjwn4CJR+VPFP0dsU3qMxbFL1d0WcrDeYKVli3U/QdhUcq3yu8VsHRig6g1H+lfytxpOgJIZ9XWLdQ8lzpNwoPUuqMMrdV4kvB8Qq+Cu23yiiRiz+hQEYfIfTI1Ddl8jtK9HwJC/nyjXjDxxrpdEgYwjeY1JQnKgg7wkoVBooEVdE+Rngeq8S3ossoca7cR+X+KD9XeLp2TX4G3cN9RPk9RVdX7oOiFynxrOSnwt+VfA7Ny8N9WMjU78I4Svk9pW8r9VPBu0reKvxI0XmU61XiI4QPwvqFgo8iz1gcPV/+/3hW8N1XvtZqD+Pxt2sCiyqwOA75d8O+GCUvlM+p4H0lnhL5Y5RYfRbrOwwX5xQPKpFJz2e4axifuFhQam4+zdR2EaQH6+j5KBrqHyqIMd5oFfk8Vfg/QVK29w==AgAAAACAAACMAgAAZRsAABIBAAA=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AQAAAACAAAAoUwAAzQ0AAA==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AQAAAACAAABlCgAAGgAAAA==eJztwSEBAAAAwyC9/oVf4hIoAAA4G4r2XY4=
26
+ </AppendedData>
27
+ </VTKFile>
CylinderKnMa/Kn0p28/simulation0590_Kn0p28Ma5p9/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/simulation0590_Kn0p28Ma5p9/config.txt ADDED
@@ -0,0 +1,78 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ variable BZ equal 1.380649E-23
2
+ variable PI equal 3.1415926536
3
+ variable molecular_mass equal 6.63E-26
4
+ variable molecular_diameter equal 4.17E-10
5
+ variable gamma equal 1.666666667
6
+ variable R equal ${BZ}/${molecular_mass}
7
+ variable L equal 1.0
8
+ variable xmin equal -5.0
9
+ variable xmax equal 6.0
10
+ variable ymin equal -5.0
11
+ variable ymax equal 5.0
12
+ variable Kn equal 0.28
13
+ variable Ma equal 5.9
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