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- .gitattributes +2 -0
- CylinderKnMa/Kn0p30/simulation0650_Kn0p30Ma6p9/output/grid.300000.dat +3 -0
- CylinderKnMa/Kn0p32/simulation0651_Kn0p32Ma2p0/output/grid.300000.dat +3 -0
- CylinderKnMa/Kn0p36/simulation0786_Kn0p36Ma5p5/Lambda/Lambda_300000.pvtu +21 -0
- CylinderKnMa/Kn0p36/simulation0786_Kn0p36Ma5p5/Lambda/Lambda_3_300000.vtu +27 -0
- CylinderKnMa/Kn0p36/simulation0786_Kn0p36Ma5p5/output/grid.300000.dat +0 -0
- CylinderKnMa/Kn0p36/simulation0786_Kn0p36Ma5p5/output/lambdakn.300000.dat +0 -0
- CylinderKnMa/Kn0p36/simulation0786_Kn0p36Ma5p5/output/surf.300000.dat +209 -0
- CylinderKnMa/Kn0p36/simulation0786_Kn0p36Ma5p5/surf/Surf_300000.vtu +38 -0
- CylinderKnMa/Kn0p36/simulation0786_Kn0p36Ma5p5/surf/geom.surf +610 -0
- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/Grid.pvd +9 -0
- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/Lambda.pvd +9 -0
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- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/Surf.pvd +9 -0
- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/config.txt +78 -0
- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/cylinder.surf +410 -0
- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/gas.species +14 -0
- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/gas.vhs +9 -0
- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/grid/Grid_0_300000.vtu +0 -0
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- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/grid/Grid_300000.pvtu +29 -0
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- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/grid/final-grid.dat +0 -0
- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/log.sparta +319 -0
- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/mir.txt +3 -0
- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/output/grid.300000.dat +0 -0
- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/output/lambdakn.300000.dat +0 -0
- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/output/surf.300000.dat +209 -0
- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/runmpirun128.sh +18 -0
- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/runmpirun64.sh +18 -0
- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/slurm-28429925.out +205 -0
- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/surf/Surf_300000.vtu +38 -0
- CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/surf/geom.surf +610 -0
- CylinderKnMa/Kn0p36/simulation0788_Kn0p36Ma5p7/Grid.pvd +9 -0
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- CylinderKnMa/Kn0p36/simulation0788_Kn0p36Ma5p7/Lambda/Lambda_300000.pvtu +21 -0
- CylinderKnMa/Kn0p36/simulation0788_Kn0p36Ma5p7/Lambda/Lambda_3_300000.vtu +27 -0
- CylinderKnMa/Kn0p36/simulation0788_Kn0p36Ma5p7/Surf.pvd +9 -0
- CylinderKnMa/Kn0p36/simulation0788_Kn0p36Ma5p7/config.txt +78 -0
- CylinderKnMa/Kn0p36/simulation0788_Kn0p36Ma5p7/cylinder.surf +410 -0
- CylinderKnMa/Kn0p36/simulation0788_Kn0p36Ma5p7/gas.species +14 -0
- CylinderKnMa/Kn0p36/simulation0788_Kn0p36Ma5p7/gas.vhs +9 -0
.gitattributes
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CylinderKnMa/Kn0p30/simulation0644_Kn0p30Ma6p3/output/grid.300000.dat filter=lfs diff=lfs merge=lfs -text
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CylinderKnMa/Kn0p30/simulation0645_Kn0p30Ma6p4/output/grid.300000.dat filter=lfs diff=lfs merge=lfs -text
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CylinderKnMa/Kn0p30/simulation0649_Kn0p30Ma6p8/output/grid.300000.dat filter=lfs diff=lfs merge=lfs -text
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CylinderKnMa/Kn0p30/simulation0644_Kn0p30Ma6p3/output/grid.300000.dat filter=lfs diff=lfs merge=lfs -text
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CylinderKnMa/Kn0p30/simulation0645_Kn0p30Ma6p4/output/grid.300000.dat filter=lfs diff=lfs merge=lfs -text
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CylinderKnMa/Kn0p30/simulation0649_Kn0p30Ma6p8/output/grid.300000.dat filter=lfs diff=lfs merge=lfs -text
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CylinderKnMa/Kn0p30/simulation0650_Kn0p30Ma6p9/output/grid.300000.dat filter=lfs diff=lfs merge=lfs -text
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CylinderKnMa/Kn0p32/simulation0651_Kn0p32Ma2p0/output/grid.300000.dat filter=lfs diff=lfs merge=lfs -text
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CylinderKnMa/Kn0p30/simulation0650_Kn0p30Ma6p9/output/grid.300000.dat
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CylinderKnMa/Kn0p36/simulation0786_Kn0p36Ma5p5/Lambda/Lambda_3_300000.vtu
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AQAAAACAAABAHgAA1wQAAA==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AQAAAACAAADyAAAADAAAAA==eJzj5BxpAAAK4QiD
|
| 26 |
+
</AppendedData>
|
| 27 |
+
</VTKFile>
|
CylinderKnMa/Kn0p36/simulation0786_Kn0p36Ma5p5/output/grid.300000.dat
ADDED
|
The diff for this file is too large to render.
See raw diff
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|
CylinderKnMa/Kn0p36/simulation0786_Kn0p36Ma5p5/output/lambdakn.300000.dat
ADDED
|
The diff for this file is too large to render.
See raw diff
|
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CylinderKnMa/Kn0p36/simulation0786_Kn0p36Ma5p5/output/surf.300000.dat
ADDED
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@@ -0,0 +1,209 @@
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|
| 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 0.00212 0.051844 -0.051838 0.00081433 -2.9422e-05 -0.0018729 -0.00081469 -1.6627e-05 12.485 0 0
|
| 11 |
+
129 -0.31871 0.38526 -0.30645 0.39508 0.12699 3.4471 2.1553 -2.6902 0.58032 0.46492 0.042969 -0.034954 991.66 0 0
|
| 12 |
+
2 0.49975 -0.015705 0.49901 -0.031395 0.00213 0.051724 -0.051666 0.0024365 2.8163e-06 5.9719e-05 -0.00081149 3.9209e-05 9.6709 0 0
|
| 13 |
+
130 -0.30645 0.39508 -0.29389 0.40451 0.12012 3.2831 1.9712 -2.6255 0.59762 0.4487 0.04035 -0.034191 957.66 0 0
|
| 14 |
+
3 0.49901 -0.031395 0.49778 -0.047054 0.00201 0.04606 -0.045918 0.0036138 0.0002573 0.0032694 -0.0007172 0.00010812 12.099 0 0
|
| 15 |
+
131 -0.29389 0.40451 -0.28104 0.41354 0.11511 3.1098 1.7881 -2.5443 0.56794 0.39916 0.037008 -0.033694 911.9 0 0
|
| 16 |
+
4 0.49778 -0.047054 0.49606 -0.062667 0.00178 0.045541 -0.045266 0.0049974 -0.00012893 -0.0011678 -0.00071303 6.0153e-05 10.215 0 0
|
| 17 |
+
132 -0.28104 0.41354 -0.26791 0.42216 0.10849 2.9557 1.6227 -2.4704 0.59609 0.39156 0.034852 -0.032653 894.84 0 0
|
| 18 |
+
5 0.49606 -0.062667 0.49384 -0.078217 0.00214 0.056265 -0.055704 0.0079278 0.00057945 0.0040714 -0.00086585 0.00018848 12.786 0 0
|
| 19 |
+
133 -0.26791 0.42216 -0.25452 0.43037 0.10267 2.8033 1.4647 -2.3902 0.60063 0.36807 0.032441 -0.031763 839.53 0 0
|
| 20 |
+
6 0.49384 -0.078217 0.49114 -0.093691 0.00194 0.046602 -0.045908 0.0080123 0.00025825 0.0014797 -0.00071704 0.00014909 10.956 0 0
|
| 21 |
+
134 -0.25452 0.43037 -0.24088 0.43815 0.09887 2.6884 1.332 -2.3352 0.60926 0.34752 0.030492 -0.031221 805.69 0 0
|
| 22 |
+
7 0.49114 -0.093691 0.48796 -0.10907 0.00174 0.041802 -0.040933 0.0084768 0.00089032 0.0042992 -0.00062896 0.00020068 11.017 0 0
|
| 23 |
+
135 -0.24088 0.43815 -0.227 0.4455 0.09124 2.479 1.16 -2.1909 0.61663 0.32649 0.027906 -0.029285 756.17 0 0
|
| 24 |
+
8 0.48796 -0.10907 0.48429 -0.12434 0.00191 0.04455 -0.043319 0.0104 0.0016538 0.0068884 -0.00065446 0.00027156 11.511 0 0
|
| 25 |
+
136 -0.227 0.4455 -0.21289 0.45241 0.08644 2.3646 1.0403 -2.1235 0.56541 0.27699 0.025221 -0.029003 721.54 0 0
|
| 26 |
+
9 0.48429 -0.12434 0.48015 -0.1395 0.00195 0.046332 -0.04469 0.012226 0.00089552 0.0032735 -0.00068789 0.00024345 11.284 0 0
|
| 27 |
+
137 -0.21289 0.45241 -0.19857 0.45888 0.08181 2.2065 0.90802 -2.011 0.5616 0.25357 0.023084 -0.027605 666.43 0 0
|
| 28 |
+
10 0.48015 -0.1395 0.47553 -0.15451 0.0018 0.043072 -0.041168 0.012665 0.003057 0.0099369 -0.00059862 0.00035501 10.599 0 0
|
| 29 |
+
138 -0.19857 0.45888 -0.18406 0.46489 0.07568 2.0539 0.78598 -1.8975 0.58745 0.24333 0.021573 -0.025983 652.72 0 0
|
| 30 |
+
11 0.47553 -0.15451 0.47044 -0.16937 0.00178 0.043148 -0.040821 0.013976 0.0015527 0.0045349 -0.00061681 0.00029076 10.993 0 0
|
| 31 |
+
139 -0.18406 0.46489 -0.16937 0.47044 0.07072 1.9173 0.67771 -1.7935 0.56745 0.21442 0.019558 -0.024803 594.03 0 0
|
| 32 |
+
12 0.47044 -0.16937 0.46489 -0.18406 0.00163 0.034231 -0.032021 0.0121 0.0028054 0.0074242 -0.0004589 0.00030667 8.5904 0 0
|
| 33 |
+
140 -0.16937 0.47044 -0.15451 0.47553 0.06647 1.7866 0.57872 -1.6903 0.5668 0.19406 0.017993 -0.023502 573.24 0 0
|
| 34 |
+
13 0.46489 -0.18406 0.45888 -0.19857 0.00194 0.044619 -0.041222 0.017075 0.004624 0.011163 -0.00057486 0.00044355 12.189 0 0
|
| 35 |
+
141 -0.15451 0.47553 -0.1395 0.48015 0.06237 1.6659 0.48984 -1.5922 0.5276 0.16231 0.015981 -0.02246 528.82 0 0
|
| 36 |
+
14 0.45888 -0.19857 0.45241 -0.21289 0.0019 0.043018 -0.039207 0.017703 0.0041254 0.0091368 -0.00055104 0.00042157 11.428 0 0
|
| 37 |
+
142 -0.1395 0.48015 -0.12434 0.48429 0.05906 1.5969 0.42137 -1.5403 0.55066 0.15064 0.015268 -0.021827 511.21 0 0
|
| 38 |
+
15 0.45241 -0.21289 0.4455 -0.227 0.00187 0.043408 -0.038982 0.019097 0.0051358 0.010483 -0.00053163 0.00046463 12.383 0 0
|
| 39 |
+
143 -0.12434 0.48429 -0.10907 0.48796 0.05474 1.4697 0.34309 -1.4291 0.50678 0.12167 0.013349 -0.020536 473.34 0 0
|
| 40 |
+
16 0.4455 -0.227 0.43815 -0.24088 0.00183 0.041167 -0.036382 0.019263 0.0052229 0.0098643 -0.00048943 0.00045752 11.066 0 0
|
| 41 |
+
144 -0.10907 0.48796 -0.093691 0.49114 0.05102 1.3602 0.27584 -1.332 0.48602 0.10065 0.011967 -0.019341 433.64 0 0
|
| 42 |
+
17 0.43815 -0.24088 0.43037 -0.25452 0.00191 0.041793 -0.036302 0.020707 0.009352 0.016396 -0.00042332 0.00058278 12.06 0 0
|
| 43 |
+
145 -0.093691 0.49114 -0.078217 0.49384 0.04647 1.2405 0.21329 -1.2221 0.4645 0.081068 0.010646 -0.017922 405.77 0 0
|
| 44 |
+
18 0.43037 -0.25452 0.42216 -0.26791 0.00225 0.048606 -0.041444 0.025397 0.013723 0.022394 -0.00043542 0.00075066 16.537 0 0
|
| 45 |
+
146 -0.078217 0.49384 -0.062667 0.49606 0.04524 1.2031 0.16952 -1.1911 0.48043 0.068376 0.010209 -0.017635 405.9 0 0
|
| 46 |
+
19 0.42216 -0.26791 0.41354 -0.28104 0.00192 0.040965 -0.034239 0.022491 0.011543 0.017573 -0.00035649 0.0006293 14.698 0 0
|
| 47 |
+
147 -0.062667 0.49606 -0.047054 0.49778 0.04111 1.0841 0.11896 -1.0776 0.45762 0.050522 0.0090566 -0.016132 368.66 0 0
|
| 48 |
+
20 0.41354 -0.28104 0.40451 -0.29389 0.00224 0.049605 -0.040584 0.028523 0.014887 0.021182 -0.00040364 0.00078074 16.825 0 0
|
| 49 |
+
148 -0.047054 0.49778 -0.031395 0.49901 0.03963 1.0417 0.081734 -1.0385 0.44605 0.035105 0.0082901 -0.015761 350.32 0 0
|
| 50 |
+
21 0.40451 -0.29389 0.39508 -0.30645 0.0021 0.043775 -0.035007 0.026284 0.016568 0.022066 -0.00028962 0.00075944 15.72 0 0
|
| 51 |
+
149 -0.031395 0.49901 -0.015705 0.49975 0.03552 0.91907 0.043294 -0.91805 0.40007 0.018867 0.0069641 -0.014124 302.04 0 0
|
| 52 |
+
22 0.39508 -0.30645 0.38526 -0.31871 0.00246 0.055453 -0.043277 0.034672 0.023661 0.029534 -0.00030812 0.0010085 19.862 0 0
|
| 53 |
+
150 -0.015705 0.49975 0 0.5 0.03216 0.86139 0.01353 -0.86128 0.39287 0.0061718 0.0063835 -0.013432 289.58 0 0
|
| 54 |
+
23 0.38526 -0.31871 0.37506 -0.33066 0.00246 0.052643 -0.04003 0.034189 0.023294 0.027273 -0.00026289 0.00096541 18.314 0 0
|
| 55 |
+
151 0 0.5 0.015705 0.49975 0.03087 0.8093 -0.012712 -0.8092 0.38866 -0.0061056 0.0059052 -0.012806 279.63 0 0
|
| 56 |
+
24 0.37506 -0.33066 0.36448 -0.34227 0.00283 0.063501 -0.046967 0.042737 0.03025 0.033244 -0.00026259 0.0011935 19.612 0 0
|
| 57 |
+
152 0.015705 0.49975 0.031395 0.49901 0.02741 0.71573 -0.033715 -0.71493 0.35486 -0.016735 0.0050444 -0.011493 255.54 0 0
|
| 58 |
+
25 0.36448 -0.34227 0.35355 -0.35355 0.003 0.067367 -0.048378 0.046882 0.03312 0.034178 -0.00023966 0.0012732 25.345 0 0
|
| 59 |
+
153 0.031395 0.49901 0.047054 0.49778 0.02459 0.63406 -0.049748 -0.63211 0.3292 -0.025908 0.0043894 -0.010336 227.1 0 0
|
| 60 |
+
26 0.35355 -0.35355 0.34227 -0.36448 0.00313 0.069853 -0.048612 0.050163 0.034576 0.033507 -0.00022046 0.0013142 25.81 0 0
|
| 61 |
+
154 0.047054 0.49778 0.062667 0.49606 0.02279 0.58549 -0.064248 -0.58195 0.30207 -0.033349 0.0037355 -0.0096647 209.22 0 0
|
| 62 |
+
27 0.34227 -0.36448 0.33066 -0.37506 0.0033 0.072013 -0.048466 0.053263 0.041679 0.037925 -0.0001066 0.0014323 29.255 0 0
|
| 63 |
+
155 0.062667 0.49606 0.078217 0.49384 0.02307 0.59018 -0.083157 -0.58429 0.32416 -0.046135 0.0037855 -0.0099023 218.66 0 0
|
| 64 |
+
28 0.33066 -0.37506 0.31871 -0.38526 0.00388 0.087 -0.056502 0.066156 0.049145 0.041974 -0.00011556 0.0016984 31.887 0 0
|
| 65 |
+
156 0.078217 0.49384 0.093691 0.49114 0.01962 0.49567 -0.085219 -0.48829 0.27944 -0.048771 0.0030508 -0.0084357 186.32 0 0
|
| 66 |
+
29 0.31871 -0.38526 0.30645 -0.39508 0.00449 0.099844 -0.062426 0.077921 0.058198 0.046626 -6.6411e-05 0.0019563 39.204 0 0
|
| 67 |
+
157 0.093691 0.49114 0.10907 0.48796 0.01767 0.44376 -0.089988 -0.43454 0.2528 -0.052352 0.0025573 -0.0076477 164.1 0 0
|
| 68 |
+
30 0.30645 -0.39508 0.29389 -0.40451 0.00493 0.11031 -0.066232 0.088213 0.071152 0.053422 7.7273e-05 0.0022247 43.97 0 0
|
| 69 |
+
158 0.10907 0.48796 0.12434 0.48429 0.0166 0.41949 -0.097929 -0.4079 0.23809 -0.05716 0.0022015 -0.0073049 153.9 0 0
|
| 70 |
+
31 0.29389 -0.40451 0.28104 -0.41354 0.00517 0.11964 -0.068796 0.097886 0.067023 0.047105 -2.7844e-05 0.0022774 47.384 0 0
|
| 71 |
+
159 0.12434 0.48429 0.1395 0.48015 0.01513 0.37323 -0.098486 -0.36 0.21938 -0.060014 0.0018988 -0.0065974 143.35 0 0
|
| 72 |
+
32 0.28104 -0.41354 0.26791 -0.42216 0.00565 0.12924 -0.070957 0.10802 0.089658 0.058894 0.00029373 0.0026218 58.696 0 0
|
| 73 |
+
160 0.1395 0.48015 0.15451 0.47553 0.01344 0.33789 -0.099353 -0.32295 0.21341 -0.065655 0.0017916 -0.0061039 136.69 0 0
|
| 74 |
+
33 0.26791 -0.42216 0.25452 -0.43037 0.0063 0.15108 -0.078938 0.12881 0.090561 0.055496 0.00018257 0.002895 58.941 0 0
|
| 75 |
+
161 0.15451 0.47553 0.16937 0.47044 0.01241 0.30525 -0.098876 -0.28879 0.18648 -0.063847 0.0013761 -0.005539 119.19 0 0
|
| 76 |
+
34 0.25452 -0.43037 0.24088 -0.43815 0.00648 0.14858 -0.073617 0.12906 0.10123 0.057741 0.00043373 0.0029342 60.055 0 0
|
| 77 |
+
162 0.16937 0.47044 0.18406 0.46489 0.01114 0.27268 -0.096387 -0.25508 0.17111 -0.064658 0.0011737 -0.0050222 108.51 0 0
|
| 78 |
+
35 0.24088 -0.43815 0.227 -0.4455 0.00788 0.1907 -0.089235 0.16854 0.12056 0.063835 0.00049209 0.0036499 80.256 0 0
|
| 79 |
+
163 0.18406 0.46489 0.19857 0.45888 0.01066 0.26079 -0.0998 -0.24094 0.15792 -0.065412 0.0009129 -0.004812 100.15 0 0
|
| 80 |
+
36 0.227 -0.4455 0.21289 -0.45241 0.00812 0.19387 -0.085291 0.1741 0.12204 0.059789 0.00057729 0.0036738 78.215 0 0
|
| 81 |
+
164 0.19857 0.45888 0.21289 0.45241 0.00919 0.22378 -0.092089 -0.20395 0.14237 -0.064281 0.00078973 -0.0042132 89.605 0 0
|
| 82 |
+
37 0.21289 -0.45241 0.19857 -0.45888 0.0091 0.22277 -0.091675 0.20304 0.14633 0.066069 0.00085844 0.0042269 90.596 0 0
|
| 83 |
+
165 0.21289 0.45241 0.227 0.4455 0.00862 0.20432 -0.089889 -0.18349 0.13488 -0.066078 0.00070673 -0.00392 80.751 0 0
|
| 84 |
+
38 0.19857 -0.45888 0.18406 -0.46489 0.01027 0.25226 -0.096534 0.23305 0.15218 0.063033 0.00087398 0.0046507 97.997 0 0
|
| 85 |
+
166 0.227 0.4455 0.24088 0.43815 0.0079 0.18591 -0.086992 -0.1643 0.11596 -0.061397 0.00045501 -0.0035451 71.816 0 0
|
| 86 |
+
39 0.18406 -0.46489 0.16937 -0.47044 0.01114 0.27333 -0.096614 0.25568 0.17586 0.066453 0.0012448 0.0050599 109.03 0 0
|
| 87 |
+
167 0.24088 0.43815 0.25452 0.43037 0.00663 0.15416 -0.076381 -0.13391 0.10279 -0.058629 0.00041477 -0.0030243 62.647 0 0
|
| 88 |
+
40 0.16937 -0.47044 0.15451 -0.47553 0.01311 0.31795 -0.10299 0.30081 0.1863 0.063786 0.0013086 0.0057268 115.22 0 0
|
| 89 |
+
168 0.25452 0.43037 0.26791 0.42216 0.00607 0.13653 -0.071334 -0.11641 0.092047 -0.056407 0.00032535 -0.0027144 56.7 0 0
|
| 90 |
+
41 0.15451 -0.47553 0.1395 -0.48015 0.01333 0.33612 -0.098834 0.32126 0.1971 0.060636 0.0015435 0.0059986 128.75 0 0
|
| 91 |
+
169 0.26791 0.42216 0.28104 0.41354 0.0054 0.12615 -0.06926 -0.10544 0.076488 -0.050243 0.00011353 -0.0024453 50.24 0 0
|
| 92 |
+
42 0.1395 -0.48015 0.12434 -0.48429 0.0158 0.39455 -0.10411 0.38056 0.22528 0.061629 0.0019032 0.0069457 139.69 0 0
|
| 93 |
+
170 0.28104 0.41354 0.29389 0.40451 0.00517 0.11954 -0.068738 -0.097804 0.076465 -0.053741 0.00012138 -0.0023804 48.776 0 0
|
| 94 |
+
43 0.12434 -0.48429 0.10907 -0.48796 0.01614 0.40719 -0.095057 0.39594 0.24314 0.058373 0.002326 0.0071361 162.29 0 0
|
| 95 |
+
171 0.29389 0.40451 0.30645 0.39508 0.0046 0.10585 -0.063557 -0.08465 0.066361 -0.049825 4.4035e-05 -0.0021122 43.358 0 0
|
| 96 |
+
44 0.10907 -0.48796 0.093691 -0.49114 0.0184 0.47209 -0.095734 0.46228 0.26177 0.054209 0.0026079 0.0081127 169.05 0 0
|
| 97 |
+
172 0.30645 0.39508 0.31871 0.38526 0.00433 0.10093 -0.063106 -0.07877 0.06202 -0.049688 -1.706e-05 -0.0020177 42.774 0 0
|
| 98 |
+
45 0.093691 -0.49114 0.078217 -0.49384 0.01969 0.50432 -0.086708 0.49681 0.27617 0.048199 0.0029759 0.0085607 187.36 0 0
|
| 99 |
+
173 0.31871 0.38526 0.33066 0.37506 0.00368 0.080793 -0.052471 -0.061435 0.046796 -0.039967 -8.9139e-05 -0.0015928 32.384 0 0
|
| 100 |
+
46 0.078217 -0.49384 0.062667 -0.49606 0.02079 0.52798 -0.074393 0.52271 0.28477 0.040528 0.0033044 0.008847 188.74 0 0
|
| 101 |
+
174 0.33066 0.37506 0.34227 0.36448 0.00359 0.080502 -0.054179 -0.059542 0.04768 -0.043385 -0.00010209 -0.0016167 32.174 0 0
|
| 102 |
+
47 0.062667 -0.49606 0.047054 -0.49778 0.0236 0.62198 -0.068253 0.61823 0.31384 0.034648 0.0038575 0.010255 221.77 0 0
|
| 103 |
+
175 0.34227 0.36448 0.35355 0.35355 0.0034 0.075705 -0.052684 -0.054366 0.037915 -0.036743 -0.00023198 -0.0014311 26.005 0 0
|
| 104 |
+
48 0.047054 -0.49778 0.031395 -0.49901 0.02579 0.67283 -0.05279 0.67076 0.3437 0.02705 0.0045695 0.010961 233.4 0 0
|
| 105 |
+
176 0.35355 0.35355 0.36448 0.34227 0.00298 0.064024 -0.045978 -0.044555 0.030823 -0.031807 -0.00023804 -0.0011994 24.24 0 0
|
| 106 |
+
49 0.031395 -0.49901 0.015705 -0.49975 0.02672 0.6977 -0.032866 0.69693 0.33161 0.015639 0.0046925 0.011192 242.38 0 0
|
| 107 |
+
177 0.36448 0.34227 0.37506 0.33066 0.00267 0.058515 -0.043279 -0.039381 0.030932 -0.033994 -0.00019394 -0.0011525 25.672 0 0
|
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|
CylinderKnMa/Kn0p36/simulation0786_Kn0p36Ma5p5/surf/Surf_300000.vtu
ADDED
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| 1 |
+
<?xml version="1.0"?>
|
| 2 |
+
<VTKFile type="UnstructuredGrid" version="0.1" byte_order="LittleEndian" header_type="UInt32" compressor="vtkZLibDataCompressor">
|
| 3 |
+
<UnstructuredGrid>
|
| 4 |
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<Piece NumberOfPoints="400" NumberOfCells="200" >
|
| 5 |
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<PointData>
|
| 6 |
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</PointData>
|
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AQAAAACAAABABgAA6QUAAA==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AQAAAACAAABABgAAFAYAAA==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AQAAAACAAABABgAABQYAAA==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AQAAAACAAABABgAADQYAAA==eJwt0ok/1AkABfAou5UuNJWI5MhVKrnTW9XWKIpCpIMN6VPZibWbDpJJJZWQpHFFmYoc89GgMiGMJecMw4y5fqaQoqQhWas+/QXvfd775oQ3nOzt/K9c48JfTiPptRsFD9pItYI1UKd5bDF9s5yVG+4dUPttE3qiRc7MgTWYRrXOvmrqjJ1KkbYxS7yR+iXkurGnMyxvVPn8N/so8uiaH8IpXvBVVKV7jQfA1PdEbOpQMHBvT2a9jAL/vrTmrbNCccBX+epdv1BQCqzW6q2MwsPKdMnrpbFo8Ry342ddgiON5Kp27jqSR7Po5vI4uNlVcZJsk0GiV4t9u27DR9a8gj+Whi5Jft3SkQw4ykNmf2JkottAYDLscR++S6NvXDZ6CGrqH9zlDXm4Q1UOm2FVBKeghV7HDAsxqduW2Tb8FCVKO0IVzJgorjqUYNFfioLc9UZK3eUIZb+mTN/Igr6dpeLHskq0hF07cO90Fcb3eqQkXqjBXff0x3m8WhjsUcqKt63DjgJr2hi3ASFlpgaW2k3QeLZlpP1lM06VXh58ldsC35PWw49tWqG6U/ngZxIHWjm95NWTXBgxHAzUbbiQtNSoHPvYAcfP62JkSTw0Pmriegx0ItmJFLu9vws19/oG/CgCLCa7fFsSIoJe6bdLn/kiaN9rWfaqUQgQlZFxphL8QfrTT2tMjNzJkGQzMwmoIxHzhmUShKiIrniZScHVsaqaOyoBcbl4dOE0AnEZo2vfPJH+3IuAIHDan5EzCOjRFj3vNSHQsX7Q+vdtBDxM1MIfphNgJz9Lipsvhf5vzqu830kx5LKwVy1MinX/rNLR/izGbt/jOmwHCbJF5fNo5mIUBdraqWuKMP7XhoCMdUIkNX3aUGLHx4NwoVt2ZRdqO9K8VDN4OKzsMG97cgf0+1LqrPgcqN29cWxzNQd9zPzpb2NbYWJxJoO0pBnv/SiJz23rsde7kDWQxoaMsWH+h8YaXDzU/9b590oIOiJDtiaW46o4wqSzsBRWOfEKGTEMJF66uK/t+WM0ul3eJpVlYoSXpHDEKBOEe7tlNRGP0YRY+caCcFBX3nHQyfEDRW6oqkgng/m30i6RrTWmsWepbWUEI0InxUy2jgp1K4vms43X0DilBLEZyJggq6h7PMTqvOhX9klPEG3/fqjDrxh88x2KHE4Z+v89EqYleIEtQdEaQ2MVCNMdZmvPYSPzCKM/pLgOpGV1MmTXw8NfRKqYbEbvmkMHz59rxaZbKfbNszn4NGi+WnMmF4ToyH7rBTzEFEj6bhXxEGlQGZ2ztwvFbsLrlH0CbP/13aTmm+6fzsRoJeSWE50ivNaNWDMkkMC+xO4Y84AEtrrbz0RNefgmfIDxm1KwB098ZWgTPx1JIdQedDdRI2D8I5BAnRevbV4EgdOUf9qDnhE4n7LvaftiKeaKV00RkmD/coePhxukKPl+l6EUX9+/e2mjK0VVm4m/ulQMu56AEoV0Ccgx7IIYKzE2DThlDi8V4cNZWBws64aWRuSpAywhUp5G+N937Mavh77LF2DWokvmrJRO8Bf5W7L1OtHT5bK2UcRDp/4j5i9P2zHxJVRMU+FCHl8TuMy9DXHyR7dmsTgICnLa5Sltwd8nNaYqNkM5+WXes7BG8FlFrdkLGxDb7sqd4VqPm9y8tARhLVb5KDI/vKlGwNrCsRLLV5izQa612qYS2ZYng1mbK/D4bbb8Wv4LuC/xnhnsUoYKWWGAXxwTdLcrRcxEBlx6HFstEhjgdZRxZk4UoNr9+5H5YDYZm98fyYFhiadr1FE6fjA/mgXzSn7Ugrh0zDl1xzcrNx2e9al3fKxv44ICdb7+vniouI+aP/dKwAMjRZqw+ioOG67scidfwVclH3qgKxWt5wb1N285jzMaX9o1FpxFy/rglSvmnkJ7fpP8CS0Qm2QzVEsvHoZ4793ifxWP41YuZyLviR+clQwiF9fuxvplQ/mco5sxrD18jmxsA6rrcq1dA/Ywfm/g3ZLtBBO9XWSdCG3Wnvyqt7YNo+Wp9FTy60c6Uzu9TNHMnI6KbbSG0/t7Nv4PWmUZow==AQAAAACAAABABgAALQYAAA==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AQAAAACAAABABgAA1QMAAA==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eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAABABgAAFQAAAA==eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAADAEgAA0gMAAA==eJxt2D1IlmEUxvE3KNqKtiJosyWMtoLe5+jm0FJDSbg0Bg3h0odBSFtBVEsfUBC12GIRtPShLS0tQiEVJAoFQURUIhmWdg5enA7PPyH4gfL2vPdzznWf++50On0d/dybXbErY6NP2x4/u2IHrneetb19ZtneP+mH9y79saHBUbjn3W8b2nUb7j25ZB/mJuHx6V/2/cgsvGnhp10eW4anphfsy5sNE20Pn5q3kd3b4Msz32zj8V54et1XezXShRe/f7bFQ/vgyTufbGLlMLxmy0cbHj4K3zk4Z8fGTsDXDr+3C/vPwXM9b+3HjvPwxSev7eHHS/CzrVO2+fRV+MbASxv5dBMe6n9he3behQfWP7en++7BD249tjN2H55f+8j8H+y/N/872D/P/HNh///NnwP25zV/bti/n/n3hH09zNcF9vUzX0fY19t83WF/P+bvCfb3af5eYX//5nUAe72Y1w3s9WVeZ7DXo3ldwl6/5nUMe72b1z3s/dF4n8DeT433Fez913gfwt6vjfctPTjaeJ/DngeN5wLs+dF4jsCeN13PHVg/k21HPpW/T0c+lc9PRz6V50lHPpXn/2fPp/J905FPZX3SkU9lPdORT2X905FP5X2lI5/K+01HPpV6SEc+lfpJRz6VektHPpX6TEc+lXpORz6V+k9HPpV+SUc+lf5KRz6VfkxHPpX+TUc+lX5PRz6VfEhHPpU8SUc+lfxJRz6VvErH70u+pePzSh6m4/8v+ZmO5y15m47vV/I5HetR8jwd61fyPx3rXfaLdLyfsr+k432W/Sgd77/sX+mol7LfpaO+yv6Yjnos+2k66rfsv+mo97Jfp6M/yv6ejn4q80A6+q/MD+no1zJvpKO/y3ySjjwo80w68qPMP+nImzIvpTv/yaryN9229ZlN23oGWM8M6zvCWhNYawhrzWG9I2tb7xRWDcCqGVg1BqsmYdUwrJqH1SOwegpWD8LqWVg9DisTYGUIrMyBlVGwMg1WBsLKTFgZCyuTYWU4rMyHtUfA2lNg7UGw9ixYexysPRHWHgprz4W1R8Pa02HNALBmBlgzBr06k8CaYWDNPLBmJFg/fW1rBrO2NbPBmvFgzYT06gwJa+aENaPCmmlhzcCwZmZYMzasmRzWDA9r5od1RoB1poB1BoF1ZoF1xoF1JoJ1hoJ15oJ1RoN1poN1BoR1ZoR1xoR1JoV1hoV15oV1RoZ1poZ1Bod1Zod1xod1JwDrDgHWnQOsOwpYdxqw7kBg3Zk0beuOBdadDKw7HFh3PrDuiGDdKcG6g+q23SlZ9RcRPekTAQAAAACAAACADAAAkgIAAA==eJw11WODEAYAgOF8l23b7rJ1GdddtnHZtnHVvNpqy21hy7Ztt4Whtmz3oaf3y/MT3kiRPhWZURiV0RidMRjAQMZkLMZmHMZlPMZnAiZkIiZmEiZlMiZnCqZkKqZmGqZlOqZnBmZkJmZmFmZlNmZnDuZkLuZmHuZlPuZnARZkIRZmEQaxKIuxOEuwJEuxNMuwLMuxPCuwIiuxMquwKoNZjdVZgzVZi7VZh3VZj/UZwgYMZRgbshEbswmbshmbswVbshVbsw3bsh3bswM7shM7swu7shvD2Z092JO92Jt92Jf92J8DOJCDOJhDOJTDOJwjOJKjOJpjOJbjOJ4TOJGTOJlTOJXTOJ0zGMGZnMXZ/IJf8it+zW/4Lb/j95zDufyBP3Ie5/Mn/swFXMhFXMwlXMplXM5f+CtXcCVXcTV/4+9cw7Vcx/XcwI3cxM3cwq3cxu3cwZ3cxd3cw73cx/08wIM8xMM8wqM8xuM8wZM8xdM8w7M8x/O8wIu8xMu8wqu8xuv8g3/yBm/yFm/zL/7Nf/gv7/Au/+P/vMf7fMCHfMTHfMKnfMbnfMGXfMXXfMO3fMf3/MDP44/MKIzKaIzOGAxgIGMyFmMzDuMyHuMzARMyERMzCZMyGZMzBVMyFVMzDdMyHdMzAzMyEzMzC7MyG7MzB3MyF3MzD/MyH/OzAAuyEAuzCINYlMVYnCVYkqVYmmVYluVYnhVYkZVYmVVYlcGsxuqswZqsxdqsw7qsx/oMYQOGMowN2YiN2YRN2YzN2YIt2Yqt2YZt2Y7t2YEd2Ymd2YVd2Y3h7M4e7Mle7M0+7Mt+7M8BHMhBHMwhHMphHM4RHMlRHM0xHMtxHM8JnMhJnMwpnMppnM4ZjOBHXq+oSQ==AQAAAACAAABABgAAXwEAAA==eJwtxVFEHAAAANBKkpzkJEmSJMlJkiRJkiRJkiQnSXKSJEmSJEmSJEmSZGYmmUmSJEmSJEkyMzOTzCRJkmT20Xs/LybqXazjHO8EB5zoJAed7BSnOs3pznCms5ztHOc6zyHnu8CFLnKxS1zqMpe7wpW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|
| 37 |
+
</AppendedData>
|
| 38 |
+
</VTKFile>
|
CylinderKnMa/Kn0p36/simulation0786_Kn0p36Ma5p5/surf/geom.surf
ADDED
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| 1 |
+
# Surface element file written by SPARTA
|
| 2 |
+
|
| 3 |
+
400 points
|
| 4 |
+
200 lines
|
| 5 |
+
|
| 6 |
+
Points
|
| 7 |
+
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| 8 |
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/jfcPOfNiBA==AQAAAACAAADARAAAhQIAAA==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AQAAAACAAADARAAA3i4AAA==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AQAAAACAAADkbAAAExUAAA==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AQAAAACAAADARAAAdAsAAA==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|
| 26 |
+
</AppendedData>
|
| 27 |
+
</VTKFile>
|
CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/Lambda/Lambda_2_300000.vtu
ADDED
|
@@ -0,0 +1,27 @@
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|
| 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="1212" NumberOfCells="1100" >
|
| 5 |
+
<PointData>
|
| 6 |
+
</PointData>
|
| 7 |
+
<CellData>
|
| 8 |
+
<DataArray type="Float64" Name="id" format="appended" RangeMin="12201" RangeMax="13520" offset="0" />
|
| 9 |
+
<DataArray type="Float64" Name="xc" format="appended" RangeMin="-4.9549" RangeMax="3.9713" offset="1968" />
|
| 10 |
+
<DataArray type="Float64" Name="yc" format="appended" RangeMin="4.0541" RangeMax="4.955" offset="3060" />
|
| 11 |
+
<DataArray type="Float64" Name="c_6[1]" format="appended" RangeMin="0.018515" RangeMax="0.033177" offset="3292" />
|
| 12 |
+
<DataArray type="Float64" Name="c_6[2]" format="appended" RangeMin="0.20535" RangeMax="0.36797" offset="9052" />
|
| 13 |
+
</CellData>
|
| 14 |
+
<Points>
|
| 15 |
+
<DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="4.0092183641" RangeMax="7.0710678119" offset="14852" />
|
| 16 |
+
</Points>
|
| 17 |
+
<Cells>
|
| 18 |
+
<DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="19552" />
|
| 19 |
+
<DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="27548" />
|
| 20 |
+
<DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="29576" />
|
| 21 |
+
</Cells>
|
| 22 |
+
</Piece>
|
| 23 |
+
</UnstructuredGrid>
|
| 24 |
+
<AppendedData encoding="base64">
|
| 25 |
+
_AQAAAACAAABgIgAAsgUAAA==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AQAAAACAAABgIgAAmwAAAA==eJzt160KwgAAhdEiWP1BwaKYBatpsGiYZSs2NawsWQwmkzAWNFgEs+AjjIFpXXAmDRYtYhhosYiC1fsIXzrPcKJT8HZbOTNCxD/LXuc5WyCicn591JIUEZXZ3tIqWXlEFE6Oxri7QUTly7msV5kCIgqHOz859xFReWs3P/UtIioH8aHhVoqIKPw1ZISISjusTu97RFR+AbvHGoI=AQAAAACAAABgIgAAzhAAAA==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AQAAAACAAADQOAAAsg0AAA==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AgAAAACAAACACQAAohUAALUBAAA=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AQAAAACAAABgIgAA3wUAAA==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eJzj5BwFo2AUjALKAQAyByat
|
| 26 |
+
</AppendedData>
|
| 27 |
+
</VTKFile>
|
CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/Lambda/Lambda_300000.pvtu
ADDED
|
@@ -0,0 +1,21 @@
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|
|
|
| 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="c_6[1]"/>
|
| 11 |
+
<PDataArray type="Float64" Name="c_6[2]"/>
|
| 12 |
+
</PCellData>
|
| 13 |
+
<PPoints>
|
| 14 |
+
<PDataArray type="Float32" Name="Points" NumberOfComponents="3"/>
|
| 15 |
+
</PPoints>
|
| 16 |
+
<Piece Source="Lambda_0_300000.vtu"/>
|
| 17 |
+
<Piece Source="Lambda_1_300000.vtu"/>
|
| 18 |
+
<Piece Source="Lambda_2_300000.vtu"/>
|
| 19 |
+
<Piece Source="Lambda_3_300000.vtu"/>
|
| 20 |
+
</PUnstructuredGrid>
|
| 21 |
+
</VTKFile>
|
CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/Lambda/Lambda_3_300000.vtu
ADDED
|
@@ -0,0 +1,27 @@
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
| 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="276" NumberOfCells="242" >
|
| 5 |
+
<PointData>
|
| 6 |
+
</PointData>
|
| 7 |
+
<CellData>
|
| 8 |
+
<DataArray type="Float64" Name="id" format="appended" RangeMin="12301" RangeMax="13542" offset="0" />
|
| 9 |
+
<DataArray type="Float64" Name="xc" format="appended" RangeMin="4.0615" RangeMax="5.9549" offset="508" />
|
| 10 |
+
<DataArray type="Float64" Name="yc" format="appended" RangeMin="4.0541" RangeMax="4.955" offset="808" />
|
| 11 |
+
<DataArray type="Float64" Name="c_6[1]" format="appended" RangeMin="0.017933" RangeMax="0.033151" offset="976" />
|
| 12 |
+
<DataArray type="Float64" Name="c_6[2]" format="appended" RangeMin="0.19889" RangeMax="0.36767" offset="3416" />
|
| 13 |
+
</CellData>
|
| 14 |
+
<Points>
|
| 15 |
+
<DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="5.6748189645" RangeMax="7.8102496759" offset="5748" />
|
| 16 |
+
</Points>
|
| 17 |
+
<Cells>
|
| 18 |
+
<DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="6688" />
|
| 19 |
+
<DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="8364" />
|
| 20 |
+
<DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="8896" />
|
| 21 |
+
</Cells>
|
| 22 |
+
</Piece>
|
| 23 |
+
</UnstructuredGrid>
|
| 24 |
+
<AppendedData encoding="base64">
|
| 25 |
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|
| 26 |
+
</AppendedData>
|
| 27 |
+
</VTKFile>
|
CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/Surf.pvd
ADDED
|
@@ -0,0 +1,9 @@
|
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|
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|
|
|
|
|
|
|
|
|
|
|
| 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/Kn0p36/simulation0787_Kn0p36Ma5p6/config.txt
ADDED
|
@@ -0,0 +1,78 @@
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
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|
|
|
|
|
|
|
|
| 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 0.36
|
| 13 |
+
variable Ma equal 5.6
|
| 14 |
+
variable To equal 273.0
|
| 15 |
+
variable Tb equal 273.0
|
| 16 |
+
variable theta equal 0.0
|
| 17 |
+
variable mfp equal ${Kn}*${L}
|
| 18 |
+
variable cpmfp equal 4
|
| 19 |
+
variable nden equal 1.0/sqrt(2.0)/${PI}/${molecular_diameter}/${molecular_diameter}/(${mfp}/${cpmfp}*${Kn})
|
| 20 |
+
variable sos equal sqrt(${gamma}*${R}*${To})
|
| 21 |
+
variable vo equal ${Ma}*${sos}
|
| 22 |
+
variable vx equal ${vo}*cos(${theta}*2*PI/360)
|
| 23 |
+
variable vy equal ${vo}*sin(${theta}*2*PI/360)
|
| 24 |
+
variable ppc equal 30
|
| 25 |
+
variable xncells equal (${xmax}-${xmin})/${mfp}*${cpmfp}
|
| 26 |
+
variable yncells equal (${ymax}-${ymin})/${mfp}*${cpmfp}
|
| 27 |
+
variable Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
|
| 28 |
+
variable tstep equal (-${xmin}+${xmax})/${vx}/${xncells}/10/4
|
| 29 |
+
variable nave equal 10000
|
| 30 |
+
variable noutput equal 300000
|
| 31 |
+
clear
|
| 32 |
+
shell mkdir output
|
| 33 |
+
shell mkdir grid
|
| 34 |
+
shell mkdir surf
|
| 35 |
+
seed 7
|
| 36 |
+
dimension 2
|
| 37 |
+
global nrho ${nden}
|
| 38 |
+
global fnum ${Fnum}
|
| 39 |
+
timestep ${tstep}
|
| 40 |
+
global gridcut 1.0 particle/reorder 100 comm/sort yes
|
| 41 |
+
region 1 cylinder z 0.0 0.0 3.50 -0.5 0.5
|
| 42 |
+
region 2 cylinder z 0.0 0.0 2.00 -0.5 0.5
|
| 43 |
+
region 3 cylinder z 0.0 0.0 0.80 -0.5 0.5
|
| 44 |
+
boundary o o p
|
| 45 |
+
create_box ${xmin} ${xmax} ${ymin} ${ymax} -0.5 0.5
|
| 46 |
+
create_grid ${xncells} ${yncells} 1 levels 4 region 2 1 2 2 1 region 3 2 2 2 1 region 4 3 2 2 1 clump xyz
|
| 47 |
+
balance_grid rcb cell
|
| 48 |
+
species gas.species Ar
|
| 49 |
+
mixture air Ar frac 1.0
|
| 50 |
+
mixture air Ar vstream ${vx} ${vy} 0.0 temp ${To}
|
| 51 |
+
collide vss air gas.vhs
|
| 52 |
+
collide_modify vremax 100 yes remain no nearcp yes 10
|
| 53 |
+
read_surf cylinder.surf
|
| 54 |
+
surf_collide 1 diffuse 273.0 1.0
|
| 55 |
+
surf_modify all collide 1
|
| 56 |
+
fix in emit/face air xlo ylo yhi
|
| 57 |
+
balance_grid rcb cell
|
| 58 |
+
create_particles air n 0
|
| 59 |
+
stats 10000
|
| 60 |
+
stats_style step cpu np nattempt ncoll nscoll npave nscollave
|
| 61 |
+
run 200000
|
| 62 |
+
compute 1 grid all air n nrho massrho u v w
|
| 63 |
+
compute 2 grid all air trot
|
| 64 |
+
compute 3 tvib/grid all air
|
| 65 |
+
compute 4 thermal/grid all air press temp
|
| 66 |
+
fix 1 ave/grid all 1 ${nave} ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
|
| 67 |
+
dump 1 grid all ${noutput} output/grid.*.dat id xc yc f_1[*]
|
| 68 |
+
dump_modify 1 format float %12.5g
|
| 69 |
+
compute 5 surf all air n press px py shx shy fx fy etot erot evib
|
| 70 |
+
fix 2 ave/surf all 1 ${nave} ${nave} c_5[*] ave running
|
| 71 |
+
dump 2 surf all ${noutput} output/surf.*.dat id v1x v1y v2x v2y f_2[*]
|
| 72 |
+
dump_modify 2 format float %12.5g
|
| 73 |
+
compute 6 lambda/grid f_1[2] f_1[8] Ar kx
|
| 74 |
+
dump 3 grid all ${noutput} output/lambdakn.*.dat id xc yc c_6[*]
|
| 75 |
+
dump_modify 3 format float %12.5g
|
| 76 |
+
run 100000
|
| 77 |
+
write_grid grid/final-grid.dat
|
| 78 |
+
write_surf surf/geom.surf
|
CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/cylinder.surf
ADDED
|
@@ -0,0 +1,410 @@
|
|
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|
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|
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|
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|
|
|
|
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|
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|
|
|
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|
|
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|
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|
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|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
surf file from Pointwise
|
| 2 |
+
|
| 3 |
+
200 points
|
| 4 |
+
200 lines
|
| 5 |
+
|
| 6 |
+
Points
|
| 7 |
+
|
| 8 |
+
1 0.5 0.0
|
| 9 |
+
2 0.499753280182866E+000 -0.157053795390643E-001
|
| 10 |
+
3 0.499013364214136E+000 -0.313952597646568E-001
|
| 11 |
+
4 0.497780982301540E+000 -0.470541566592573E-001
|
| 12 |
+
5 0.496057350657239E+000 -0.626666167821523E-001
|
| 13 |
+
6 0.493844170297569E+000 -0.782172325201156E-001
|
| 14 |
+
7 0.491143625364344E+000 -0.936906572928624E-001
|
| 15 |
+
8 0.487958380969374E+000 -0.109071620698271E+000
|
| 16 |
+
9 0.484291580564315E+000 -0.124344943582427E+000
|
| 17 |
+
10 0.480146842838471E+000 -0.139495553019615E+000
|
| 18 |
+
11 0.475528258147577E+000 -0.154508497187474E+000
|
| 19 |
+
12 0.470440384477113E+000 -0.169368960122646E+000
|
| 20 |
+
13 0.464888242944126E+000 -0.184062276342339E+000
|
| 21 |
+
14 0.458877312841991E+000 -0.198573945317390E+000
|
| 22 |
+
15 0.452413526233010E+000 -0.212889645782536E+000
|
| 23 |
+
16 0.445503262094184E+000 -0.226995249869774E+000
|
| 24 |
+
17 0.438153340021932E+000 -0.240876837050858E+000
|
| 25 |
+
18 0.430371013501972E+000 -0.254520707875186E+000
|
| 26 |
+
19 0.422163962751007E+000 -0.267913397489498E+000
|
| 27 |
+
20 0.413540287137281E+000 -0.281041688926065E+000
|
| 28 |
+
21 0.404508497187474E+000 -0.293892626146237E+000
|
| 29 |
+
22 0.395077506187845E+000 -0.306453526826488E+000
|
| 30 |
+
23 0.385256621387895E+000 -0.318711994874345E+000
|
| 31 |
+
24 0.375055534815230E+000 -0.330655932661826E+000
|
| 32 |
+
25 0.364484313710706E+000 -0.342273552964344E+000
|
| 33 |
+
26 0.353553390593274E+000 -0.353553390593274E+000
|
| 34 |
+
27 0.342273552964344E+000 -0.364484313710706E+000
|
| 35 |
+
28 0.330655932661826E+000 -0.375055534815230E+000
|
| 36 |
+
29 0.318711994874345E+000 -0.385256621387895E+000
|
| 37 |
+
30 0.306453526826488E+000 -0.395077506187845E+000
|
| 38 |
+
31 0.293892626146236E+000 -0.404508497187474E+000
|
| 39 |
+
32 0.281041688926065E+000 -0.413540287137281E+000
|
| 40 |
+
33 0.267913397489498E+000 -0.422163962751008E+000
|
| 41 |
+
34 0.254520707875185E+000 -0.430371013501972E+000
|
| 42 |
+
35 0.240876837050857E+000 -0.438153340021932E+000
|
| 43 |
+
36 0.226995249869773E+000 -0.445503262094184E+000
|
| 44 |
+
37 0.212889645782536E+000 -0.452413526233010E+000
|
| 45 |
+
38 0.198573945317390E+000 -0.458877312841991E+000
|
| 46 |
+
39 0.184062276342339E+000 -0.464888242944126E+000
|
| 47 |
+
40 0.169368960122645E+000 -0.470440384477113E+000
|
| 48 |
+
41 0.154508497187474E+000 -0.475528258147577E+000
|
| 49 |
+
42 0.139495553019614E+000 -0.480146842838472E+000
|
| 50 |
+
43 0.124344943582427E+000 -0.484291580564316E+000
|
| 51 |
+
44 0.109071620698271E+000 -0.487958380969374E+000
|
| 52 |
+
45 0.936906572928621E-001 -0.491143625364344E+000
|
| 53 |
+
46 0.782172325201152E-001 -0.493844170297569E+000
|
| 54 |
+
47 0.626666167821520E-001 -0.496057350657239E+000
|
| 55 |
+
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+
155 155 156
|
| 366 |
+
156 156 157
|
| 367 |
+
157 157 158
|
| 368 |
+
158 158 159
|
| 369 |
+
159 159 160
|
| 370 |
+
160 160 161
|
| 371 |
+
161 161 162
|
| 372 |
+
162 162 163
|
| 373 |
+
163 163 164
|
| 374 |
+
164 164 165
|
| 375 |
+
165 165 166
|
| 376 |
+
166 166 167
|
| 377 |
+
167 167 168
|
| 378 |
+
168 168 169
|
| 379 |
+
169 169 170
|
| 380 |
+
170 170 171
|
| 381 |
+
171 171 172
|
| 382 |
+
172 172 173
|
| 383 |
+
173 173 174
|
| 384 |
+
174 174 175
|
| 385 |
+
175 175 176
|
| 386 |
+
176 176 177
|
| 387 |
+
177 177 178
|
| 388 |
+
178 178 179
|
| 389 |
+
179 179 180
|
| 390 |
+
180 180 181
|
| 391 |
+
181 181 182
|
| 392 |
+
182 182 183
|
| 393 |
+
183 183 184
|
| 394 |
+
184 184 185
|
| 395 |
+
185 185 186
|
| 396 |
+
186 186 187
|
| 397 |
+
187 187 188
|
| 398 |
+
188 188 189
|
| 399 |
+
189 189 190
|
| 400 |
+
190 190 191
|
| 401 |
+
191 191 192
|
| 402 |
+
192 192 193
|
| 403 |
+
193 193 194
|
| 404 |
+
194 194 195
|
| 405 |
+
195 195 196
|
| 406 |
+
196 196 197
|
| 407 |
+
197 197 198
|
| 408 |
+
198 198 199
|
| 409 |
+
199 199 200
|
| 410 |
+
200 200 1
|
CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/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/Kn0p36/simulation0787_Kn0p36Ma5p6/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/Kn0p36/simulation0787_Kn0p36Ma5p6/grid/Grid_0_300000.vtu
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/grid/Grid_1_300000.vtu
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/grid/Grid_2_300000.vtu
ADDED
|
@@ -0,0 +1,35 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 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="1212" NumberOfCells="1100" >
|
| 5 |
+
<PointData>
|
| 6 |
+
</PointData>
|
| 7 |
+
<CellData>
|
| 8 |
+
<DataArray type="Float64" Name="id" format="appended" RangeMin="12201" RangeMax="13520" offset="0" />
|
| 9 |
+
<DataArray type="Float64" Name="xc" format="appended" RangeMin="-4.9549" RangeMax="3.9713" offset="1968" />
|
| 10 |
+
<DataArray type="Float64" Name="yc" format="appended" RangeMin="4.0541" RangeMax="4.955" offset="3060" />
|
| 11 |
+
<DataArray type="Float64" Name="f_1[1]" format="appended" RangeMin="29.757" RangeMax="72.832" offset="3292" />
|
| 12 |
+
<DataArray type="Float64" Name="f_1[2]" format="appended" RangeMin="3.9515e+19" RangeMax="9.6715e+19" offset="7440" />
|
| 13 |
+
<DataArray type="Float64" Name="f_1[3]" format="appended" RangeMin="2.6199e-06" RangeMax="6.4122e-06" offset="13820" />
|
| 14 |
+
<DataArray type="Float64" Name="f_1[4]" format="appended" RangeMin="1515.4" RangeMax="1726.8" offset="19460" />
|
| 15 |
+
<DataArray type="Float64" Name="f_1[5]" format="appended" RangeMin="-2.3786" RangeMax="407.14" offset="21484" />
|
| 16 |
+
<DataArray type="Float64" Name="f_1[6]" format="appended" RangeMin="-2.1046" RangeMax="3.1697" offset="30960" />
|
| 17 |
+
<DataArray type="Float64" Name="f_1[7]" format="appended" RangeMin="0.14783" RangeMax="1.0385" offset="40192" />
|
| 18 |
+
<DataArray type="Float64" Name="f_1[8]" format="appended" RangeMin="270.33" RangeMax="777.75" offset="45408" />
|
| 19 |
+
<DataArray type="Float64" Name="f_1[9]" format="appended" RangeMin="0" RangeMax="0" offset="48852" />
|
| 20 |
+
<DataArray type="Float64" Name="f_1[10]" format="appended" RangeMin="0" RangeMax="0" offset="48920" />
|
| 21 |
+
</CellData>
|
| 22 |
+
<Points>
|
| 23 |
+
<DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="4.0092183641" RangeMax="7.0710678119" offset="48988" />
|
| 24 |
+
</Points>
|
| 25 |
+
<Cells>
|
| 26 |
+
<DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="53688" />
|
| 27 |
+
<DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="61684" />
|
| 28 |
+
<DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="63712" />
|
| 29 |
+
</Cells>
|
| 30 |
+
</Piece>
|
| 31 |
+
</UnstructuredGrid>
|
| 32 |
+
<AppendedData encoding="base64">
|
| 33 |
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AQAAAACAAABgIgAAnxIAAA==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AQAAAACAAABgIgAA2wUAAA==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AQAAAACAAABgIgAAsBsAAA==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AQAAAACAAABgIgAA+hoAAA==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AQAAAACAAABgIgAABQoAAA==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eJztwYEAAAAAw6D5U5/gBlUBAAAAAAAAAMA3ImAAAQ==AQAAAACAAABgIgAAHwAAAA==eJztwYEAAAAAw6D5U5/gBlUBAAAAAAAAAMA3ImAAAQ==AQAAAACAAADQOAAAsg0AAA==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AgAAAACAAACACQAAohUAALUBAAA=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AQAAAACAAABgIgAA3wUAAA==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eJzj5BwFo2AUjALKAQAyByat
|
| 34 |
+
</AppendedData>
|
| 35 |
+
</VTKFile>
|
CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/grid/Grid_300000.pvtu
ADDED
|
@@ -0,0 +1,29 @@
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
| 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/Kn0p36/simulation0787_Kn0p36Ma5p6/grid/Grid_3_300000.vtu
ADDED
|
@@ -0,0 +1,35 @@
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|
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|
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|
|
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|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 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="276" NumberOfCells="242" >
|
| 5 |
+
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IyWf1C22ODqx0k5qL03Vh/HZyZWmBHm4mH7TrrZcgarHO7i1qGkN6upLBTBZW/62IkfJ7tHa3tsJJye+fT3+wnY0E/wfTkRDcAQAAAACAAACQBwAAMAcAAA==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AQAAAACAAACQBwAAlQIAAA==eJxdlUtIVFEYxyWGkJhAxEqwgkykrKTswcgwcFOSXBjCmLUQieghuEioKMjXIoxUBDfee08oJC5cZKRoUQuRFhU4Aw0UBqmM9jAfM2UhYZtyzvmdOTF38+P/Pc73v9/ceycc2rgGbUu4G9ewbaUlrnHbCifiIThvW0cTVwyu2daVxJXuqL5tjurLd1S+2FF9ZeSD6Bp0Pfo2bKO/h/5eR50/QPwR+in9EXw8h8/wM4GehHPwO/e3Tt0Wzs3m3IPM9cNS8pVQ+75KfQN1d8h3cR8Ouh/9hL5b6Cz4mT2/wd9rGGHfUfQyXKfey9wdnJPHPB9zThGvxmcd+RvEG2Er7KTvAfX96CFXaa+brJfxvdT9ZJ8f4Xs4AxfgL/btwUcmc3Nhodm7rC/n/NqUPTfR30ZdN/k+4neFYpFQ5z7Gf4ar6juYdwx6OGeVvS7BuNm3rEvj/Ay4Gz+H0CdgCedWwTrqbjKnBX0f3yGhOCpU/p5Q+eNwDP87oeCcUvMcybq/7Pk3/v9AD3MyofZ9AO3jHIt4Rcr7eY26ZvQX/M7iN8yeR9l7O779xMd5bg6z/yHmBOEeuJW5m1PoZf526vYT9xEvgfr9rCV/CS7hcxHf32AUnxGzf6k7YABO4vsk+3/JuReh/l7sMs+1rM9B6+c73zznMh8gfwb/Neg4e1xh/iL6K/fxib1O4/st+gX5buKn6Z9h/9Wu0lP4vQ4DzM8zvqXOxU8B8SPQT76M/mXmxkTSv8zHmR8Tyd9B34dklPg79AS6h/OCeg+uYgO/wyq+Opl/Fj/6fS5A7zPvud63+g6JJGX+B3P+o/YvuWKeH/38q/8T+j/AV8Qfoi/Qvwm2m++onDNivsOy7zI8R/y8Y/0Dx0E9aQ==AQAAAACAAACQBwAAkgQAAA==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AQAAAACAAACQBwAAfwMAAA==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AQAAAACAAACQBwAAFwAAAA==eJxjYBgFo2AUjIJRMApGwUADAAeQAAE=AQAAAACAAACQBwAAFwAAAA==eJxjYBgFo2AUjIJRMApGwUADAAeQAAE=AQAAAACAAADwDAAArgIAAA==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AQAAAACAAABAHgAA1wQAAA==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AQAAAACAAADyAAAADAAAAA==eJzj5BxpAAAK4QiD
|
| 34 |
+
</AppendedData>
|
| 35 |
+
</VTKFile>
|
CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/grid/final-grid.dat
ADDED
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The diff for this file is too large to render.
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CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/log.sparta
ADDED
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@@ -0,0 +1,319 @@
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|
| 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 0.36
|
| 17 |
+
variable Ma equal 5.6
|
| 18 |
+
variable To equal 273.0
|
| 19 |
+
variable Tb equal 273.0
|
| 20 |
+
variable theta equal 0.0
|
| 21 |
+
variable mfp equal ${Kn}*${L}
|
| 22 |
+
variable mfp equal 0.36*${L}
|
| 23 |
+
variable mfp equal 0.36*1
|
| 24 |
+
variable cpmfp equal 4
|
| 25 |
+
variable nden equal 1.0/sqrt(2.0)/${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}*${Kn})
|
| 29 |
+
variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.36/${cpmfp}*${Kn})
|
| 30 |
+
variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.36/4*${Kn})
|
| 31 |
+
variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.36/4*0.36)
|
| 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 5.6*${sos}
|
| 38 |
+
variable vo equal 5.6*307.815564238681
|
| 39 |
+
variable vx equal ${vo}*cos(${theta}*2*PI/360)
|
| 40 |
+
variable vx equal 1723.76715973661*cos(${theta}*2*PI/360)
|
| 41 |
+
variable vx equal 1723.76715973661*cos(0*2*PI/360)
|
| 42 |
+
variable vy equal ${vo}*sin(${theta}*2*PI/360)
|
| 43 |
+
variable vy equal 1723.76715973661*sin(${theta}*2*PI/360)
|
| 44 |
+
variable vy equal 1723.76715973661*sin(0*2*PI/360)
|
| 45 |
+
variable ppc equal 30
|
| 46 |
+
variable xncells equal (${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)/0.36*${cpmfp}
|
| 50 |
+
variable xncells equal (6--5)/0.36*4
|
| 51 |
+
variable yncells equal (${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)/0.36*${cpmfp}
|
| 55 |
+
variable yncells equal (5--5)/0.36*4
|
| 56 |
+
variable Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
|
| 57 |
+
variable Fnum equal 3.99501127472736e+19*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
|
| 58 |
+
variable Fnum equal 3.99501127472736e+19*(6-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
|
| 59 |
+
variable Fnum equal 3.99501127472736e+19*(6--5)*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
|
| 60 |
+
variable Fnum equal 3.99501127472736e+19*(6--5)*(5-${ymin})/${ppc}/${xncells}/${yncells}
|
| 61 |
+
variable Fnum equal 3.99501127472736e+19*(6--5)*(5--5)/${ppc}/${xncells}/${yncells}
|
| 62 |
+
variable Fnum equal 3.99501127472736e+19*(6--5)*(5--5)/30/${xncells}/${yncells}
|
| 63 |
+
variable Fnum equal 3.99501127472736e+19*(6--5)*(5--5)/30/122.222222222222/${yncells}
|
| 64 |
+
variable Fnum equal 3.99501127472736e+19*(6--5)*(5--5)/30/122.222222222222/111.111111111111
|
| 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}/${xncells}/10/4
|
| 68 |
+
variable tstep equal (--5+6)/1723.76715973661/${xncells}/10/4
|
| 69 |
+
variable tstep equal (--5+6)/1723.76715973661/122.222222222222/10/4
|
| 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 3.99501127472736e+19
|
| 81 |
+
global fnum ${Fnum}
|
| 82 |
+
global fnum 1.07865304417639e+16
|
| 83 |
+
timestep ${tstep}
|
| 84 |
+
timestep 1.30528069715854e-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 122.222222222222 ${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 122.222222222222 111.111111111111 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 59673 child grid cells
|
| 100 |
+
CPU time = 0.12631 secs
|
| 101 |
+
create/ghost percent = 0.927893 99.0721
|
| 102 |
+
balance_grid rcb cell
|
| 103 |
+
Balance grid migrated 59557 cells
|
| 104 |
+
CPU time = 0.0868504 secs
|
| 105 |
+
reassign/sort/migrate/ghost percent = 61.4121 0.0326769 9.10183 29.4533
|
| 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 1723.76715973661 ${vy} 0.0 temp ${To}
|
| 110 |
+
mixture air Ar vstream 1723.76715973661 0 0.0 temp ${To}
|
| 111 |
+
mixture air Ar vstream 1723.76715973661 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 |
+
356 0 = cells overlapping surfs, overlap cells with unmarked corner pts
|
| 121 |
+
53305 6012 356 = cells outside/inside/overlapping surfs
|
| 122 |
+
356 = surf cells with 1,2,etc splits
|
| 123 |
+
109.215 109.215 = cell-wise and global flow volume
|
| 124 |
+
CPU time = 0.110544 secs
|
| 125 |
+
read/check/sort/surf2grid/ghost/inout/particle percent = 32.1369 20.4796 3.2139 21.1141 23.0554 5.72911 0.128426
|
| 126 |
+
surf2grid time = 0.0233404 secs
|
| 127 |
+
map/comm1/comm2/comm3/comm4/split percent = 14.4423 25.0079 4.17563 1.87231 11.7293 6.70125
|
| 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 1317 cells
|
| 133 |
+
CPU time = 0.0368603 secs
|
| 134 |
+
reassign/sort/migrate/ghost percent = 12.168 0.0767763 24.0217 63.7335
|
| 135 |
+
create_particles air n 0
|
| 136 |
+
WARNING: Created unexpected # of particles: 404497 versus 404499 (../create_particles.cpp:346)
|
| 137 |
+
Created 404497 particles
|
| 138 |
+
CPU time = 0.0128946 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) = 1.59521 0 1.6875
|
| 144 |
+
grid (ave,min,max) = 3.07385 1.51379 5.26379
|
| 145 |
+
surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
|
| 146 |
+
total (ave,min,max) = 4.68967 3.22189 6.97189
|
| 147 |
+
Step CPU Np Natt Ncoll Nscoll Npave Nscollave
|
| 148 |
+
0 0 404497 0 0 0 0 0
|
| 149 |
+
10000 10.50125 451488 5863 5136 16 427810.72 15.5875
|
| 150 |
+
20000 22.584876 452160 5964 5209 17 440383.12 15.68445
|
| 151 |
+
30000 34.380161 452917 5826 5132 15 444484.28 15.695433
|
| 152 |
+
40000 48.292268 453688 5879 5162 13 446708.98 15.73845
|
| 153 |
+
50000 60.292831 452759 5833 5115 17 448002.13 15.7548
|
| 154 |
+
60000 72.447338 452682 5981 5243 27 448782.75 15.7586
|
| 155 |
+
70000 84.353978 453248 5874 5235 20 449386.82 15.761143
|
| 156 |
+
80000 96.002077 453411 5964 5233 14 449832.16 15.770775
|
| 157 |
+
90000 109.41216 453158 5881 5166 19 450235.48 15.787189
|
| 158 |
+
100000 121.9543 453132 5876 5166 18 450552.04 15.79768
|
| 159 |
+
110000 134.12583 453524 6023 5283 10 450820.45 15.803736
|
| 160 |
+
120000 146.25301 453590 5961 5214 23 451068.3 15.801533
|
| 161 |
+
130000 159.03997 452563 5794 5098 15 451197.73 15.806962
|
| 162 |
+
140000 171.37651 453571 5883 5201 19 451348.31 15.806979
|
| 163 |
+
150000 183.82197 452591 5927 5201 21 451470.37 15.815427
|
| 164 |
+
160000 197.4691 453525 5983 5246 16 451580.66 15.823281
|
| 165 |
+
170000 209.62294 453072 5977 5295 17 451666.21 15.825653
|
| 166 |
+
180000 222.05551 453009 6011 5282 15 451741.1 15.824894
|
| 167 |
+
190000 235.29392 453043 5779 5061 11 451802.45 15.826911
|
| 168 |
+
200000 247.57521 453607 5940 5182 22 451881.02 15.829175
|
| 169 |
+
Loop time of 247.576 on 128 procs for 200000 steps with 453607 particles
|
| 170 |
+
|
| 171 |
+
MPI task timing breakdown:
|
| 172 |
+
Section | min time | avg time | max time |%varavg| %total
|
| 173 |
+
---------------------------------------------------------------
|
| 174 |
+
Move | 0.022118 | 11.13 | 72.009 | 434.7 | 4.50
|
| 175 |
+
Coll | 0.30502 | 8.9291 | 74.494 | 406.9 | 3.61
|
| 176 |
+
Sort | 0.10425 | 1.8498 | 12.553 | 180.9 | 0.75
|
| 177 |
+
Comm | 55.704 | 88.63 | 99.21 | 91.5 | 35.80
|
| 178 |
+
Modify | 0.018227 | 0.11027 | 2.1531 | 95.3 | 0.04
|
| 179 |
+
Output | 0.0038717 | 0.0086809 | 0.009974 | 1.0 | 0.00
|
| 180 |
+
Other | | 136.9 | | | 55.30
|
| 181 |
+
|
| 182 |
+
Particle moves = 90376203483 (90.4B)
|
| 183 |
+
Cells touched = 94409108578 (94.4B)
|
| 184 |
+
Particle comms = 193857737 (194M)
|
| 185 |
+
Boundary collides = 0 (0K)
|
| 186 |
+
Boundary exits = 18639566 (18.6M)
|
| 187 |
+
SurfColl checks = 201159653 (201M)
|
| 188 |
+
SurfColl occurs = 3165835 (3.17M)
|
| 189 |
+
Surf reactions = 0 (0K)
|
| 190 |
+
Collide attempts = 1373974645 (1.37B)
|
| 191 |
+
Collide occurs = 1078679656 (1.08B)
|
| 192 |
+
Reactions = 0 (0K)
|
| 193 |
+
Particles stuck = 0
|
| 194 |
+
Axisymm bad moves = 0
|
| 195 |
+
|
| 196 |
+
Particle-moves/CPUsec/proc: 2.85191e+06
|
| 197 |
+
Particle-moves/step: 451881
|
| 198 |
+
Cell-touches/particle/step: 1.04462
|
| 199 |
+
Particle comm iterations/step: 1
|
| 200 |
+
Particle fraction communicated: 0.00214501
|
| 201 |
+
Particle fraction colliding with boundary: 0
|
| 202 |
+
Particle fraction exiting boundary: 0.000206244
|
| 203 |
+
Surface-checks/particle/step: 0.0022258
|
| 204 |
+
Surface-collisions/particle/step: 3.50295e-05
|
| 205 |
+
Surf-reactions/particle/step: 0
|
| 206 |
+
Collision-attempts/particle/step: 0.0152028
|
| 207 |
+
Collisions/particle/step: 0.0119354
|
| 208 |
+
Reactions/particle/step: 0
|
| 209 |
+
|
| 210 |
+
Particles: 3543.8 ave 24895 max 0 min
|
| 211 |
+
Histogram: 84 16 6 10 2 6 0 2 0 2
|
| 212 |
+
Cells: 466.195 ave 467 max 465 min
|
| 213 |
+
Histogram: 2 0 0 0 0 99 0 0 0 27
|
| 214 |
+
GhostCell: 12074.5 ave 22142 max 674 min
|
| 215 |
+
Histogram: 18 12 12 10 17 3 6 4 16 30
|
| 216 |
+
EmptyCell: 0 ave 0 max 0 min
|
| 217 |
+
Histogram: 128 0 0 0 0 0 0 0 0 0
|
| 218 |
+
Surfs: 200 ave 200 max 200 min
|
| 219 |
+
Histogram: 128 0 0 0 0 0 0 0 0 0
|
| 220 |
+
GhostSurf: 0 ave 0 max 0 min
|
| 221 |
+
Histogram: 128 0 0 0 0 0 0 0 0 0
|
| 222 |
+
compute 1 grid all air n nrho massrho u v w
|
| 223 |
+
compute 2 grid all air trot
|
| 224 |
+
compute 3 tvib/grid all air
|
| 225 |
+
compute 4 thermal/grid all air press temp
|
| 226 |
+
fix 1 ave/grid all 1 ${nave} ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
|
| 227 |
+
fix 1 ave/grid all 1 10000 ${nave} c_1[*] c_4[*] c_2[*] c_3[*] ave running
|
| 228 |
+
fix 1 ave/grid all 1 10000 10000 c_1[*] c_4[*] c_2[*] c_3[*] ave running
|
| 229 |
+
dump 1 grid all ${noutput} output/grid.*.dat id xc yc f_1[*]
|
| 230 |
+
dump 1 grid all 300000 output/grid.*.dat id xc yc f_1[*]
|
| 231 |
+
dump_modify 1 format float %12.5g
|
| 232 |
+
compute 5 surf all air n press px py shx shy fx fy etot erot evib
|
| 233 |
+
fix 2 ave/surf all 1 ${nave} ${nave} c_5[*] ave running
|
| 234 |
+
fix 2 ave/surf all 1 10000 ${nave} c_5[*] ave running
|
| 235 |
+
fix 2 ave/surf all 1 10000 10000 c_5[*] ave running
|
| 236 |
+
dump 2 surf all ${noutput} output/surf.*.dat id v1x v1y v2x v2y f_2[*]
|
| 237 |
+
dump 2 surf all 300000 output/surf.*.dat id v1x v1y v2x v2y f_2[*]
|
| 238 |
+
dump_modify 2 format float %12.5g
|
| 239 |
+
compute 6 lambda/grid f_1[2] f_1[8] Ar kx
|
| 240 |
+
dump 3 grid all ${noutput} output/lambdakn.*.dat id xc yc c_6[*]
|
| 241 |
+
dump 3 grid all 300000 output/lambdakn.*.dat id xc yc c_6[*]
|
| 242 |
+
dump_modify 3 format float %12.5g
|
| 243 |
+
run 100000
|
| 244 |
+
Memory usage per proc in Mbytes:
|
| 245 |
+
particles (ave,min,max) = 1.6875 0 3.375
|
| 246 |
+
grid (ave,min,max) = 3.07385 1.51379 5.26379
|
| 247 |
+
surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
|
| 248 |
+
total (ave,min,max) = 4.93871 3.37849 7.129
|
| 249 |
+
Step CPU Np Natt Ncoll Nscoll Npave Nscollave
|
| 250 |
+
200000 0 453607 5940 5182 0 0 0
|
| 251 |
+
210000 22.231697 452692 5959 5196 12 452720.73 15.904
|
| 252 |
+
220000 45.539215 452964 5841 5088 19 452874.11 15.8944
|
| 253 |
+
230000 68.086105 452929 5907 5250 16 452942.45 15.868933
|
| 254 |
+
240000 91.003486 452962 5892 5181 18 453001.57 15.871425
|
| 255 |
+
250000 113.8093 453385 5844 5143 24 452911.39 15.86468
|
| 256 |
+
260000 136.1009 453410 5864 5139 20 452945.06 15.872283
|
| 257 |
+
270000 158.3668 453029 5774 5114 7 452971.87 15.874957
|
| 258 |
+
280000 181.74383 453528 5931 5209 17 453066.43 15.896638
|
| 259 |
+
290000 203.55888 453578 6001 5257 16 453155.02 15.891633
|
| 260 |
+
300000 226.8626 453245 5935 5181 24 453172.82 15.89254
|
| 261 |
+
Loop time of 226.863 on 128 procs for 100000 steps with 453245 particles
|
| 262 |
+
|
| 263 |
+
MPI task timing breakdown:
|
| 264 |
+
Section | min time | avg time | max time |%varavg| %total
|
| 265 |
+
---------------------------------------------------------------
|
| 266 |
+
Move | 0.011439 | 5.6104 | 36.297 | 307.9 | 2.47
|
| 267 |
+
Coll | 0.15332 | 4.4956 | 38.107 | 290.2 | 1.98
|
| 268 |
+
Sort | 0.058432 | 0.93666 | 6.3738 | 127.8 | 0.41
|
| 269 |
+
Comm | 32.579 | 49.268 | 54.944 | 61.8 | 21.72
|
| 270 |
+
Modify | 2.1702 | 15.446 | 94.285 | 475.3 | 6.81
|
| 271 |
+
Output | 0.036442 | 0.037927 | 0.041894 | 0.6 | 0.02
|
| 272 |
+
Other | | 151.1 | | | 66.59
|
| 273 |
+
|
| 274 |
+
Particle moves = 45317282074 (45.3B)
|
| 275 |
+
Cells touched = 47338267340 (47.3B)
|
| 276 |
+
Particle comms = 97118076 (97.1M)
|
| 277 |
+
Boundary collides = 0 (0K)
|
| 278 |
+
Boundary exits = 9343955 (9.34M)
|
| 279 |
+
SurfColl checks = 101142879 (101M)
|
| 280 |
+
SurfColl occurs = 1589254 (1.59M)
|
| 281 |
+
Surf reactions = 0 (0K)
|
| 282 |
+
Collide attempts = 692916293 (693M)
|
| 283 |
+
Collide occurs = 543919555 (544M)
|
| 284 |
+
Reactions = 0 (0K)
|
| 285 |
+
Particles stuck = 0
|
| 286 |
+
Axisymm bad moves = 0
|
| 287 |
+
|
| 288 |
+
Particle-moves/CPUsec/proc: 1.5606e+06
|
| 289 |
+
Particle-moves/step: 453173
|
| 290 |
+
Cell-touches/particle/step: 1.0446
|
| 291 |
+
Particle comm iterations/step: 1
|
| 292 |
+
Particle fraction communicated: 0.00214307
|
| 293 |
+
Particle fraction colliding with boundary: 0
|
| 294 |
+
Particle fraction exiting boundary: 0.00020619
|
| 295 |
+
Surface-checks/particle/step: 0.00223188
|
| 296 |
+
Surface-collisions/particle/step: 3.50695e-05
|
| 297 |
+
Surf-reactions/particle/step: 0
|
| 298 |
+
Collision-attempts/particle/step: 0.0152903
|
| 299 |
+
Collisions/particle/step: 0.0120025
|
| 300 |
+
Reactions/particle/step: 0
|
| 301 |
+
|
| 302 |
+
Particles: 3540.98 ave 24696 max 0 min
|
| 303 |
+
Histogram: 84 16 6 10 2 6 0 1 1 2
|
| 304 |
+
Cells: 466.195 ave 467 max 465 min
|
| 305 |
+
Histogram: 2 0 0 0 0 99 0 0 0 27
|
| 306 |
+
GhostCell: 12074.5 ave 22142 max 674 min
|
| 307 |
+
Histogram: 18 12 12 10 17 3 6 4 16 30
|
| 308 |
+
EmptyCell: 0 ave 0 max 0 min
|
| 309 |
+
Histogram: 128 0 0 0 0 0 0 0 0 0
|
| 310 |
+
Surfs: 200 ave 200 max 200 min
|
| 311 |
+
Histogram: 128 0 0 0 0 0 0 0 0 0
|
| 312 |
+
GhostSurf: 0 ave 0 max 0 min
|
| 313 |
+
Histogram: 128 0 0 0 0 0 0 0 0 0
|
| 314 |
+
write_grid grid/final-grid.dat
|
| 315 |
+
grid cells = 59673
|
| 316 |
+
CPU time = 0.00888779 secs
|
| 317 |
+
write_surf surf/geom.surf
|
| 318 |
+
surf elements = 200
|
| 319 |
+
CPU time = 0.00177362 secs
|
CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/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/Kn0p36/simulation0787_Kn0p36Ma5p6/output/grid.300000.dat
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/output/lambdakn.300000.dat
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/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 0.00192 0.049875 -0.049869 0.0007834 4.362e-05 0.0027767 -0.00078262 5.592e-05 14.611 0 0
|
| 11 |
+
129 -0.31871 0.38526 -0.30645 0.39508 0.12666 3.5215 2.2018 -2.7483 0.59442 0.47622 0.043921 -0.035689 1030 0 0
|
| 12 |
+
2 0.49975 -0.015705 0.49901 -0.031395 0.00181 0.046208 -0.046157 0.0021767 8.0534e-05 0.0017077 -0.00072373 6.1014e-05 10.066 0 0
|
| 13 |
+
130 -0.30645 0.39508 -0.29389 0.40451 0.12215 3.3703 2.0236 -2.6952 0.58559 0.43968 0.040984 -0.035428 980.63 0 0
|
| 14 |
+
3 0.49901 -0.031395 0.49778 -0.047054 0.00212 0.051513 -0.051354 0.0040416 0.0004649 0.0059071 -0.00079933 0.00015627 12.66 0 0
|
| 15 |
+
131 -0.29389 0.40451 -0.28104 0.41354 0.11634 3.2142 1.8482 -2.6297 0.61407 0.43157 0.038675 -0.034526 956.38 0 0
|
| 16 |
+
4 0.49778 -0.047054 0.49606 -0.062667 0.00184 0.047149 -0.046864 0.0051738 0.00046405 0.0042033 -0.00072882 0.00014729 13.725 0 0
|
| 17 |
+
132 -0.28104 0.41354 -0.26791 0.42216 0.11045 3.0809 1.6915 -2.5751 0.63191 0.41508 0.036495 -0.033928 942.09 0 0
|
| 18 |
+
5 0.49606 -0.062667 0.49384 -0.078217 0.00188 0.048826 -0.048339 0.0068797 4.8306e-05 0.00033942 -0.00075852 0.00011339 12.443 0 0
|
| 19 |
+
133 -0.26791 0.42216 -0.25452 0.43037 0.10269 2.8655 1.4972 -2.4433 0.60176 0.36876 0.03297 -0.032585 881.75 0 0
|
| 20 |
+
6 0.49384 -0.078217 0.49114 -0.093691 0.00201 0.049817 -0.049075 0.0085649 -0.00054087 -0.0030991 -0.00077933 8.5854e-05 12.304 0 0
|
| 21 |
+
134 -0.25452 0.43037 -0.24088 0.43815 0.09813 2.7073 1.3414 -2.3517 0.6227 0.35518 0.03085 -0.031359 834.52 0 0
|
| 22 |
+
7 0.49114 -0.093691 0.48796 -0.10907 0.00227 0.057482 -0.056287 0.011657 6.4309e-05 0.00031054 -0.00088311 0.00018797 15.2 0 0
|
| 23 |
+
135 -0.24088 0.43815 -0.227 0.4455 0.09433 2.6323 1.2317 -2.3263 0.60208 0.31878 0.028804 -0.031533 824.25 0 0
|
| 24 |
+
8 0.48796 -0.10907 0.48429 -0.12434 0.00176 0.043697 -0.04249 0.010201 0.0012841 0.0053488 -0.00064723 0.00024425 9.7283 0 0
|
| 25 |
+
136 -0.227 0.4455 -0.21289 0.45241 0.08791 2.4345 1.071 -2.1863 0.59132 0.28969 0.026111 -0.02979 761.43 0 0
|
| 26 |
+
9 0.48429 -0.12434 0.48015 -0.1395 0.00178 0.044236 -0.042668 0.011673 0.0012835 0.0046918 -0.00065004 0.00025704 10.51 0 0
|
| 27 |
+
137 -0.21289 0.45241 -0.19857 0.45888 0.08163 2.2703 0.93428 -2.0692 0.60654 0.27386 0.024202 -0.0282 705.65 0 0
|
| 28 |
+
10 0.48015 -0.1395 0.47553 -0.15451 0.00182 0.04595 -0.043919 0.013511 0.0022081 0.0071776 -0.00065516 0.00032496 12.23 0 0
|
| 29 |
+
138 -0.19857 0.45888 -0.18406 0.46489 0.07829 2.1889 0.83767 -2.0223 0.63249 0.26198 0.023092 -0.02765 694.51 0 0
|
| 30 |
+
11 0.47553 -0.15451 0.47044 -0.16937 0.00182 0.042334 -0.040051 0.013713 0.0020329 0.0059377 -0.00059717 0.00030865 10.346 0 0
|
| 31 |
+
139 -0.18406 0.46489 -0.16937 0.47044 0.07202 1.9971 0.70591 -1.8681 0.57986 0.21911 0.020196 -0.025902 641.52 0 0
|
| 32 |
+
12 0.47044 -0.16937 0.46489 -0.18406 0.00178 0.041856 -0.039154 0.014795 0.00278 0.0073572 -0.00057134 0.00034795 11.191 0 0
|
| 33 |
+
140 -0.16937 0.47044 -0.15451 0.47553 0.06926 1.9131 0.61968 -1.8099 0.59383 0.20331 0.019061 -0.025236 608.99 0 0
|
| 34 |
+
13 0.46489 -0.18406 0.45888 -0.19857 0.00193 0.042991 -0.039719 0.016452 0.0051853 0.012518 -0.00054243 0.00045505 10.356 0 0
|
| 35 |
+
141 -0.15451 0.47553 -0.1395 0.48015 0.06413 1.7647 0.51889 -1.6867 0.55529 0.17083 0.016872 -0.02381 558.29 0 0
|
| 36 |
+
14 0.45888 -0.19857 0.45241 -0.21289 0.00207 0.047076 -0.042906 0.019373 0.0052749 0.011683 -0.00059108 0.0004878 12.956 0 0
|
| 37 |
+
142 -0.1395 0.48015 -0.12434 0.48429 0.05979 1.6334 0.431 -1.5755 0.53983 0.14768 0.015249 -0.022427 528.14 0 0
|
| 38 |
+
15 0.45241 -0.21289 0.4455 -0.227 0.00155 0.036379 -0.032669 0.016004 0.0055697 0.011369 -0.00042566 0.00042996 10.88 0 0
|
| 39 |
+
143 -0.12434 0.48429 -0.10907 0.48796 0.05725 1.5596 0.36408 -1.5165 0.55256 0.13266 0.014398 -0.021736 507.13 0 0
|
| 40 |
+
16 0.4455 -0.227 0.43815 -0.24088 0.00182 0.039253 -0.03469 0.018368 0.0065309 0.012335 -0.00044231 0.00048225 11.929 0 0
|
| 41 |
+
144 -0.10907 0.48796 -0.093691 0.49114 0.05228 1.4311 0.29021 -1.4014 0.52696 0.10913 0.012835 -0.020298 467.52 0 0
|
| 42 |
+
17 0.43815 -0.24088 0.43037 -0.25452 0.0018 0.040028 -0.03477 0.019832 0.0067968 0.011916 -0.00043938 0.00049868 13.457 0 0
|
| 43 |
+
145 -0.093691 0.49114 -0.078217 0.49384 0.04813 1.3205 0.22703 -1.3008 0.4916 0.085798 0.011288 -0.019085 443.55 0 0
|
| 44 |
+
18 0.43037 -0.25452 0.42216 -0.26791 0.00183 0.041723 -0.035575 0.0218 0.012486 0.020375 -0.00036266 0.00066247 12.978 0 0
|
| 45 |
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146 -0.078217 0.49384 -0.062667 0.49606 0.04547 1.2365 0.17423 -1.2242 0.48341 0.068799 0.01033 -0.018148 409.36 0 0
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| 46 |
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19 0.42216 -0.26791 0.41354 -0.28104 0.00191 0.043046 -0.035978 0.023633 0.012 0.018268 -0.00037663 0.00065816 13.617 0 0
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| 47 |
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147 -0.062667 0.49606 -0.047054 0.49778 0.04285 1.1422 0.12534 -1.1354 0.47939 0.052925 0.0094988 -0.017002 386.9 0 0
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| 48 |
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| 49 |
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148 -0.047054 0.49778 -0.031395 0.49901 0.03805 1.0222 0.080199 -1.019 0.44219 0.034801 0.0082053 -0.01546 354.54 0 0
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21 0.40451 -0.29389 0.39508 -0.30645 0.00229 0.049151 -0.039305 0.029511 0.017899 0.023839 -0.00033624 0.000838 18.001 0 0
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| 51 |
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149 -0.031395 0.49901 -0.015705 0.49975 0.03626 0.97619 0.045985 -0.97511 0.43883 0.020695 0.0076152 -0.014991 339.14 0 0
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| 52 |
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22 0.39508 -0.30645 0.38526 -0.31871 0.00242 0.053604 -0.041834 0.033516 0.019469 0.024301 -0.0003513 0.00090815 19.008 0 0
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| 53 |
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150 -0.015705 0.49975 0 0.5 0.03299 0.89635 0.014079 -0.89624 0.41741 0.0065573 0.0067776 -0.013975 313.05 0 0
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23 0.38526 -0.31871 0.37506 -0.33066 0.00266 0.061777 -0.046976 0.040121 0.024253 0.028397 -0.00035691 0.0010762 23.807 0 0
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| 55 |
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151 0 0.5 0.015705 0.49975 0.03064 0.81291 -0.012769 -0.81281 0.39481 -0.0062022 0.0060009 -0.012864 293.35 0 0
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| 56 |
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24 0.37506 -0.33066 0.36448 -0.34227 0.00256 0.056618 -0.041877 0.038105 0.026345 0.028952 -0.00024397 0.0010533 22.218 0 0
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| 57 |
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152 0.015705 0.49975 0.031395 0.49901 0.02837 0.7555 -0.035589 -0.75467 0.37762 -0.017808 0.0053725 -0.012133 274.75 0 0
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| 58 |
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| 59 |
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153 0.031395 0.49901 0.047054 0.49778 0.0254 0.67963 -0.053323 -0.67753 0.34065 -0.02681 0.0045132 -0.011063 252.89 0 0
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| 60 |
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26 0.35355 -0.35355 0.34227 -0.36448 0.00316 0.072913 -0.050741 0.052361 0.039442 0.038222 -0.00017748 0.0014228 27.76 0 0
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154 0.047054 0.49778 0.062667 0.49606 0.02392 0.6284 -0.068957 -0.6246 0.32658 -0.036055 0.0040466 -0.010377 221.53 0 0
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| 62 |
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27 0.34227 -0.36448 0.33066 -0.37506 0.00362 0.082915 -0.055803 0.061327 0.044791 0.040757 -0.00017297 0.0016035 34.052 0 0
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| 63 |
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155 0.062667 0.49606 0.078217 0.49384 0.02148 0.56039 -0.078959 -0.5548 0.30747 -0.043759 0.0035893 -0.0094017 213.03 0 0
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| 65 |
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156 0.078217 0.49384 0.093691 0.49114 0.02001 0.53033 -0.091179 -0.52243 0.2958 -0.051625 0.003214 -0.0090169 205.32 0 0
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| 66 |
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29 0.31871 -0.38526 0.30645 -0.39508 0.00402 0.093443 -0.058424 0.072926 0.060258 0.048276 2.8799e-05 0.0019037 41.002 0 0
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157 0.093691 0.49114 0.10907 0.48796 0.01824 0.46789 -0.094883 -0.45817 0.26335 -0.054538 0.0026462 -0.0080533 179.35 0 0
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| 69 |
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158 0.10907 0.48796 0.12434 0.48429 0.01723 0.45118 -0.10533 -0.43871 0.26379 -0.063331 0.0024891 -0.0078858 180.17 0 0
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| 70 |
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| 71 |
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159 0.12434 0.48429 0.1395 0.48015 0.01493 0.38156 -0.10068 -0.36804 0.23161 -0.063362 0.0020565 -0.0067761 149.11 0 0
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| 72 |
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32 0.28104 -0.41354 0.26791 -0.42216 0.00548 0.13552 -0.074404 0.11327 0.089358 0.058697 0.00023489 0.0027011 57.551 0 0
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| 73 |
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| 74 |
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33 0.26791 -0.42216 0.25452 -0.43037 0.00606 0.14427 -0.075381 0.12301 0.088642 0.05432 0.00020829 0.0027854 53.923 0 0
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| 75 |
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161 0.15451 0.47553 0.16937 0.47044 0.01321 0.33759 -0.10935 -0.31939 0.20711 -0.070911 0.0015356 -0.0061305 134.42 0 0
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| 76 |
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34 0.25452 -0.43037 0.24088 -0.43815 0.00663 0.15809 -0.078325 0.13732 0.11262 0.064236 0.00053865 0.0031659 72.147 0 0
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| 77 |
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162 0.16937 0.47044 0.18406 0.46489 0.0108 0.27628 -0.097658 -0.25844 0.16775 -0.063386 0.0011009 -0.0050551 105.98 0 0
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| 78 |
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35 0.24088 -0.43815 0.227 -0.4455 0.00738 0.17781 -0.083203 0.15714 0.11611 0.061476 0.00051686 0.0034339 75.611 0 0
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| 79 |
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163 0.18406 0.46489 0.19857 0.45888 0.01091 0.26952 -0.10314 -0.24901 0.16396 -0.067916 0.00095536 -0.004978 106.78 0 0
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| 80 |
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36 0.227 -0.4455 0.21289 -0.45241 0.00869 0.21565 -0.094872 0.19366 0.13382 0.065557 0.00061176 0.0040716 83.636 0 0
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| 81 |
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164 0.19857 0.45888 0.21289 0.45241 0.00882 0.22006 -0.09056 -0.20057 0.14198 -0.064106 0.00080765 -0.0041573 90.44 0 0
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| 82 |
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37 0.21289 -0.45241 0.19857 -0.45888 0.00938 0.23481 -0.09663 0.21401 0.14666 0.06622 0.00078586 0.0044017 92.846 0 0
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| 83 |
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165 0.21289 0.45241 0.227 0.4455 0.00862 0.20996 -0.092369 -0.18855 0.13812 -0.067662 0.00071856 -0.0040244 87.313 0 0
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| 84 |
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38 0.19857 -0.45888 0.18406 -0.46489 0.01059 0.26882 -0.10287 0.24835 0.15556 0.064437 0.00082766 0.0049131 98.06 0 0
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| 85 |
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166 0.227 0.4455 0.24088 0.43815 0.00749 0.18847 -0.088192 -0.16657 0.12323 -0.065245 0.0005503 -0.0036411 80.809 0 0
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| 86 |
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39 0.18406 -0.46489 0.16937 -0.47044 0.01139 0.28855 -0.102 0.26992 0.17361 0.065601 0.0011248 0.0052702 115.7 0 0
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| 87 |
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167 0.24088 0.43815 0.25452 0.43037 0.00703 0.17115 -0.084798 -0.14867 0.11204 -0.063907 0.00042793 -0.003339 73.736 0 0
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| 88 |
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40 0.16937 -0.47044 0.15451 -0.47553 0.01281 0.32166 -0.10419 0.30432 0.19731 0.067554 0.0014626 0.0058411 123.4 0 0
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| 89 |
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168 0.25452 0.43037 0.26791 0.42216 0.00647 0.15424 -0.08059 -0.13151 0.10125 -0.062049 0.00032458 -0.0030403 69.002 0 0
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| 90 |
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41 0.15451 -0.47553 0.1395 -0.48015 0.01375 0.35916 -0.10561 0.34328 0.20904 0.064309 0.0016247 0.0064022 137.25 0 0
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| 91 |
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169 0.26791 0.42216 0.28104 0.41354 0.00596 0.13957 -0.07663 -0.11666 0.088004 -0.057808 0.00017867 -0.0027404 58.868 0 0
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| 92 |
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42 0.1395 -0.48015 0.12434 -0.48429 0.01494 0.3873 -0.1022 0.37357 0.23438 0.06412 0.0020763 0.006875 148.5 0 0
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| 93 |
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170 0.28104 0.41354 0.29389 0.40451 0.00515 0.12077 -0.069441 -0.098805 0.078576 -0.055224 0.00014348 -0.0024194 51.491 0 0
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| 94 |
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43 0.12434 -0.48429 0.10907 -0.48796 0.01723 0.44424 -0.10371 0.43197 0.25472 0.061152 0.0023719 0.0077456 175.03 0 0
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| 95 |
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| 96 |
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44 0.10907 -0.48796 0.093691 -0.49114 0.01902 0.49153 -0.099676 0.48132 0.28922 0.059895 0.0029772 0.008501 194.4 0 0
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| 97 |
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45 0.093691 -0.49114 0.078217 -0.49384 0.01978 0.52235 -0.089807 0.51457 0.27556 0.048093 0.0029177 0.0088379 194.71 0 0
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| 99 |
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| 100 |
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46 0.078217 -0.49384 0.062667 -0.49606 0.0227 0.59236 -0.083464 0.58645 0.3207 0.045642 0.0037263 0.0099285 227.55 0 0
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| 101 |
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|
| 102 |
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47 0.062667 -0.49606 0.047054 -0.49778 0.02336 0.61999 -0.068034 0.61625 0.31631 0.034921 0.0038997 0.010228 220.84 0 0
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| 103 |
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175 0.34227 0.36448 0.35355 0.35355 0.00314 0.071374 -0.04967 -0.051255 0.036011 -0.034897 -0.00021455 -0.0013532 26.986 0 0
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| 104 |
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48 0.047054 -0.49778 0.031395 -0.49901 0.02638 0.70484 -0.055301 0.70267 0.35922 0.028271 0.0047738 0.011481 260.26 0 0
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| 105 |
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| 106 |
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49 0.031395 -0.49901 0.015705 -0.49975 0.02736 0.73601 -0.034671 0.73519 0.34866 0.016442 0.0049319 0.011806 264.24 0 0
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| 107 |
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177 0.36448 0.34227 0.37506 0.33066 0.00284 0.064672 -0.047833 -0.043525 0.030189 -0.033177 -0.00027715 -0.0012048 23.802 0 0
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| 108 |
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50 0.015705 -0.49975 0 -0.5 0.0317 0.84578 -0.013285 0.84567 0.4037 0.0063419 0.0061324 0.013383 293.43 0 0
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| 109 |
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| 110 |
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51 0 -0.5 -0.015705 -0.49975 0.03329 0.8854 0.013907 0.88529 0.40383 -0.0063438 0.0065615 0.013806 307.55 0 0
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| 111 |
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179 0.38526 0.31871 0.39508 0.30645 0.00205 0.044448 -0.034689 -0.027791 0.017649 -0.022029 -0.00026766 -0.00078254 16.239 0 0
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| 112 |
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52 -0.015705 -0.49975 -0.031395 -0.49901 0.03561 0.97982 0.046156 0.97873 0.42235 -0.019918 0.007359 0.01506 348.43 0 0
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| 113 |
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| 114 |
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53 -0.031395 -0.49901 -0.047054 -0.49778 0.0395 1.0673 0.083739 1.064 0.4624 -0.036391 0.0085783 0.016141 362.18 0 0
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| 115 |
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181 0.40451 0.29389 0.41354 0.28104 0.00216 0.047446 -0.038818 -0.027282 0.013996 -0.019914 -0.00038989 -0.00074133 15.285 0 0
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| 116 |
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54 -0.047054 -0.49778 -0.062667 -0.49606 0.04134 1.1189 0.12278 1.1121 0.46028 -0.050816 0.0091584 0.016671 377.27 0 0
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| 117 |
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| 118 |
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55 -0.062667 -0.49606 -0.078217 -0.49384 0.04438 1.2097 0.17045 1.1976 0.46577 -0.066289 0.0099933 0.01777 412.49 0 0
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| 119 |
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183 0.42216 0.26791 0.43037 0.25452 0.00177 0.042436 -0.036183 -0.022173 0.011052 -0.018035 -0.00039474 -0.00063155 15.571 0 0
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| 120 |
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56 -0.078217 -0.49384 -0.093691 -0.49114 0.04794 1.3088 0.22501 1.2893 0.49655 -0.086662 0.011334 0.01889 436.42 0 0
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| 121 |
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| 122 |
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57 -0.093691 -0.49114 -0.10907 -0.48796 0.0511 1.4056 0.28504 1.3764 0.50155 -0.10387 0.012355 0.019988 468.51 0 0
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| 123 |
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| 124 |
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58 -0.10907 -0.48796 -0.12434 -0.48429 0.05604 1.5229 0.35552 1.4809 0.5322 -0.12777 0.013944 0.021253 493.3 0 0
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| 125 |
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| 126 |
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59 -0.12434 -0.48429 -0.1395 -0.48015 0.05812 1.6098 0.42477 1.5527 0.5487 -0.15011 0.015291 0.022031 524.81 0 0
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| 127 |
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| 128 |
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| 129 |
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| 130 |
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| 131 |
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| 132 |
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63 -0.18406 -0.46489 -0.19857 -0.45888 0.07702 2.1325 0.81608 1.9702 0.60842 -0.25202 0.022375 0.026988 688.99 0 0
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| 135 |
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| 137 |
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| 138 |
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| 139 |
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| 140 |
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66 -0.227 -0.4455 -0.24088 -0.43815 0.09195 2.5379 1.1876 2.2429 0.62004 -0.32829 0.028393 0.030074 791.61 0 0
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| 141 |
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| 142 |
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67 -0.24088 -0.43815 -0.25452 -0.43037 0.0976 2.7174 1.3464 2.3604 0.64109 -0.36567 0.031218 0.031332 852.42 0 0
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| 143 |
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| 144 |
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| 145 |
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196 0.49384 0.078217 0.49606 0.062667 0.002 0.050857 -0.050349 -0.0071658 -0.00010728 0.00075382 -0.00079254 -0.00010071 11.206 0 0
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| 146 |
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69 -0.26791 -0.42216 -0.28104 -0.41354 0.11011 3.0783 1.6901 2.5729 0.60264 -0.39586 0.036013 0.034196 932.84 0 0
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| 147 |
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197 0.49606 0.062667 0.49778 0.047054 0.00211 0.052825 -0.052506 -0.0057968 0.00045983 -0.0041651 -0.00081751 -0.00015647 13.277 0 0
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| 148 |
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70 -0.28104 -0.41354 -0.29389 -0.40451 0.11741 3.2741 1.8826 2.6787 0.61137 -0.42968 0.039174 0.035326 975.91 0 0
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| 149 |
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198 0.49778 0.047054 0.49901 0.031395 0.00211 0.051789 -0.051629 -0.0040633 -5.8745e-05 0.00074642 -0.00081188 -5.21e-05 12.832 0 0
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| 150 |
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71 -0.29389 -0.40451 -0.30645 -0.39508 0.12232 3.3993 2.041 2.7184 0.59331 -0.44547 0.041378 0.035701 1014.4 0 0
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| 151 |
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199 0.49901 0.031395 0.49975 0.015705 0.002 0.050215 -0.050159 -0.0023654 -5.1462e-05 0.0010913 -0.00078867 -2.0014e-05 12.518 0 0
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| 152 |
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72 -0.30645 -0.39508 -0.31871 -0.38526 0.12943 3.5969 2.2489 2.8071 0.56505 -0.45269 0.0442 0.036982 1044.6 0 0
|
| 153 |
+
200 0.49975 0.015705 0.5 0 0.00221 0.056147 -0.05614 -0.00088192 6.0221e-05 -0.0038335 -0.00088087 -7.4066e-05 12.701 0 0
|
| 154 |
+
73 -0.31871 -0.38526 -0.33066 -0.37506 0.13591 3.7645 2.4448 2.8625 0.57279 -0.48921 0.047399 0.037278 1091.6 0 0
|
| 155 |
+
74 -0.33066 -0.37506 -0.34227 -0.36448 0.14097 3.9293 2.6445 2.9062 0.58194 -0.52952 0.050678 0.037332 1183 0 0
|
| 156 |
+
75 -0.34227 -0.36448 -0.35355 -0.35355 0.14927 4.1725 2.9037 2.9964 0.56539 -0.54791 0.054491 0.038459 1222.5 0 0
|
| 157 |
+
76 -0.35355 -0.35355 -0.36448 -0.34227 0.15455 4.305 3.0915 2.9959 0.51928 -0.53585 0.056716 0.038641 1258.8 0 0
|
| 158 |
+
77 -0.36448 -0.34227 -0.37506 -0.33066 0.16128 4.4958 3.3253 3.0257 0.49871 -0.54808 0.060064 0.038918 1297.9 0 0
|
| 159 |
+
78 -0.37506 -0.33066 -0.38526 -0.31871 0.16887 4.7013 3.5749 3.0533 0.50693 -0.59354 0.064115 0.038636 1353.5 0 0
|
| 160 |
+
79 -0.38526 -0.31871 -0.39508 -0.30645 0.17369 4.8036 3.7489 3.0034 0.47431 -0.59204 0.066335 0.037876 1379.9 0 0
|
| 161 |
+
80 -0.39508 -0.30645 -0.40451 -0.29389 0.18371 5.1323 4.1043 3.0816 0.45457 -0.60543 0.071607 0.038893 1473.9 0 0
|
| 162 |
+
81 -0.40451 -0.29389 -0.41354 -0.28104 0.18677 5.1866 4.2434 2.9823 0.40232 -0.57244 0.072972 0.037853 1471.7 0 0
|
| 163 |
+
82 -0.41354 -0.28104 -0.42216 -0.26791 0.1937 5.4052 4.5177 2.9676 0.36478 -0.55533 0.076691 0.03789 1516 0 0
|
| 164 |
+
83 -0.42216 -0.26791 -0.43037 -0.25452 0.19966 5.5348 4.7192 2.8919 0.36376 -0.5936 0.07984 0.036101 1547.7 0 0
|
| 165 |
+
84 -0.43037 -0.25452 -0.43815 -0.24088 0.20611 5.7388 4.9849 2.8433 0.33514 -0.58757 0.083564 0.035432 1601.1 0 0
|
| 166 |
+
85 -0.43815 -0.24088 -0.4455 -0.227 0.21478 5.9741 5.2797 2.7954 0.29987 -0.56637 0.08764 0.035013 1647.3 0 0
|
| 167 |
+
86 -0.4455 -0.227 -0.45241 -0.21289 0.21628 6.036 5.4205 2.6555 0.25877 -0.52821 0.089206 0.033414 1693.5 0 0
|
| 168 |
+
87 -0.45241 -0.21289 -0.45888 -0.19857 0.22235 6.1657 5.6194 2.5373 0.23163 -0.513 0.091905 0.031796 1711.2 0 0
|
| 169 |
+
88 -0.45888 -0.19857 -0.46489 -0.18406 0.23023 6.3957 5.9089 2.4475 0.21374 -0.51602 0.09617 0.030339 1781.4 0 0
|
| 170 |
+
89 -0.46489 -0.18406 -0.47044 -0.16937 0.23476 6.524 6.1029 2.3061 0.16984 -0.44947 0.098527 0.029162 1802 0 0
|
| 171 |
+
90 -0.47044 -0.16937 -0.47553 -0.15451 0.23678 6.5583 6.2047 2.1243 0.14021 -0.40953 0.099662 0.026935 1816.8 0 0
|
| 172 |
+
91 -0.47553 -0.15451 -0.48015 -0.1395 0.24664 6.8286 6.5268 2.0079 0.12731 -0.41383 0.10452 0.025039 1900.5 0 0
|
| 173 |
+
92 -0.48015 -0.1395 -0.48429 -0.12434 0.24242 6.8638 6.6205 1.8112 0.10569 -0.38632 0.10565 0.022381 1987.3 0 0
|
| 174 |
+
93 -0.48429 -0.12434 -0.48796 -0.10907 0.25179 7.0086 6.815 1.6361 0.073734 -0.30713 0.1082 0.020875 1944.8 0 0
|
| 175 |
+
94 -0.48796 -0.10907 -0.49114 -0.093691 0.25242 7.0184 6.8725 1.4232 0.054679 -0.26404 0.10881 0.018208 1914.6 0 0
|
| 176 |
+
95 -0.49114 -0.093691 -0.49384 -0.078217 0.2507 7.0504 6.9454 1.2122 0.042155 -0.24153 0.10976 0.015246 2013.3 0 0
|
| 177 |
+
96 -0.49384 -0.078217 -0.49606 -0.062667 0.25663 7.1308 7.0597 1.0047 0.035039 -0.2462 0.11144 0.011915 1964.4 0 0
|
| 178 |
+
97 -0.49606 -0.062667 -0.49778 -0.047054 0.25909 7.2271 7.1834 0.79306 0.021444 -0.19424 0.11317 0.0094058 2000.1 0 0
|
| 179 |
+
98 -0.49778 -0.047054 -0.49901 -0.031395 0.25944 7.2195 7.1973 0.56644 0.0077994 -0.099101 0.11317 0.0073406 1992.6 0 0
|
| 180 |
+
99 -0.49901 -0.031395 -0.49975 -0.015705 0.26171 7.2896 7.2815 0.34339 0.0023536 -0.049909 0.11441 0.0046098 1981.2 0 0
|
| 181 |
+
100 -0.49975 -0.015705 -0.5 0 0.26238 7.2891 7.2882 0.11449 5.2744e-05 -0.0033575 0.11448 0.0017456 2014.1 0 0
|
| 182 |
+
101 -0.5 0 -0.49975 0.015705 0.25868 7.2033 7.2025 -0.11315 -0.00021583 -0.013739 0.11313 -0.001993 1969.1 0 0
|
| 183 |
+
102 -0.49975 0.015705 -0.49901 0.031395 0.25974 7.1821 7.1741 -0.33832 0.0033579 0.071205 0.11274 -0.0041957 1947.4 0 0
|
| 184 |
+
103 -0.49901 0.031395 -0.49778 0.047054 0.26099 7.2434 7.2211 -0.56831 0.010942 0.13903 0.1136 -0.0067428 2019.7 0 0
|
| 185 |
+
104 -0.49778 0.047054 -0.49606 0.062667 0.26069 7.2545 7.2106 -0.79606 0.017867 0.16183 0.11354 -0.009962 2012.6 0 0
|
| 186 |
+
105 -0.49606 0.062667 -0.49384 0.078217 0.25738 7.1586 7.0872 -1.0087 0.035317 0.24815 0.11187 -0.011945 1991 0 0
|
| 187 |
+
106 -0.49384 0.078217 -0.49114 0.093691 0.25139 7.0649 6.9597 -1.2147 0.05813 0.33307 0.11023 -0.013847 2031 0 0
|
| 188 |
+
107 -0.49114 0.093691 -0.48796 0.10907 0.25287 7.0285 6.8824 -1.4253 0.058876 0.2843 0.10903 -0.017922 1939.4 0 0
|
| 189 |
+
108 -0.48796 0.10907 -0.48429 0.12434 0.24947 6.9071 6.7163 -1.6124 0.089241 0.37171 0.1069 -0.019488 1877.2 0 0
|
| 190 |
+
109 -0.48429 0.12434 -0.48015 0.1395 0.24464 6.8135 6.572 -1.7979 0.10579 0.3867 0.10489 -0.022166 1881.8 0 0
|
| 191 |
+
110 -0.48015 0.1395 -0.47553 0.15451 0.24125 6.6704 6.3756 -1.9614 0.11508 0.37407 0.10195 -0.024932 1819.6 0 0
|
| 192 |
+
111 -0.47553 0.15451 -0.47044 0.16937 0.23826 6.6377 6.2799 -2.1501 0.15279 0.44626 0.10104 -0.026762 1851.8 0 0
|
| 193 |
+
112 -0.47044 0.16937 -0.46489 0.18406 0.23085 6.4131 5.9991 -2.2669 0.17542 0.46423 0.096985 -0.028315 1774.3 0 0
|
| 194 |
+
113 -0.46489 0.18406 -0.45888 0.19857 0.22806 6.322 5.8408 -2.4193 0.21942 0.52973 0.095189 -0.02968 1753.4 0 0
|
| 195 |
+
114 -0.45888 0.19857 -0.45241 0.21289 0.22459 6.2382 5.6855 -2.5671 0.22277 0.49337 0.092803 -0.032573 1743.4 0 0
|
| 196 |
+
115 -0.45241 0.21289 -0.4455 0.227 0.21639 6.0409 5.4249 -2.6576 0.26008 0.5309 0.089296 -0.033405 1693.3 0 0
|
| 197 |
+
116 -0.4455 0.227 -0.43815 0.24088 0.21357 5.9196 5.2315 -2.77 0.3045 0.5751 0.086956 -0.034475 1694.3 0 0
|
| 198 |
+
117 -0.43815 0.24088 -0.43037 0.25452 0.20508 5.7111 4.9608 -2.8296 0.32469 0.56924 0.083021 -0.035504 1605.9 0 0
|
| 199 |
+
118 -0.43037 0.25452 -0.42216 0.26791 0.19896 5.559 4.7398 -2.9046 0.33179 0.54143 0.079661 -0.037118 1590.1 0 0
|
| 200 |
+
119 -0.42216 0.26791 -0.41354 0.28104 0.19433 5.4013 4.5145 -2.9654 0.39253 0.59757 0.077076 -0.037193 1532.5 0 0
|
| 201 |
+
120 -0.41354 0.28104 -0.40451 0.29389 0.18775 5.2258 4.2755 -3.0048 0.40398 0.5748 0.073501 -0.038169 1486.8 0 0
|
| 202 |
+
121 -0.40451 0.29389 -0.39508 0.30645 0.18396 5.1491 4.1177 -3.0917 0.45286 0.60315 0.071791 -0.039088 1494.9 0 0
|
| 203 |
+
122 -0.39508 0.30645 -0.38526 0.31871 0.17405 4.8475 3.7832 -3.0309 0.45773 0.57134 0.066613 -0.038633 1390.8 0 0
|
| 204 |
+
123 -0.38526 0.31871 -0.37506 0.33066 0.16671 4.6439 3.5313 -3.016 0.4821 0.56446 0.063039 -0.038507 1314.8 0 0
|
| 205 |
+
124 -0.37506 0.33066 -0.36448 0.34227 0.16063 4.4808 3.3141 -3.0156 0.53098 0.58354 0.060396 -0.038202 1298.1 0 0
|
| 206 |
+
125 -0.36448 0.34227 -0.35355 0.35355 0.15401 4.2979 3.0864 -2.991 0.52161 0.53826 0.056673 -0.038525 1250.3 0 0
|
| 207 |
+
126 -0.35355 0.35355 -0.34227 0.36448 0.14537 4.0823 2.841 -2.9316 0.54198 0.52521 0.053137 -0.037798 1199.1 0 0
|
| 208 |
+
127 -0.34227 0.36448 -0.33066 0.37506 0.13921 3.8825 2.613 -2.8716 0.55358 0.50372 0.049738 -0.037194 1139.2 0 0
|
| 209 |
+
128 -0.33066 0.37506 -0.31871 0.38526 0.13646 3.8031 2.4699 -2.8919 0.56662 0.48394 0.047695 -0.037822 1108.4 0 0
|
CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/runmpirun128.sh
ADDED
|
@@ -0,0 +1,18 @@
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|
| 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/Kn0p36/simulation0787_Kn0p36Ma5p6/runmpirun64.sh
ADDED
|
@@ -0,0 +1,18 @@
|
|
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|
|
|
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|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
| 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/Kn0p36/simulation0787_Kn0p36Ma5p6/slurm-28429925.out
ADDED
|
@@ -0,0 +1,205 @@
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|
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|
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|
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|
|
|
|
|
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|
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|
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|
|
| 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 59673 child grid cells
|
| 6 |
+
CPU time = 0.12631 secs
|
| 7 |
+
create/ghost percent = 0.927893 99.0721
|
| 8 |
+
Balance grid migrated 59557 cells
|
| 9 |
+
CPU time = 0.0868504 secs
|
| 10 |
+
reassign/sort/migrate/ghost percent = 61.4121 0.0326769 9.10183 29.4533
|
| 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 |
+
356 0 = cells overlapping surfs, overlap cells with unmarked corner pts
|
| 18 |
+
53305 6012 356 = cells outside/inside/overlapping surfs
|
| 19 |
+
356 = surf cells with 1,2,etc splits
|
| 20 |
+
109.214731023047 109.214731023047 = cell-wise and global flow volume
|
| 21 |
+
CPU time = 0.110544 secs
|
| 22 |
+
read/check/sort/surf2grid/ghost/inout/particle percent = 32.1369 20.4796 3.2139 21.1141 23.0554 5.72911 0.128426
|
| 23 |
+
surf2grid time = 0.0233404 secs
|
| 24 |
+
map/comm1/comm2/comm3/comm4/split percent = 14.4423 25.0079 4.17563 1.87231 11.7293 6.70125
|
| 25 |
+
Balance grid migrated 1317 cells
|
| 26 |
+
CPU time = 0.0368603 secs
|
| 27 |
+
reassign/sort/migrate/ghost percent = 12.168 0.0767763 24.0217 63.7335
|
| 28 |
+
Creating particles ...
|
| 29 |
+
WARNING: Created unexpected # of particles: 404497 versus 404499 (../create_particles.cpp:346)
|
| 30 |
+
Created 404497 particles
|
| 31 |
+
CPU time = 0.0128946 secs
|
| 32 |
+
Memory usage per proc in Mbytes:
|
| 33 |
+
particles (ave,min,max) = 1.59521 0 1.6875
|
| 34 |
+
grid (ave,min,max) = 3.07385 1.51379 5.26379
|
| 35 |
+
surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
|
| 36 |
+
total (ave,min,max) = 4.68967 3.22189 6.97189
|
| 37 |
+
Step CPU Np Natt Ncoll Nscoll Npave Nscollave
|
| 38 |
+
0 0 404497 0 0 0 0 0
|
| 39 |
+
10000 10.50125 451488 5863 5136 16 427810.72 15.5875
|
| 40 |
+
20000 22.584876 452160 5964 5209 17 440383.12 15.68445
|
| 41 |
+
30000 34.380161 452917 5826 5132 15 444484.28 15.695433
|
| 42 |
+
40000 48.292268 453688 5879 5162 13 446708.98 15.73845
|
| 43 |
+
50000 60.292831 452759 5833 5115 17 448002.13 15.7548
|
| 44 |
+
60000 72.447338 452682 5981 5243 27 448782.75 15.7586
|
| 45 |
+
70000 84.353978 453248 5874 5235 20 449386.82 15.761143
|
| 46 |
+
80000 96.002077 453411 5964 5233 14 449832.16 15.770775
|
| 47 |
+
90000 109.41216 453158 5881 5166 19 450235.48 15.787189
|
| 48 |
+
100000 121.9543 453132 5876 5166 18 450552.04 15.79768
|
| 49 |
+
110000 134.12583 453524 6023 5283 10 450820.45 15.803736
|
| 50 |
+
120000 146.25301 453590 5961 5214 23 451068.3 15.801533
|
| 51 |
+
130000 159.03997 452563 5794 5098 15 451197.73 15.806962
|
| 52 |
+
140000 171.37651 453571 5883 5201 19 451348.31 15.806979
|
| 53 |
+
150000 183.82197 452591 5927 5201 21 451470.37 15.815427
|
| 54 |
+
160000 197.4691 453525 5983 5246 16 451580.66 15.823281
|
| 55 |
+
170000 209.62294 453072 5977 5295 17 451666.21 15.825653
|
| 56 |
+
180000 222.05551 453009 6011 5282 15 451741.1 15.824894
|
| 57 |
+
190000 235.29392 453043 5779 5061 11 451802.45 15.826911
|
| 58 |
+
200000 247.57521 453607 5940 5182 22 451881.02 15.829175
|
| 59 |
+
Loop time of 247.576 on 128 procs for 200000 steps with 453607 particles
|
| 60 |
+
|
| 61 |
+
MPI task timing breakdown:
|
| 62 |
+
Section | min time | avg time | max time |%varavg| %total
|
| 63 |
+
---------------------------------------------------------------
|
| 64 |
+
Move | 0.022118 | 11.13 | 72.009 | 434.7 | 4.50
|
| 65 |
+
Coll | 0.30502 | 8.9291 | 74.494 | 406.9 | 3.61
|
| 66 |
+
Sort | 0.10425 | 1.8498 | 12.553 | 180.9 | 0.75
|
| 67 |
+
Comm | 55.704 | 88.63 | 99.21 | 91.5 | 35.80
|
| 68 |
+
Modify | 0.018227 | 0.11027 | 2.1531 | 95.3 | 0.04
|
| 69 |
+
Output | 0.0038717 | 0.0086809 | 0.009974 | 1.0 | 0.00
|
| 70 |
+
Other | | 136.9 | | | 55.30
|
| 71 |
+
|
| 72 |
+
Particle moves = 90376203483 (90.4B)
|
| 73 |
+
Cells touched = 94409108578 (94.4B)
|
| 74 |
+
Particle comms = 193857737 (194M)
|
| 75 |
+
Boundary collides = 0 (0K)
|
| 76 |
+
Boundary exits = 18639566 (18.6M)
|
| 77 |
+
SurfColl checks = 201159653 (201M)
|
| 78 |
+
SurfColl occurs = 3165835 (3.17M)
|
| 79 |
+
Surf reactions = 0 (0K)
|
| 80 |
+
Collide attempts = 1373974645 (1.37B)
|
| 81 |
+
Collide occurs = 1078679656 (1.08B)
|
| 82 |
+
Gas reactions = 0 (0K)
|
| 83 |
+
Particles stuck = 0
|
| 84 |
+
Axisymm bad moves = 0
|
| 85 |
+
|
| 86 |
+
Particle-moves/CPUsec/proc: 2.85191e+06
|
| 87 |
+
Particle-moves/step: 451881
|
| 88 |
+
Cell-touches/particle/step: 1.04462
|
| 89 |
+
Particle comm iterations/step: 1
|
| 90 |
+
Particle fraction communicated: 0.00214501
|
| 91 |
+
Particle fraction colliding with boundary: 0
|
| 92 |
+
Particle fraction exiting boundary: 0.000206244
|
| 93 |
+
Surface-checks/particle/step: 0.0022258
|
| 94 |
+
Surface-collisions/particle/step: 3.50295e-05
|
| 95 |
+
Surface-reactions/particle/step: 0
|
| 96 |
+
Collision-attempts/particle/step: 0.0152028
|
| 97 |
+
Collisions/particle/step: 0.0119354
|
| 98 |
+
Gas-reactions/particle/step: 0
|
| 99 |
+
|
| 100 |
+
Particles: 3543.8 ave 24895 max 0 min
|
| 101 |
+
Histogram: 84 16 6 10 2 6 0 2 0 2
|
| 102 |
+
Cells: 466.195 ave 467 max 465 min
|
| 103 |
+
Histogram: 2 0 0 0 0 99 0 0 0 27
|
| 104 |
+
GhostCell: 12074.5 ave 22142 max 674 min
|
| 105 |
+
Histogram: 18 12 12 10 17 3 6 4 16 30
|
| 106 |
+
EmptyCell: 0 ave 0 max 0 min
|
| 107 |
+
Histogram: 128 0 0 0 0 0 0 0 0 0
|
| 108 |
+
Surfs: 200 ave 200 max 200 min
|
| 109 |
+
Histogram: 128 0 0 0 0 0 0 0 0 0
|
| 110 |
+
GhostSurf: 0 ave 0 max 0 min
|
| 111 |
+
Histogram: 128 0 0 0 0 0 0 0 0 0
|
| 112 |
+
Memory usage per proc in Mbytes:
|
| 113 |
+
particles (ave,min,max) = 1.6875 0 3.375
|
| 114 |
+
grid (ave,min,max) = 3.07385 1.51379 5.26379
|
| 115 |
+
surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
|
| 116 |
+
total (ave,min,max) = 4.93871 3.37849 7.129
|
| 117 |
+
Step CPU Np Natt Ncoll Nscoll Npave Nscollave
|
| 118 |
+
200000 0 453607 5940 5182 0 0 0
|
| 119 |
+
210000 22.231697 452692 5959 5196 12 452720.73 15.904
|
| 120 |
+
220000 45.539215 452964 5841 5088 19 452874.11 15.8944
|
| 121 |
+
230000 68.086105 452929 5907 5250 16 452942.45 15.868933
|
| 122 |
+
240000 91.003486 452962 5892 5181 18 453001.57 15.871425
|
| 123 |
+
250000 113.8093 453385 5844 5143 24 452911.39 15.86468
|
| 124 |
+
260000 136.1009 453410 5864 5139 20 452945.06 15.872283
|
| 125 |
+
270000 158.3668 453029 5774 5114 7 452971.87 15.874957
|
| 126 |
+
280000 181.74383 453528 5931 5209 17 453066.43 15.896638
|
| 127 |
+
290000 203.55888 453578 6001 5257 16 453155.02 15.891633
|
| 128 |
+
300000 226.8626 453245 5935 5181 24 453172.82 15.89254
|
| 129 |
+
Loop time of 226.863 on 128 procs for 100000 steps with 453245 particles
|
| 130 |
+
|
| 131 |
+
MPI task timing breakdown:
|
| 132 |
+
Section | min time | avg time | max time |%varavg| %total
|
| 133 |
+
---------------------------------------------------------------
|
| 134 |
+
Move | 0.011439 | 5.6104 | 36.297 | 307.9 | 2.47
|
| 135 |
+
Coll | 0.15332 | 4.4956 | 38.107 | 290.2 | 1.98
|
| 136 |
+
Sort | 0.058432 | 0.93666 | 6.3738 | 127.8 | 0.41
|
| 137 |
+
Comm | 32.579 | 49.268 | 54.944 | 61.8 | 21.72
|
| 138 |
+
Modify | 2.1702 | 15.446 | 94.285 | 475.3 | 6.81
|
| 139 |
+
Output | 0.036442 | 0.037927 | 0.041894 | 0.6 | 0.02
|
| 140 |
+
Other | | 151.1 | | | 66.59
|
| 141 |
+
|
| 142 |
+
Particle moves = 45317282074 (45.3B)
|
| 143 |
+
Cells touched = 47338267340 (47.3B)
|
| 144 |
+
Particle comms = 97118076 (97.1M)
|
| 145 |
+
Boundary collides = 0 (0K)
|
| 146 |
+
Boundary exits = 9343955 (9.34M)
|
| 147 |
+
SurfColl checks = 101142879 (101M)
|
| 148 |
+
SurfColl occurs = 1589254 (1.59M)
|
| 149 |
+
Surf reactions = 0 (0K)
|
| 150 |
+
Collide attempts = 692916293 (693M)
|
| 151 |
+
Collide occurs = 543919555 (544M)
|
| 152 |
+
Gas reactions = 0 (0K)
|
| 153 |
+
Particles stuck = 0
|
| 154 |
+
Axisymm bad moves = 0
|
| 155 |
+
|
| 156 |
+
Particle-moves/CPUsec/proc: 1.5606e+06
|
| 157 |
+
Particle-moves/step: 453173
|
| 158 |
+
Cell-touches/particle/step: 1.0446
|
| 159 |
+
Particle comm iterations/step: 1
|
| 160 |
+
Particle fraction communicated: 0.00214307
|
| 161 |
+
Particle fraction colliding with boundary: 0
|
| 162 |
+
Particle fraction exiting boundary: 0.00020619
|
| 163 |
+
Surface-checks/particle/step: 0.00223188
|
| 164 |
+
Surface-collisions/particle/step: 3.50695e-05
|
| 165 |
+
Surface-reactions/particle/step: 0
|
| 166 |
+
Collision-attempts/particle/step: 0.0152903
|
| 167 |
+
Collisions/particle/step: 0.0120025
|
| 168 |
+
Gas-reactions/particle/step: 0
|
| 169 |
+
|
| 170 |
+
Particles: 3540.98 ave 24696 max 0 min
|
| 171 |
+
Histogram: 84 16 6 10 2 6 0 1 1 2
|
| 172 |
+
Cells: 466.195 ave 467 max 465 min
|
| 173 |
+
Histogram: 2 0 0 0 0 99 0 0 0 27
|
| 174 |
+
GhostCell: 12074.5 ave 22142 max 674 min
|
| 175 |
+
Histogram: 18 12 12 10 17 3 6 4 16 30
|
| 176 |
+
EmptyCell: 0 ave 0 max 0 min
|
| 177 |
+
Histogram: 128 0 0 0 0 0 0 0 0 0
|
| 178 |
+
Surfs: 200 ave 200 max 200 min
|
| 179 |
+
Histogram: 128 0 0 0 0 0 0 0 0 0
|
| 180 |
+
GhostSurf: 0 ave 0 max 0 min
|
| 181 |
+
Histogram: 128 0 0 0 0 0 0 0 0 0
|
| 182 |
+
Writing grid file ...
|
| 183 |
+
grid cells = 59673
|
| 184 |
+
CPU time = 0.00888779 secs
|
| 185 |
+
Writing surface file ...
|
| 186 |
+
surf elements = 200
|
| 187 |
+
CPU time = 0.00177362 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 0:00:09 (wall clock time)
|
| 195 |
+
|
| 196 |
+
Processing 4 grid chunk(s).
|
| 197 |
+
Completed grid chunk number: 3
|
| 198 |
+
Completed grid chunk number: 2
|
| 199 |
+
Completed grid chunk number: 1
|
| 200 |
+
Completed grid chunk number: 0
|
| 201 |
+
|
| 202 |
+
Done in 0:00:09 (wall clock time)
|
| 203 |
+
|
| 204 |
+
Processing SPARTA surface information.
|
| 205 |
+
Processing dump result file: ['./output/surf.300000.dat']
|
CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/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="0.00155" RangeMax="0.26238" offset="4512" />
|
| 14 |
+
<DataArray type="Float64" Name="f_2[2]" format="appended" RangeMin="0.036379" RangeMax="7.2896" offset="6452" />
|
| 15 |
+
<DataArray type="Float64" Name="f_2[3]" format="appended" RangeMin="-0.10935" RangeMax="7.2882" offset="8480" />
|
| 16 |
+
<DataArray type="Float64" Name="f_2[4]" format="appended" RangeMin="-3.0917" RangeMax="3.0816" offset="10572" />
|
| 17 |
+
<DataArray type="Float64" Name="f_2[5]" format="appended" RangeMin="-0.00054087" RangeMax="0.64109" offset="12628" />
|
| 18 |
+
<DataArray type="Float64" Name="f_2[6]" format="appended" RangeMin="-0.60543" RangeMax="0.60315" offset="14708" />
|
| 19 |
+
<DataArray type="Float64" Name="f_2[7]" format="appended" RangeMin="-0.00088311" RangeMax="0.11448" offset="16844" />
|
| 20 |
+
<DataArray type="Float64" Name="f_2[8]" format="appended" RangeMin="-0.039088" RangeMax="0.038918" offset="18980" />
|
| 21 |
+
<DataArray type="Float64" Name="f_2[9]" format="appended" RangeMin="9.0251" RangeMax="2031" offset="21116" />
|
| 22 |
+
<DataArray type="Float64" Name="f_2[10]" format="appended" RangeMin="0" RangeMax="0" offset="22476" />
|
| 23 |
+
<DataArray type="Float64" Name="f_2[11]" format="appended" RangeMin="0" RangeMax="0" offset="22528" />
|
| 24 |
+
</CellData>
|
| 25 |
+
<Points>
|
| 26 |
+
<DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="0.49999998503" RangeMax="0.50000001255" offset="22580" />
|
| 27 |
+
</Points>
|
| 28 |
+
<Cells>
|
| 29 |
+
<DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="23908" />
|
| 30 |
+
<DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="24812" />
|
| 31 |
+
<DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="25304" />
|
| 32 |
+
</Cells>
|
| 33 |
+
</Piece>
|
| 34 |
+
</UnstructuredGrid>
|
| 35 |
+
<AppendedData encoding="base64">
|
| 36 |
+
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AQAAAACAAABABgAA3wUAAA==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AQAAAACAAABABgAA8wUAAA==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AQAAAACAAABABgAABAYAAA==eJwtVGk0FAoYrSdFtqiJXpSthaR0XuUVcytFlhZFkvSyVBNSyRI9nMhWEmNptdaQlkHLZERDmbENRjOjsU2zWEKhxCuhR6ef37n3u+c7373f5zicVZMsnI2v+fTUK5oEPK0uty0JIiIgRUgOOknEanFMVNR+eSgwlC8so29l+OoT1j9rm4emuN2iHnlHaMslZnvMcUSas0F+8UJ3jLpHiuzyjmJkOFeXwDoOM83iI8bmAcgu5K/RvR0A/9TkkS2cQHwPTl+yrDwEtQUhi0ebL+APG4ur28hxGAvzKvVPjsUOK7/vKr0x0NkSnaDlQIZigX4wdTAZBg32VlX8GxiQy5NdM3YLyzsjM+ofZMLjwuoPZSb3MH5qT6JgIBfSDX+Wu2jnw1uJMqrbSsW25Eqy339FiOvXcDqsWYT6hpwgQxEN3+yVfpgX0bBAVzTvAa8UO9TK4t3pZZgMZUXJ6FSAxOGggvkaXK+d7R69bxCmoWPWasoC0zyN6L+1BpXLqtLfVtSiStX7s8GMBiSzSFqOuzj44XTgVkrEW2iEyp5k5TRBMPTVxjmah25/ZzsfIg+BPrMkARPNcNRwkfPb24yRKdS0uQXK62qqnQUt8GS72lbPaQO/x2vV6PUOrF1TTtwU0IHE3a7fjRo7oKLwPDe46j2KxL2pTxRFv/liLFnotWs4QYyj1X0HGq3FmOSd711uIsG+FVlxhWIJDE9bma4+L0X+rjvtg3ulCDvNzZzYKcWxKkvtI++k2DMtH9mJS54z5xcHdOKFK4nKncKnmpqcEqXoO8/ecmxcguhD3FLpAgkImwqKbB0k6AqLydmSKQE9drDykboE1CFj9c/pInDmKjp39L3H7WveFkzTqfr2ZQcNF+FvXgeqn2e732G0wFLu2oaEg++gPNwlK7B6h70buuYO+vGx2O7NkKoJF1rddQqF1zjIErnvUMqtR6P3RzW+Sx0+lLKM7cuYuGxmXXL8SwUaF0wPVA4zSuRIuPJLRJy+RdwseoL+/Qk1ksmHINXRFzilUnDIetWr7KFsbNaqDvEaSYVfU2uYxZdwHLfsPNpm5QGmjOtc4zwFfO8npirZGDGqFnbwZ0d4Y/ynqdtrUjQMu56rldiSEeIw/l6VkAOhGV9n45vHMBTLl03qU5HnEhgbLqBhymyqEuElbH8ZXoakL8lemQlvcHdzbLqBPwtquxWOfCWw4c2z+Kskko3WydTU5RQOCv1ISZ/+5YJO4ScWV/GgN1y9VNGMj3MlRss3LG3BMzOVgYbWFvTf94q4/6Mdy0IWMf1sO8B56jxCbxViVmJrZc2ECPkxJP85RSKsqpCc6XYSI2NO0IlPNDEmdq3cXq4jwSVuhHqorBS6D13MV5RJoHp1QDswVwpe6Ix9t007cWXPzLUZW6UolOmJX/lJim/eTyzNt0uhN6+gX/2jBAYfRskskhSHLupMKXRC+5eREiy2esTMmyFFVNC002IY1/okWluKIROqu4dMFaP3Vs3GtnYRMh8+FvwT+B4JbL3wtUNCHJTMPLafKgSSVli/s2uHrVmWTy2hHS/DKnwFtFZEX4s1SNreggsmKfM/GQpADD54f309HxFMMbugm4dDalm5aY+5kJG/vNRj4O3vfXAwUVF+blDMQdRNWvgxSj1ozeryp/6u+32ntbCkDU/wzjMxrXpvvBLTaT9u9Bo96wPj+h5XQL9Zsn9GPAPdU+nMo5bio33xkqh+OsjsPi3fGBouak8/qmeIuEJYfyO6CLIMJZMjww9gWLNJ05XyECntbvNv0u9DSL2eK3cmBzbcLNKS8hyMvagL6+jNQM8pn8B7YxkIDt7klKJGRteLD575Iwl4+XbdvsH8eMz++jpdQe8qDp896+CbE42Pqir14p+RyLL0PlC1+SLcZKliwckQqHfvHot39Eee482GYTtPrHrh7JZJOYr0vKEDdi7uKHFkBWzL8MDZBukV+3UO0INRF4v45VW0YX7TU79toFJ8mywWKeLufJrrmaWajBPt7MYHukSkD6XxMtjKjGrh4jbNH3MZQUPSejpZBf8D0lIjaQ==AQAAAACAAABABgAAMAYAAA==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AQAAAACAAABABgAAMAYAAA==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AQAAAACAAABABgAAFQAAAA==eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAABABgAAFQAAAA==eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAADAEgAA0gMAAA==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AQAAAACAAABABgAAXwEAAA==eJwtxVFEHAAAANBKkpzkJEmSJMlJkiRJkiRJkiQnSXKSJEmSJEmSJEmSZGYmmUmSJEmSJEkyMzOTzCRJkmT20Xs/LybqXazjHO8EB5zoJAed7BSnOs3pznCms5ztHOc6zyHnu8CFLnKxS1zqMpe7wpWucrVrXOs617v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|
| 37 |
+
</AppendedData>
|
| 38 |
+
</VTKFile>
|
CylinderKnMa/Kn0p36/simulation0787_Kn0p36Ma5p6/surf/geom.surf
ADDED
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| 1 |
+
# Surface element file written by SPARTA
|
| 2 |
+
|
| 3 |
+
400 points
|
| 4 |
+
200 lines
|
| 5 |
+
|
| 6 |
+
Points
|
| 7 |
+
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| 8 |
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/jfcPOfNiBA==AQAAAACAAADARAAAhQIAAA==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AQAAAACAAADARAAAdAsAAA==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|
| 26 |
+
</AppendedData>
|
| 27 |
+
</VTKFile>
|
CylinderKnMa/Kn0p36/simulation0788_Kn0p36Ma5p7/Lambda/Lambda_2_300000.vtu
ADDED
|
@@ -0,0 +1,27 @@
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|
| 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="1212" NumberOfCells="1100" >
|
| 5 |
+
<PointData>
|
| 6 |
+
</PointData>
|
| 7 |
+
<CellData>
|
| 8 |
+
<DataArray type="Float64" Name="id" format="appended" RangeMin="12201" RangeMax="13520" offset="0" />
|
| 9 |
+
<DataArray type="Float64" Name="xc" format="appended" RangeMin="-4.9549" RangeMax="3.9713" offset="1968" />
|
| 10 |
+
<DataArray type="Float64" Name="yc" format="appended" RangeMin="4.0541" RangeMax="4.955" offset="3060" />
|
| 11 |
+
<DataArray type="Float64" Name="c_6[1]" format="appended" RangeMin="0.01894" RangeMax="0.033181" offset="3292" />
|
| 12 |
+
<DataArray type="Float64" Name="c_6[2]" format="appended" RangeMin="0.21007" RangeMax="0.368" offset="9348" />
|
| 13 |
+
</CellData>
|
| 14 |
+
<Points>
|
| 15 |
+
<DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="4.0092183641" RangeMax="7.0710678119" offset="15316" />
|
| 16 |
+
</Points>
|
| 17 |
+
<Cells>
|
| 18 |
+
<DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="20016" />
|
| 19 |
+
<DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="28012" />
|
| 20 |
+
<DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="30040" />
|
| 21 |
+
</Cells>
|
| 22 |
+
</Piece>
|
| 23 |
+
</UnstructuredGrid>
|
| 24 |
+
<AppendedData encoding="base64">
|
| 25 |
+
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DfcSzknqe1B3iCf3BwfoDHEUhozrg8hCKW8WNOu0Lfssr4C/yeK5jpufbUI5f+OV+ioOZkT+PyAesi/hCfPZ6bURIyXmBuHPoVGB4lfJmj9ZY2+duopBZtGBxghvzmmrw+n1bdlN8uA382Y7ee1e+v77TbsbjiyM1QstpH53fymiOc2W+C7VPCmqm64K+bV9PprieJmdywJf480y1zQtjO4qr1asbba3pHOU0TxVtFAVr4zoPi02ikLZIV/XQDt4X7EZ+wR/A9bHGwsSyIM4bL4WG5lWePOKcgDfAuyMGEe/60X1bBdknY4KZv8Bn4IFBOh2CJtK57FD5XLaI9mMq67tLmfY/VX2fQpftvN9+P6c/O0t+S1wdc7rjHsbPMxqBf44KYN4Cb3x1tjq5LYzz1VhG68HNQ+R/a7+LswnfDx5rnz83m9YrKqm/RmPD+KW2B+n+JnMtlQcFohCTcpUiVhQeBd1Xic8QhbKgL/Ibj4uCmd2cn+X03jXnAz5daD69Tx3UtSkP9hbeepRKY/Mt7yadTFGIdQvZp36E8rn2vntyIcWV0rfaDcUUD/XXvUqui4KVWuvJiUKgQ050v++U775Z9r1qRWFWau3DpQspXjW7va24FyuIjz9vWRHD54N8AY/gGji0w7sXUQmdd/VzZ2/CiVGKfW7+RWN0uayXBu3jrLX1U8d04g0VA6ejhDsdghPWyEQwbsgsP5twzIHs1X6au92G4rxF7e2VLRQPnWI2tf1Nn+23WNAmmuJsrk7F2Th72u+n8Jieu0gvJLgtnUj327wvdD6zmfYvfdbgiBWd9+S5K2LXEL56i1Yf6XrygUVuYRSfHx973B5rzfHpb9R3WYetvN7gsoxHT2n+5OI2ElWyJ1shf8ylTfyds2KSZuNWtntjlbZaoQfzKfyCMUPjULtPhPOF+tUZPuQn46y/ktqS/+w+VVgeCmU9hjwslslafo/Wjcwqb4in/Si4P1PdTPZP/BUQ/LxZ3//rULL3i02Zbeo2vnbLqru1kfxlWzdG8RH5xcPvoPlLJ8Yp4AT4SCPnQ/nKvayz3v1wyDKlfPkzblhphzTiR5tpnW4ncdwdnfTl7Foae1hmpzfS84d5/VIH07X/415LRqUxb7ww0Rt9KoHwsGSN4E888+Xb+U1l9N7VVtil9/ZplL4+Q+8lRexyM6H3ZvlJ9ZhPPGRemXn7o8i6C7rk5yvbx1bEP5ny1oF2xGs3QwO3jqNxS1GKTDuav0PdqZi7lD+tKuhvGsdrJXbsRfkQGCFZP4zyI9dsokZtKr+/v0H/+0mKy97NTdqbKB+TSk2104tEQVtD0/P9DYoD6ef6aU/ILmsFnRmkx/TNLh6vrmZdObr5znKR7H/Z7YpmQQrvUy2uQ7VmDJ/3NxPl2R8i2M/ACeA4+Ac4VpSuu+fIb3gDPkZ+Zf8KC/GfPIWegm4Gvn2clCAnRfP5ZaiH36O4TEu32Lib/Fh17PLLHAmfT2edYdvbkJ2HKEocIjku8P2PY6EDFQgHj612uTuN4ue8Xb7rtZ2Mn+CXPnonKi86MX+8ke/9oBvlxxbZTRErbalOInV7nOKWigVJ02pRCArQOnnYnOKh1Z1LKd8sa1asXCIKlq+frNxCz0/abyhZtYHxoDW7+toz/0BHgBdhB3hrptPKiy50vcjS5HPQHvYrvoNOxXmYWqTk/aD9j3HanakfwPP+uy7BuazpdGtydCDXZZjnulSr4OHvwBPQ/+B9PMc8mBf8CLzFvNeUvBdohPD70N3bKoPfj6D4clWe5V0cwvuCzgRPoh6EPsS8wCl8D95E3iHfJpTomJzez7rM2+DqiSMUhzN/ASHp9YxnXxKIZxxrdt6ft4frbNRZqIvAH9C/SgGVGgejuC5+0sPVZW4E42M/Y7MBEdGsu4EXM6p2/2EYzfrcTGHUheZo/g7Pg2xMGxKziNcbLJ/5EI+q+Cl+6ZvBvJkm5XFgAfHqEmXnv5em874wL/wIO4FPV0oH7eiewrr9wV1jxQM0tnU65viMcGG2RUnUpUTW2aePvbzqTPdvWy/8lhnLOnxmluB7NZbPDfyIc0EdivMCjkC/rbPU7H6O8jKwZnmTqyPnK/i11SsLfVh/Ql+hXnhjPUG+OoTrd+wX/QDUaaj/oHegc6HrXh7Lalv7W1yDD2209I2zA7g+MKubK33Q5b/9GuAO4g72ot6Ajsb+UX+groOOXPHptcGOOMY3nCfixzB6csHjBK4rgOcjtBfPS45nP1SXtg2ZTfd/LS/h94AT4CecC65fvQo8P5HiqJ3qVP9HNMaZ/T0oN5fywF6ta9MJ1qNh6e6L9GJ5PuAz/FGjZLVhM+VNlXlW9hNnxrefoUYpEg/GJ9QxOC/gwTIty2lO+zkfwBPYD/AM66DP5bzI/cdMeu+q/vkLJwP5GvU7zhPnjjiF36AbgSPQw6hnsd/hlmElw2OZL1Hf4hyg43/BHI0qqlKndUIZHwXFr2+XRDLPTqWqLJt0RaXJuu5+lNfiJPn0cfmUryPL5S4WMk4VJv2sMc1jnQ1dvajYftzqeLYXeYE4Q12Aegt4iT7jPKNWpuM6A3a+HXJM6SHZGWPQWoDxd8B75CFwD7oGI/gZeJOs3xoBjGuIr5a9nWVm5nCdAf1zKLR0eindn1t5qag4g3EH9Tzqf/AN4g9+Hzz4Up+8YK57wCfYJ/oX6Ac6p8eT50m3/jo+qm9khnzqKDLuIa+wL+Q34hbniboC14gz6NR63aZYc7L3hNIB9faxzB84D/T7YC/yAPkCHFyt0it74F6eD3wO+xBn81XGR77cx3GBejW58amJ+14+R/AjcAY6DXGPPiL8C30G/EIcoL8I3t+eYbgzhdb3LPIdPGU/69g/LkywrItnXYj4AC9JGzu2WZXKvCmXoyz5Quf/o1v2kvqo/+IE9AXwBf0+5DfwA7wFXoMOriGVqhXP9qI/DDuh45FvOD/EI3AacYN6BPEBngHegTcilIcnfNzD+hB1o/GvwpLOp0h1y83tXAeFRD9t7+TMuIe+AvqF8ANG6EJcoz+D/mR5oQtl9n/7YejHLDVuZzXegXk6S9L9kaIn9x/RJ0N/HPmI/wPQS+A/8Cf2jzxBv25KJ7l2E+g8lKuiXgz8LQ66OEpPMsznftq7JZF1yrncZ0BfQqnmrZ1THusm6CXgK3RUilJrZ411FOYF/yEufEeGzFL5Te8g/qGXkbeIL/A48gbv4T8JRtTTyEPUP+BlxDniF/kFPQ7/4z8O+m34Dv89uge8HWSfwrxh/3i85ify2/Di7JZm8ud1tRFRMtlcf/b5VWjxtUXfHR6WmTwPcBj6+leZI+H/Asgf8Ar2CT0dtqh1RlF41tp+c+W4Qh9cXed1mpU79+fmBM89kmTL9Rv6An2H7jad7cI6AHXdOcnHz4YUrz5x4Xqy1lSHqhR9L7AUhe+eucvK15J+qhxg0mwhCk2Fs1dmUH3W3v2PfhpUn+VWThHO23L9hz7N9fTR8TWOrGeOT5ux+gTdP+pdtLDYnutH9P3LpFv667lzX3VFXIV8sifbebUxNeDVNl4n1d4rfQzld/qDWWOuZPJ5gBdLdFWsPlN83vsREaGUzP0o6HXwF/4fQe+D/3AO+J/4b30C3AAvIJ77qyom94hjHQDeAX5BB0BnYB58Dz2OegT8Ab76t37Fel1vW3XbRXi/s69pbMxvI/oWR1JyRrxJ5NFGYhnsnsr5Cl00sC4hXzaJcRx4jHxDfYv+MfQp8HX+7Z7L+zhzP3V5SZeA4e7c90IdY2+kTiUb90OAt/i/Cd2Ea+Rpa5emwZ3nhx/xHwi4jHoF36HfAl2D/6rAddiJfjn6avNaFlXtp7jtONlzlDqNTyOGXm3azf97kJcXDBw6GuzmvMP/ZvgJ/Aq78L8BI54jTlAPoZ+BEXajPoOegU4AL0APoW+A/5D/9i/iCX0C8P8s1ed3dnqxvbolI+0aA7iOQJ8c/oN94DX4GToYOIf4Rlyjbsd/K/AM+tvok8//v8LuP/X3tpGHR307zDggr6h24i2N6xsnd3lBerlT3MzDVbn8HPkAXoI9yGvUTehbwO4ug2u/u5CuO/Vg+BypRNaf0DnQ68Ab6DL0R5FvGKGDgPs4H/x/hV2wB/yF/3bgO+hy8CfWRR/exXNVcSjl9bcjes7nsrheAJ+tlA7YP6tIFHQkiWb9TxNvm9m0d6Ex527Iq6k0qlfWJu09zjri1nlrNVeqq06aeHxeXMD1BngP50Gi7/iALK7Ttkvb5DrQ+T37Vm0Ykc/PgTvwC3AMPLym9TcTfb9MssfeIJf1y47CxnN2+dzHxTm7mQ/RkzvMOgX9mA95LcWL47heRZ/gf6+vJrc=AQAAAACAAABgIgAAahEAAA==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AgAAAACAAACACQAAohUAALUBAAA=eJxd3dUTQFXZRnFP0N3d3d3d3d3dqYAgJYLSoXR3l9LdCkooqXQrLSkd38V3fhfvc26emTXrH1h75uz9s5/9/9cMu+OwOwRvh90pPLwbdufw8H7YXcLDRxh21/DwEYfdLTx8pGF3Dw8fedg9wsNHGXbP8PBRh90rPHy0YfcODx992J+Hh48x7C/Cw8ccdp/w8LGG3Tc8fOxh9wsPH2fYX4aHjzvs/uHh4w17QHj4+MP+Kjx8gmEPDA+fcNiDwsMnGvbg8PCJhz0kPHySYQ8ND5902F+Hh0827GHh4ZMP+5vw8CmGPTw8fMphjwgPn2rY34aHTz3s78LDpxn2yPDwaYc9Kjx8umGPDg+ffthjwsNnGPbY8PAZhz0uPHymYY8PD5952BPCw2cZ9sTw8FmHPSk8fLZhfx8ePvuwfwgPn2PYk8PD5xz2lPDwuYY9NTx87mFPCw+fZ9jTw8PnHfaM8PD5hj0zPHz+Yc8KD19g2LPDwxcc9pzw8IWGPTc8fOFhzwsPX2TY88PDFx32gvDwxYa9MDx88WEvCg9fYtiLw8OXHPaS8PClhr00PHzpYS8LD19m2MvDw5cd9orw8OWGvTI8fPlhrwoPX2HYq8PDVxz2mvDwlYa9Njx85WGvCw9fZdjrw8NXHfaP4eGrDfun8PDVh70hPHyNYW8MD19z2JvCw9ca9ubw8LWHvSU8fJ1hbw0PX3fY28LD1xv29vDw9Ye9Izx8g2HvDA/fcNi7wsM3Gvbu8PCNh70nPHyTYe8ND9902PvCwzcb9v7w8M2HfSA8fIthHwwP33LYh8LDtxr2z+HhWw/7l/DwbYZ9ODx822EfCQ/fbti/hodvP+zfwtMZeuKxYR8NriceDw/XE0+Eh+uJv4eH64l/hIfriSfDw/XEU+HheuLp8HA98Ux4uJ54NjxcTzwXHq4n/hkerif+FR6uJ54PD9cTL4SH64kXw8P1xEvh4Xri5fBwPfFKeLieeDU8XE+8Fh6uJ14PD9cTb4SH64k3w8P1xFvh4Xri7fDww4b9d3i4nvhPeLieeCc8XE+8Gx6uJ94LD9cT74eH64kPwsP1xIfh4Xrio/BwPfHf8HA98XF4uJ74JDxcT3waHq4nPgsP1xOfh4friS/Cw/XE/8LD9cSX4eF64qvwcD3xdXi4nvgmPFxPfBserie+Cw/XE9+Hh+uJH8LD9cSP4eF64qfwcD3hQOyn4HqiaaqH64m2qR6uJ7qmerie6Jvq4RcOO0JTPVxPjNhUD9cTIzXVw/XEyE31cD0xSlM9XE+M2lQP1xOjNdXD9cToTfVwPTFGUz1cT4zZVA/XE2M11cP1xNhN9XA9MU5TPVxPjNtUD9cT4zXVw/XE+E31cD0xQVM9XE9M2FQP1xMTNdXD9cTETfVwPTFJUz1cT0zaVA/XE5M11cP1xORN9XA9MUVTPVxPTNlUD9cTUzXVw/XE1E31cD0xTVM9XE9M21QP1xPTNdXD9cT0TfXw+4edoakeridmbKqH64mZmurhemLmpnq4npilqR6uJ2Ztqofridma6uF6YvameriemKOpHq475myqpzP0xNwDn6upXE/M01QP1xPzNtXD9cR8TfVwPTF/Uz1cTyzQVA/XEws21cP1xEJN9XA9sXBTPVxPLNJUD9cTizbVw/XEYk31cD2xeFM9XE8s0VQP1xNLNtXD9cRSTfVwPbF0Uz1cTyzTVA/XE8s21cP1xHJN9XA9sXxTPfz1YVdoqoe/MeyKTfVwPbFSUz1cT6zcVA/XE6s01cP1xKpN9XA9sVpTPVxPrN5UD9cTazTVw/XEmk31cD2xVlM9XE+s3VQP1xPrNNXD9cS6TfVwPbFeUz1cT6zfVA/XExs01cP1xIZN9XA9sVFTPVxPbNxUD9cTmzTVw/XEpk31cD2xWVM9XE9s3lQP1xNbNNXD9cSWTfVwPbFVUz1cT2zdVA/XE9s01cP1xLZN9XA9sV1TPVxPbN9UD9cTOzTVw/XEjuHhemKn8HA9sXN4uJ7YJTxcT+waHq4ndgsP1xO7h4friT3Cw/XEnuHhemKv8HA9sXd4uJ74eXi4nvhFeLie2Cc8XE/sGx6uJ/YLD9cTvwwP1xP7h4friQPCw/XEr8LD9cSB4eF64qDwcD1xcHi4njgkPFxPHBoerid+HR6uJw4LD9cTvwkP1xOHh4friSPCw/XEb8PD9cTvwsP1xJHh4XriqPBwPXF0eLieOCY8XE8cGx6uJ44LD9cTx4eH64kTwsP1xInh4XripPBwPfH78HA98YfwcD1xcni47jglPJ2hJ04b9tTgeuL08HA9cUZ4uJ44MzxcT5wVHq4nzg4P1xPnhIfriXPDw/XEeeHheuL88HA9cUF4uJ64MDxcT1wUHq4nLg4P1xOXhIfriUvDw/XEZeHheuLy8HA9cUV4uJ64MjxcT1wVHq4nrg4P1xPXhIfriWvDw/XEdeHheuL68HA98cfwcD3xp/BwPXFDeLieuDE8XE/cFB6uJ24OD9cTt4SH64lbw8P1xG3h4Xri9vBwPXFHeLieuDM8XE/cFR6uJ+4OD9cT94SH64l7w8P1xH3h4Xri/vBwPfFAeLieeDA8XE88FB6uJ/4cHq4n/hIericeDg/XE4+Eh+uJv4aH64m/hYfriUfDw/XEY+HheuLx8HA98UR4uJ74e3i4nvhHeLieeDI8XE88FR6uJ54OD9cTz4SH64lnw8P1xHPh4Xrin+HheuJf4eF64vnwcD3xQni4nngxPFxPvBQerideDg/XE6+Eh+uJV8PD9cRr4eF64vXwcD3xRni4nngzPFxPvBUerifeDg/XE/8OD9cT/wkP1xPvhIfriXfDw/XEe+HheuL98HA98UF4uJ74MDxcT3wUHq4n/hseric+Dg/XE5+Eh+uJT8PD9cRn4eF64vPwcD3xRXi4nvhfeLie+DI8XE98FR6uO74OT2foiW+H/Sa4nvguPFxPfB8erid+CA/XEz+Gh+uJn8LD9YQfUn4Krieatnq4nmjb6uF6omurh+uJvq0eridGaKuH64kR2+rhemKktnq4nhi5rR6uJ0Zpq4friVHb6uF6YrS2erieGL2tHq4nxmirh+uJMdvq4XpirLZ6uJ4Yu60erifGaauH64lx2+rhemK8tnq4nhi/rR6uJyZoq4friQnb6uF6YqK2eriemLitHq4nJmmrh+uJSdvq4XpisrZ6uJ6YvK0eriemaKuH64kp2+rhemKqtnq4npi6rR6uJ6Zpq4friWnb6uF6Yrq2eriemL6tHq4nZmirh+uJGdvq4XpiprZ6uJ6Yua0eridmaauH64lZ2+rhemK2tnq4npi9rR6uJ+Zoq4friTnb6uF6Yq62eriemLutHq4n5mmrh+uJedvq4XpivrZ6uJ6Yv60ericWaKuH64kF2+rhemKhtnq4nli4rR6uJxZpq4friUXb6uF6YrG2erieWLytHq4nlmirh+uJJdvq4XpiqbZ6uJ5Yuq0erieWaauH64ll2+rhemK5tnq4nli+rR6uJ1Zoq4friRXb6uF6YqW2erieWLmtHq4nVmmrh+uJVdvq4XpitbZ6uJ5Yva0erifWaKuH64k12+rhemKttnq4nli7rR6uJ9Zpq4friXXb6uF6Yr22erieWL+tHq4nNmirh+uJDdvq4Xpio7Z6uJ7YuK0eric2aauH64lN2+rhemKztnq4nti8rR6uO7Zoq6cz9MRWA9+yrVxPbN1WD9cT27TVw/XEtm31cD2xXVs9XE9s31YP1xM7tNXD9cSO4eF6YqfwcD2xc3i4ntglPFxP7Boerid2Cw/XE7uHh+uJPcLD9cSe4eF6Yq/wcD2xd3i4nvh5eLie+EV4uJ7YJzxcT+wbHq4n9gsP1xO/DA/XE/uHh+uJA8LD9cSvwsP1xIHh4XrioPBwPXFweLieOCQ8XE8cGh6uJ34dHq4nDgsP1xO/CQ/XE4eHh+uJI8LD9cRvw8P1xO/Cw/XEkeHheuKo8HA9cXR4uJ44JjxcTxwbHq4njgsP1xPHh4friRPCw/XEieHheuKk8HA98fvwcD3xh/BwPXFyeLieOCU8XE+cGh6uJ04LD9cTp4eH64kzwsP1xJnh4XrirPBwPXF2eLieOCc8XE+cGx6uJ84LD9cT54eH64kLwsP1xIXh4XriovBwPXFxeLieuCQ8XE9cGh6uJy4LD9cTl4eH64krwsP1xJXh4XriqvBwPXF1eLieuCY8XE9cGx6uJ64LD9cT14eH64k/hofriT+Fh+uJG8LD9cSN4eF64qbwcD1xc3i4nrglPFxP3BoeriduCw/XE7eHh+uJO8LD9cSd4eF64q7wcD1xd3i4nrgnPFxP3BserifuCw/XE/eHh+uJB8LDdceD4ekMPfHnYR8Krif+Eh6uJx4OD9cTj4SH64m/hofrib+Fh+uJR8PD9cRj4eF64vHwcD3xRHi4nvh7eLie+Ed4uJ54MjxcTzwVHq4nng4P1xPPhIfriWfDw/XEc+HheuKf4eF64l/h4Xri+fBwPfFCeLieeDE8XE+8FB6uJ14OD9cTr4SH64lXw8P1xGvh4Xri9fBwPfFGeLieeDM8XE+8FR6uJ94OD9cT/w4P1xP/CQ/XE++Eh+uJd8PD9cR74eF64v3wcD3xQXi4nvgwPFxPfBQerif+Gx6uJz4OD9cTn4SH64lPw8P1xGfh4Xri8/BwPfFFeLie+F94uJ74MjxcT3wVHq4nvg4P1xPfhIfriW/Dw/XEd+HheuL78HA98UN4uJ74MTxcT/wUHq4nXBj5U3A90XTVw/VE21UP1xNdVz1cT/Rd9XA9MUJXPVxPjNhVD9cTI3XVw/XEyF31cD0xSlc9XE+M2lUP1xOjddXD9cToXfVwPTFGVz1cT4zZVQ/XE2N11cP1xNhd9XA9MU5XPVxPjNtVD9cT43XVw/XE+F31cD0xQVc9XE9M2FUP1xMTddXD9cTEXfVwPTFJVz1cT0zaVQ/XE5N11cP1xORd9XA9MUVXPVxPTNlVD9cTU3XVw/XE1F31cD0xTVc9XE9M21UP1xPTddXD9cT0XfVwPTFDVz1cT8zYVQ/XHTN11dMZemKWgc/cVa4nZu2qh+uJ2brq4Xpi9q56uJ6Yo6serifm7KqH64m5uurhemLurnq4npinqx6uJ+btqofrifm66uF6Yv6uerieWKCrHq4nFuyqh+uJhbrq4Xpi4a56uJ5YpKsericW7aqH64nFuurhemLxrnq4nliiqx6uJ5bsqofriaW66uF6YumuerieWKarHq4nlu2qh+uJ5brq4Xpi+a56uJ5YoaseridW7KqH64mVuurhemLlrnq4nlilqx6uJ1btqofridW66uF6YvWuerieWKOrHq4n1uyqh+uJtbrq4Xpi7a56uJ5Yp6serifW7aqH64n1uurhemL9rnq4ntigqx6uJzbsqofriY266uF6YuOuerie2KSrHq4nNu2qh+uJzbrq4Xpi8656uJ7Yoqserie27KqH64mtuurhemLrrnq4ntimqx6uJ7btqofrie266uF6Yvuuerie2KGrHq4ndgwP1xM7hYfriZ3Dw/XELuHhemLX8HA9sVt4uJ7YPTxcT+wRHq4n9gwP1xN7hYfrib3Dw/XEz8PD9cQvwsP1xD7h4Xpi3/BwPbFfeLie+GV4uJ7YPzxcTxwQHq4nfhUericODA/XEweFh+uJg8PD9cQh4eF64tDwcD3x6/BwPXFYeLie+E14uJ44PDxcTxwRHq4nfhserid+Fx6uJ44MD9cTR4WH64mjw8P1xDHh4Xri2PBwPXFceLjuOD48naEnThz2hOB64qTwcD3x+/BwPfGH8HA9cXJ4uJ44JTxcT5waHq4nTgsP1xOnh4friTPCw/XEmeHheuKs8HA9cXZ4uJ44JzxcT5wbHq4nzgsP1xPnh4friQvCw/XEheHheuKi8HA9cXF4uJ64JDxcT1waHq4nLgsP1xOXh4friSvCw/XEleHheuKq8HA9cXV4uJ64JjxcT1wbHq4nrgsP1xPXh4friT+Gh+uJP4WH64kbwsP1xI3h4XripvBwPXFzeLieuCU8XE/cGh6uJ24LD9cTt4eH64k7wsP1xJ3h4XrirvBwPXF3eLieuCc8XE/cGx6uJ+4LD9cT94eH64kHwsP1xIPh4XriofBwPfHn8HA98ZfwcD3xcHi4nngkPFxP/DU8XE/8LTxcTzwaHq4nHgsP1xOPh4friSfCw/XE38PD9cQ/wsP1xJPh4XriqfBwPfF0eLieeCY8XE88Gx6uJ54LD9cT/wwP1xP/Cg/XE8+Hh+uJF8LD9cSL4eF64qXwcD3xcni4nnglPFxPvBoerideCw/XE6+Hh+uJN8LD9cSb4eF64q3wcD3xdni4nvh3eLie+E94uJ54JzxcT7wbHq4n3gsP1xPvh4friQ/Cw/XEh+HheuKj8HA98d/wcD3xcXi4nvgkPFx3fBqeztATnw/7WXA98UV4uJ74X3i4nvgyPFxPfBUerie+Dg/XE9+Eh+uJb8PD9cR34eF64vvwcD3xQ3i4nvgxPFxP/BQeric82PhTcD3R9NXD9UTbVw/XE11fPVxP9H31cD0xQl89XE+M2FcP1xMj9dXD9cTIffVwPTFKXz1cT4zaVw/XE6P11cP1xOh99XA9MUZfPVxPjNlXD9cTY/XVw/XE2H31cD0xTl89XE+M21cP1xPj9dXD9cT4ffVwPTFBXz1cT0zYVw/XExP11cP1xMR99XA9MUlfPVxPTNpXD9cTk/XVw/XE5H31cD0xRV89XE9M2VcP1xNT9dXD9cTUffVwPTFNXz1cT0zbVw/XE9P11cP1xPR99XA9MUNfPVxPzNhXD9cTM/XVw/XEzH31cD0xS189XE/M2lcP1xOz9dXD9cTsffVwPTFHXz1cT8zZVw/XE3P11cP1xNx99XA9MU9fPVxPzNtXD9cT8/XVw/XE/H31cD2xQF89XE8s2FcP1xML9dXD9cTCffVwPbFIXz1cTyzaVw/XE4v11cP1xOJ99XA9sURfPVxPLNlXD9cTS/XVw/XE0n31cD2xTF89XE8s21cP1xPL9dXD9cTyffVwPbFCXz1cT6zYVw/XEyv11cP1xMp99XA9sUpfPVxPrNpXD9cTq/XVw/XE6n31cD2xRl89XE+s2VcP1xNr9dXD9cTaffVwPbFOXz1cT6zbVw/XE+v11cP1xPp99XA9sUFfPVx3bNhXT2foiY0HvlFfuZ7YpK8eric27auH64nN+urhemLzvnq4ntiirx6uJ7bsq4fria366uF6Yuu+erie2KavHq4ntu2rh+uJ7frq4Xpi+756uJ7Yoa8erid2DA/XEzuFh+uJncPD9cQu4eF6YtfwcD2xW3i4ntg9PFxP7BEerif2DA/XE3uF938YiQYReJxdyldXCAAAhmEXrpBZskM2IRnZIYqUmb9hhuy9tyIjlFUSEjL+XOc473fzfjfPOd95hw0d8n/D8RAe1D8CD6vLX4BH1OUfiUfV5R+Fx9TlH41N6vKPwePq8o/FE+ryj8OT6vIXYrO6/EV4Sl3+8XhaXf5iPKMu/wQ8qy7/RDynLv8kPK8u/2S8oC7/FLyoLv9UvKQu/zS8rC5/CV5Rl386XlWXfwZeU5d/Jl5Xl78Ub6jLPwtvqss/G2+pyz8Hb6vLPxfvqMs/D++qyz8f76nLvwDvq8u/EB+oy78IH6rLX4aP1OVfjI/V5V+CLeryL8VWdfnL8Ym6/Mvwqbr8FdimLv9yfKYu/wp8ri7/SnyhLv8qfKkufyW2q8u/Gl+py78GX6vLvxbfqMu/DjvU5V+Pneryb8C36vJvxHfq8lfhe3X5N+EHdfk340d1+bdgl7r81ditLv9W/KQu/zbsUZe/Bj+ry1+Lveryb8cv6vLvwK/q8tfhN3X5d2Kfuvz1+F1d/gbsV5d/F/5Ql383/lSXfw/+Upd/Lw6oy78Pf6vLvx//qMvfiH/V5T+A/9QNAuQGebk=AQAAAACAAABgIgAA3wUAAA==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eJzj5BwFo2AUjALKAQAyByat
|
| 26 |
+
</AppendedData>
|
| 27 |
+
</VTKFile>
|
CylinderKnMa/Kn0p36/simulation0788_Kn0p36Ma5p7/Lambda/Lambda_300000.pvtu
ADDED
|
@@ -0,0 +1,21 @@
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|
| 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="c_6[1]"/>
|
| 11 |
+
<PDataArray type="Float64" Name="c_6[2]"/>
|
| 12 |
+
</PCellData>
|
| 13 |
+
<PPoints>
|
| 14 |
+
<PDataArray type="Float32" Name="Points" NumberOfComponents="3"/>
|
| 15 |
+
</PPoints>
|
| 16 |
+
<Piece Source="Lambda_0_300000.vtu"/>
|
| 17 |
+
<Piece Source="Lambda_1_300000.vtu"/>
|
| 18 |
+
<Piece Source="Lambda_2_300000.vtu"/>
|
| 19 |
+
<Piece Source="Lambda_3_300000.vtu"/>
|
| 20 |
+
</PUnstructuredGrid>
|
| 21 |
+
</VTKFile>
|
CylinderKnMa/Kn0p36/simulation0788_Kn0p36Ma5p7/Lambda/Lambda_3_300000.vtu
ADDED
|
@@ -0,0 +1,27 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 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="276" NumberOfCells="242" >
|
| 5 |
+
<PointData>
|
| 6 |
+
</PointData>
|
| 7 |
+
<CellData>
|
| 8 |
+
<DataArray type="Float64" Name="id" format="appended" RangeMin="12301" RangeMax="13542" offset="0" />
|
| 9 |
+
<DataArray type="Float64" Name="xc" format="appended" RangeMin="4.0615" RangeMax="5.9549" offset="508" />
|
| 10 |
+
<DataArray type="Float64" Name="yc" format="appended" RangeMin="4.0541" RangeMax="4.955" offset="808" />
|
| 11 |
+
<DataArray type="Float64" Name="c_6[1]" format="appended" RangeMin="0.018028" RangeMax="0.033044" offset="976" />
|
| 12 |
+
<DataArray type="Float64" Name="c_6[2]" format="appended" RangeMin="0.19994" RangeMax="0.36649" offset="3420" />
|
| 13 |
+
</CellData>
|
| 14 |
+
<Points>
|
| 15 |
+
<DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="5.6748189645" RangeMax="7.8102496759" offset="5800" />
|
| 16 |
+
</Points>
|
| 17 |
+
<Cells>
|
| 18 |
+
<DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="6740" />
|
| 19 |
+
<DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="8416" />
|
| 20 |
+
<DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="8948" />
|
| 21 |
+
</Cells>
|
| 22 |
+
</Piece>
|
| 23 |
+
</UnstructuredGrid>
|
| 24 |
+
<AppendedData encoding="base64">
|
| 25 |
+
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|
| 26 |
+
</AppendedData>
|
| 27 |
+
</VTKFile>
|
CylinderKnMa/Kn0p36/simulation0788_Kn0p36Ma5p7/Surf.pvd
ADDED
|
@@ -0,0 +1,9 @@
|
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|
|
|
|
| 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/Kn0p36/simulation0788_Kn0p36Ma5p7/config.txt
ADDED
|
@@ -0,0 +1,78 @@
|
|
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|
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|
|
|
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|
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|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
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|
|
|
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|
|
|
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|
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|
|
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|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 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 0.36
|
| 13 |
+
variable Ma equal 5.7
|
| 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/Kn0p36/simulation0788_Kn0p36Ma5p7/cylinder.surf
ADDED
|
@@ -0,0 +1,410 @@
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
surf file from Pointwise
|
| 2 |
+
|
| 3 |
+
200 points
|
| 4 |
+
200 lines
|
| 5 |
+
|
| 6 |
+
Points
|
| 7 |
+
|
| 8 |
+
1 0.5 0.0
|
| 9 |
+
2 0.499753280182866E+000 -0.157053795390643E-001
|
| 10 |
+
3 0.499013364214136E+000 -0.313952597646568E-001
|
| 11 |
+
4 0.497780982301540E+000 -0.470541566592573E-001
|
| 12 |
+
5 0.496057350657239E+000 -0.626666167821523E-001
|
| 13 |
+
6 0.493844170297569E+000 -0.782172325201156E-001
|
| 14 |
+
7 0.491143625364344E+000 -0.936906572928624E-001
|
| 15 |
+
8 0.487958380969374E+000 -0.109071620698271E+000
|
| 16 |
+
9 0.484291580564315E+000 -0.124344943582427E+000
|
| 17 |
+
10 0.480146842838471E+000 -0.139495553019615E+000
|
| 18 |
+
11 0.475528258147577E+000 -0.154508497187474E+000
|
| 19 |
+
12 0.470440384477113E+000 -0.169368960122646E+000
|
| 20 |
+
13 0.464888242944126E+000 -0.184062276342339E+000
|
| 21 |
+
14 0.458877312841991E+000 -0.198573945317390E+000
|
| 22 |
+
15 0.452413526233010E+000 -0.212889645782536E+000
|
| 23 |
+
16 0.445503262094184E+000 -0.226995249869774E+000
|
| 24 |
+
17 0.438153340021932E+000 -0.240876837050858E+000
|
| 25 |
+
18 0.430371013501972E+000 -0.254520707875186E+000
|
| 26 |
+
19 0.422163962751007E+000 -0.267913397489498E+000
|
| 27 |
+
20 0.413540287137281E+000 -0.281041688926065E+000
|
| 28 |
+
21 0.404508497187474E+000 -0.293892626146237E+000
|
| 29 |
+
22 0.395077506187845E+000 -0.306453526826488E+000
|
| 30 |
+
23 0.385256621387895E+000 -0.318711994874345E+000
|
| 31 |
+
24 0.375055534815230E+000 -0.330655932661826E+000
|
| 32 |
+
25 0.364484313710706E+000 -0.342273552964344E+000
|
| 33 |
+
26 0.353553390593274E+000 -0.353553390593274E+000
|
| 34 |
+
27 0.342273552964344E+000 -0.364484313710706E+000
|
| 35 |
+
28 0.330655932661826E+000 -0.375055534815230E+000
|
| 36 |
+
29 0.318711994874345E+000 -0.385256621387895E+000
|
| 37 |
+
30 0.306453526826488E+000 -0.395077506187845E+000
|
| 38 |
+
31 0.293892626146236E+000 -0.404508497187474E+000
|
| 39 |
+
32 0.281041688926065E+000 -0.413540287137281E+000
|
| 40 |
+
33 0.267913397489498E+000 -0.422163962751008E+000
|
| 41 |
+
34 0.254520707875185E+000 -0.430371013501972E+000
|
| 42 |
+
35 0.240876837050857E+000 -0.438153340021932E+000
|
| 43 |
+
36 0.226995249869773E+000 -0.445503262094184E+000
|
| 44 |
+
37 0.212889645782536E+000 -0.452413526233010E+000
|
| 45 |
+
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+
131 131 132
|
| 342 |
+
132 132 133
|
| 343 |
+
133 133 134
|
| 344 |
+
134 134 135
|
| 345 |
+
135 135 136
|
| 346 |
+
136 136 137
|
| 347 |
+
137 137 138
|
| 348 |
+
138 138 139
|
| 349 |
+
139 139 140
|
| 350 |
+
140 140 141
|
| 351 |
+
141 141 142
|
| 352 |
+
142 142 143
|
| 353 |
+
143 143 144
|
| 354 |
+
144 144 145
|
| 355 |
+
145 145 146
|
| 356 |
+
146 146 147
|
| 357 |
+
147 147 148
|
| 358 |
+
148 148 149
|
| 359 |
+
149 149 150
|
| 360 |
+
150 150 151
|
| 361 |
+
151 151 152
|
| 362 |
+
152 152 153
|
| 363 |
+
153 153 154
|
| 364 |
+
154 154 155
|
| 365 |
+
155 155 156
|
| 366 |
+
156 156 157
|
| 367 |
+
157 157 158
|
| 368 |
+
158 158 159
|
| 369 |
+
159 159 160
|
| 370 |
+
160 160 161
|
| 371 |
+
161 161 162
|
| 372 |
+
162 162 163
|
| 373 |
+
163 163 164
|
| 374 |
+
164 164 165
|
| 375 |
+
165 165 166
|
| 376 |
+
166 166 167
|
| 377 |
+
167 167 168
|
| 378 |
+
168 168 169
|
| 379 |
+
169 169 170
|
| 380 |
+
170 170 171
|
| 381 |
+
171 171 172
|
| 382 |
+
172 172 173
|
| 383 |
+
173 173 174
|
| 384 |
+
174 174 175
|
| 385 |
+
175 175 176
|
| 386 |
+
176 176 177
|
| 387 |
+
177 177 178
|
| 388 |
+
178 178 179
|
| 389 |
+
179 179 180
|
| 390 |
+
180 180 181
|
| 391 |
+
181 181 182
|
| 392 |
+
182 182 183
|
| 393 |
+
183 183 184
|
| 394 |
+
184 184 185
|
| 395 |
+
185 185 186
|
| 396 |
+
186 186 187
|
| 397 |
+
187 187 188
|
| 398 |
+
188 188 189
|
| 399 |
+
189 189 190
|
| 400 |
+
190 190 191
|
| 401 |
+
191 191 192
|
| 402 |
+
192 192 193
|
| 403 |
+
193 193 194
|
| 404 |
+
194 194 195
|
| 405 |
+
195 195 196
|
| 406 |
+
196 196 197
|
| 407 |
+
197 197 198
|
| 408 |
+
198 198 199
|
| 409 |
+
199 199 200
|
| 410 |
+
200 200 1
|
CylinderKnMa/Kn0p36/simulation0788_Kn0p36Ma5p7/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/Kn0p36/simulation0788_Kn0p36Ma5p7/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
|