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- .gitattributes +5 -0
- CylinderKnMa/Kn0p32/simulation0667_Kn0p32Ma3p6/output/grid.300000.dat +3 -0
- CylinderKnMa/Kn0p32/simulation0668_Kn0p32Ma3p7/output/grid.300000.dat +3 -0
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- CylinderKnMa/Kn0p32/simulation0670_Kn0p32Ma3p9/output/grid.300000.dat +3 -0
- CylinderKnMa/Kn0p32/simulation0671_Kn0p32Ma4p0/output/grid.300000.dat +3 -0
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- CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/config.txt +78 -0
- CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/cylinder.surf +410 -0
- CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/gas.species +14 -0
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- CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/log.sparta +319 -0
- CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/mir.txt +3 -0
- CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/output/grid.300000.dat +0 -0
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- CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/runmpirun128.sh +18 -0
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- CylinderKnMa/Kn0p38/simulation0832_Kn0p38Ma5p1/config.txt +78 -0
- CylinderKnMa/Kn0p38/simulation0832_Kn0p38Ma5p1/cylinder.surf +410 -0
.gitattributes
CHANGED
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CylinderKnMa/Kn0p38/simulation0830_Kn0p38Ma4p9/output/lambdakn.300000.dat
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CylinderKnMa/Kn0p38/simulation0830_Kn0p38Ma4p9/output/surf.300000.dat
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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 0.00182 0.03624 -0.036236 0.00056923 -8.8061e-06 -0.00056057 -0.0005693 1.3612e-07 6.5222 0 0
|
| 11 |
+
129 -0.31871 0.38526 -0.30645 0.39508 0.11157 2.4826 1.5522 -1.9375 0.42063 0.33699 0.030988 -0.025139 654.24 0 0
|
| 12 |
+
2 0.49975 -0.015705 0.49901 -0.031395 0.00192 0.036698 -0.036657 0.0017287 0.00015262 0.0032363 -0.00057339 7.7987e-05 6.6486 0 0
|
| 13 |
+
130 -0.30645 0.39508 -0.29389 0.40451 0.1064 2.37 1.423 -1.8953 0.41737 0.31337 0.028907 -0.024847 598.68 0 0
|
| 14 |
+
3 0.49901 -0.031395 0.49778 -0.047054 0.00216 0.04291 -0.042778 0.0033667 0.00025789 0.0032768 -0.00066787 0.00010435 8.5888 0 0
|
| 15 |
+
131 -0.29389 0.40451 -0.28104 0.41354 0.10199 2.2741 1.3076 -1.8606 0.45433 0.31931 0.027676 -0.024209 609.52 0 0
|
| 16 |
+
4 0.49778 -0.047054 0.49606 -0.062667 0.00199 0.040344 -0.0401 0.0044271 4.6026e-06 4.169e-05 -0.00062979 7.0192e-05 6.9874 0 0
|
| 17 |
+
132 -0.28104 0.41354 -0.26791 0.42216 0.09565 2.1417 1.1759 -1.7901 0.435 0.28574 0.025302 -0.023629 570.5 0 0
|
| 18 |
+
5 0.49606 -0.062667 0.49384 -0.078217 0.0019 0.037834 -0.037456 0.0053308 0.00050661 0.0035596 -0.00058038 0.00013965 6.8277 0 0
|
| 19 |
+
133 -0.26791 0.42216 -0.25452 0.43037 0.09014 2.0097 1.0501 -1.7136 0.46653 0.28589 0.023822 -0.022425 550.96 0 0
|
| 20 |
+
6 0.49384 -0.078217 0.49114 -0.093691 0.0017 0.032688 -0.032201 0.00562 0.00014492 0.00083038 -0.00050352 0.00010132 7.0063 0 0
|
| 21 |
+
134 -0.25452 0.43037 -0.24088 0.43815 0.0865 1.9133 0.94797 -1.662 0.45154 0.25755 0.021982 -0.022059 514.76 0 0
|
| 22 |
+
7 0.49114 -0.093691 0.48796 -0.10907 0.00154 0.029062 -0.028459 0.0058935 1.6801e-05 8.1128e-05 -0.00044675 9.3845e-05 5.6738 0 0
|
| 23 |
+
135 -0.24088 0.43815 -0.227 0.4455 0.08048 1.7903 0.83775 -1.5822 0.45084 0.23871 0.02024 -0.021103 493.25 0 0
|
| 24 |
+
8 0.48796 -0.10907 0.48429 -0.12434 0.00191 0.036539 -0.03553 0.0085299 6.0706e-05 0.00025286 -0.00055712 0.00013795 6.4232 0 0
|
| 25 |
+
136 -0.227 0.4455 -0.21289 0.45241 0.07521 1.6693 0.73438 -1.499 0.42609 0.20874 0.018228 -0.020267 450.66 0 0
|
| 26 |
+
9 0.48429 -0.12434 0.48015 -0.1395 0.00182 0.03489 -0.033654 0.0092066 0.00052784 0.0019295 -0.00052032 0.00017492 7.0971 0 0
|
| 27 |
+
137 -0.21289 0.45241 -0.19857 0.45888 0.07269 1.6119 0.66333 -1.4691 0.44933 0.20288 0.017477 -0.019889 447.7 0 0
|
| 28 |
+
10 0.48015 -0.1395 0.47553 -0.15451 0.00188 0.036523 -0.034908 0.010739 0.00086766 0.0028204 -0.00053469 0.00021298 8.739 0 0
|
| 29 |
+
138 -0.19857 0.45888 -0.18406 0.46489 0.06958 1.548 0.59241 -1.4302 0.44434 0.18405 0.016284 -0.019574 429.2 0 0
|
| 30 |
+
11 0.47553 -0.15451 0.47044 -0.16937 0.00159 0.032544 -0.030789 0.010542 0.0021131 0.0061718 -0.00045043 0.00026252 6.2163 0 0
|
| 31 |
+
139 -0.18406 0.46489 -0.16937 0.47044 0.06291 1.386 0.48992 -1.2965 0.41576 0.1571 0.014226 -0.017898 385.85 0 0
|
| 32 |
+
12 0.47044 -0.16937 0.46489 -0.18406 0.00169 0.030974 -0.028975 0.010949 0.0016925 0.004479 -0.00042853 0.00024233 8.231 0 0
|
| 33 |
+
140 -0.16937 0.47044 -0.15451 0.47553 0.0617 1.3694 0.44359 -1.2956 0.41941 0.1436 0.013555 -0.018095 388.86 0 0
|
| 34 |
+
13 0.46489 -0.18406 0.45888 -0.19857 0.00168 0.031628 -0.02922 0.012103 0.0021586 0.0052114 -0.00042507 0.00027197 7.5826 0 0
|
| 35 |
+
141 -0.15451 0.47553 -0.1395 0.48015 0.05527 1.2122 0.35644 -1.1586 0.39849 0.12259 0.011858 -0.016273 347.84 0 0
|
| 36 |
+
14 0.45888 -0.19857 0.45241 -0.21289 0.00169 0.033781 -0.030788 0.013901 0.0028141 0.0062324 -0.0004394 0.00031625 7.3932 0 0
|
| 37 |
+
142 -0.1395 0.48015 -0.12434 0.48429 0.05332 1.1679 0.30818 -1.1265 0.39549 0.10819 0.011053 -0.015995 330.89 0 0
|
| 38 |
+
15 0.45241 -0.21289 0.4455 -0.227 0.00177 0.031999 -0.028736 0.014078 0.0049813 0.010168 -0.00037313 0.00038083 7.6955 0 0
|
| 39 |
+
143 -0.12434 0.48429 -0.10907 0.48796 0.04924 1.087 0.25375 -1.057 0.38423 0.092245 0.010021 -0.015153 310.49 0 0
|
| 40 |
+
16 0.4455 -0.227 0.43815 -0.24088 0.00148 0.026957 -0.023824 0.012614 0.00385 0.0072713 -0.00031374 0.00031235 6.1992 0 0
|
| 41 |
+
144 -0.10907 0.48796 -0.093691 0.49114 0.04652 1.0146 0.20575 -0.99354 0.39947 0.082726 0.0095064 -0.014306 296.4 0 0
|
| 42 |
+
17 0.43815 -0.24088 0.43037 -0.25452 0.00169 0.030681 -0.02665 0.015201 0.0060624 0.010629 -0.00032338 0.00040571 8.3913 0 0
|
| 43 |
+
145 -0.093691 0.49114 -0.078217 0.49384 0.04382 0.95351 0.16394 -0.93931 0.36823 0.064266 0.0083588 -0.013745 266.92 0 0
|
| 44 |
+
18 0.43037 -0.25452 0.42216 -0.26791 0.00198 0.035471 -0.030244 0.018533 0.008373 0.013664 -0.00034353 0.00050573 10.684 0 0
|
| 45 |
+
146 -0.078217 0.49384 -0.062667 0.49606 0.03906 0.83764 0.11803 -0.82929 0.33917 0.048271 0.0071813 -0.012268 241.74 0 0
|
| 46 |
+
19 0.42216 -0.26791 0.41354 -0.28104 0.0021 0.039808 -0.033272 0.021856 0.01008 0.015345 -0.00036428 0.00058432 11.005 0 0
|
| 47 |
+
147 -0.062667 0.49606 -0.047054 0.49778 0.03776 0.80985 0.088868 -0.80496 0.34047 0.037589 0.0067438 -0.012053 235.4 0 0
|
| 48 |
+
20 0.41354 -0.28104 0.40451 -0.29389 0.00191 0.034479 -0.028209 0.019826 0.009682 0.013776 -0.00029101 0.00052779 9.341 0 0
|
| 49 |
+
148 -0.047054 0.49778 -0.031395 0.49901 0.03467 0.75626 0.059336 -0.75393 0.32971 0.025949 0.0061109 -0.011435 231.96 0 0
|
| 50 |
+
21 0.40451 -0.29389 0.39508 -0.30645 0.00186 0.033598 -0.026868 0.020173 0.013079 0.01742 -0.00021658 0.00059048 9.9056 0 0
|
| 51 |
+
149 -0.031395 0.49901 -0.015705 0.49975 0.0318 0.68271 0.03216 -0.68195 0.30509 0.014388 0.0052974 -0.010486 206.32 0 0
|
| 52 |
+
22 0.39508 -0.30645 0.38526 -0.31871 0.00222 0.040697 -0.031761 0.025445 0.015796 0.019717 -0.00025076 0.00070938 11.897 0 0
|
| 53 |
+
150 -0.015705 0.49975 0 0.5 0.02974 0.64414 0.010118 -0.64406 0.29669 0.0046608 0.0048192 -0.010043 200.38 0 0
|
| 54 |
+
23 0.38526 -0.31871 0.37506 -0.33066 0.00243 0.042908 -0.032628 0.027867 0.019526 0.022862 -0.00020579 0.00079681 13.43 0 0
|
| 55 |
+
151 0 0.5 0.015705 0.49975 0.02746 0.58453 -0.0091815 -0.58446 0.28689 -0.0045069 0.0043621 -0.0092511 185.98 0 0
|
| 56 |
+
24 0.37506 -0.33066 0.36448 -0.34227 0.0025 0.044777 -0.033118 0.030135 0.022119 0.024308 -0.00017277 0.00085516 15.65 0 0
|
| 57 |
+
152 0.015705 0.49975 0.031395 0.49901 0.02558 0.54362 -0.025608 -0.54302 0.26927 -0.012698 0.0038272 -0.0087288 164.17 0 0
|
| 58 |
+
25 0.36448 -0.34227 0.35355 -0.35355 0.00274 0.050656 -0.036378 0.035252 0.025792 0.026615 -0.00016627 0.00097177 17.301 0 0
|
| 59 |
+
153 0.031395 0.49901 0.047054 0.49778 0.02439 0.51869 -0.040696 -0.51709 0.25343 -0.019946 0.0033415 -0.0084353 157.93 0 0
|
| 60 |
+
26 0.35355 -0.35355 0.34227 -0.36448 0.00291 0.051046 -0.035524 0.036658 0.024616 0.023854 -0.00017134 0.00095048 16.136 0 0
|
| 61 |
+
154 0.047054 0.49778 0.062667 0.49606 0.02185 0.45975 -0.05045 -0.45697 0.24254 -0.026777 0.0030173 -0.0075984 145.92 0 0
|
| 62 |
+
27 0.34227 -0.36448 0.33066 -0.37506 0.00307 0.054547 -0.036711 0.040345 0.033578 0.030553 -4.9219e-05 0.0011136 21.356 0 0
|
| 63 |
+
155 0.062667 0.49606 0.078217 0.49384 0.01975 0.41566 -0.058567 -0.41152 0.21758 -0.030967 0.0024977 -0.0069502 126.21 0 0
|
| 64 |
+
28 0.33066 -0.37506 0.31871 -0.38526 0.00351 0.064822 -0.042098 0.049291 0.035675 0.030469 -0.0001009 0.0012528 21.264 0 0
|
| 65 |
+
156 0.078217 0.49384 0.093691 0.49114 0.01721 0.35454 -0.060956 -0.34926 0.19189 -0.033491 0.0020567 -0.006012 110.4 0 0
|
| 66 |
+
29 0.31871 -0.38526 0.30645 -0.39508 0.00411 0.075709 -0.047337 0.059086 0.048282 0.038681 1.4851e-05 0.0015357 27.721 0 0
|
| 67 |
+
157 0.093691 0.49114 0.10907 0.48796 0.01621 0.33054 -0.067028 -0.32367 0.19243 -0.03985 0.0019697 -0.0057099 108.86 0 0
|
| 68 |
+
30 0.30645 -0.39508 0.29389 -0.40451 0.00408 0.074989 -0.045025 0.059967 0.05035 0.037804 8.364e-05 0.0015357 26.645 0 0
|
| 69 |
+
158 0.10907 0.48796 0.12434 0.48429 0.01483 0.3036 -0.070874 -0.29521 0.16727 -0.040158 0.0015141 -0.0052677 97.2 0 0
|
| 70 |
+
31 0.29389 -0.40451 0.28104 -0.41354 0.00517 0.095073 -0.054668 0.077784 0.056888 0.039982 3.4879e-05 0.0018498 33.517 0 0
|
| 71 |
+
159 0.12434 0.48429 0.1395 0.48015 0.01392 0.28136 -0.074244 -0.27139 0.16076 -0.043979 0.0013589 -0.0049536 93.352 0 0
|
| 72 |
+
32 0.28104 -0.41354 0.26791 -0.42216 0.0051 0.096143 -0.052785 0.080357 0.060695 0.039869 0.00012425 0.0018884 34.098 0 0
|
| 73 |
+
160 0.1395 0.48015 0.15451 0.47553 0.01214 0.24974 -0.073434 -0.2387 0.15356 -0.04724 0.0012585 -0.0044914 83.732 0 0
|
| 74 |
+
33 0.26791 -0.42216 0.25452 -0.43037 0.00551 0.10685 -0.055829 0.091105 0.069102 0.042346 0.00020849 0.0020962 40.608 0 0
|
| 75 |
+
161 0.15451 0.47553 0.16937 0.47044 0.01198 0.24052 -0.077907 -0.22755 0.14618 -0.050048 0.0010724 -0.0043603 84.653 0 0
|
| 76 |
+
34 0.25452 -0.43037 0.24088 -0.43815 0.00701 0.1317 -0.065252 0.1144 0.08482 0.04838 0.00030735 0.0025568 45.964 0 0
|
| 77 |
+
162 0.16937 0.47044 0.18406 0.46489 0.01049 0.20072 -0.07095 -0.18776 0.12428 -0.046963 0.00083773 -0.0036869 65.601 0 0
|
| 78 |
+
35 0.24088 -0.43815 0.227 -0.4455 0.00725 0.14003 -0.065526 0.12376 0.087349 0.046249 0.00034278 0.0026703 49.323 0 0
|
| 79 |
+
163 0.18406 0.46489 0.19857 0.45888 0.00951 0.18697 -0.071549 -0.17274 0.11961 -0.049544 0.0007549 -0.0034914 64.901 0 0
|
| 80 |
+
36 0.227 -0.4455 0.21289 -0.45241 0.0083 0.15932 -0.070092 0.14308 0.099616 0.048801 0.00046374 0.0030139 52.279 0 0
|
| 81 |
+
164 0.19857 0.45888 0.21289 0.45241 0.00908 0.17406 -0.071629 -0.15864 0.11789 -0.053231 0.00072668 -0.0033279 63.066 0 0
|
| 82 |
+
37 0.21289 -0.45241 0.19857 -0.45888 0.00891 0.17647 -0.07262 0.16084 0.10561 0.047684 0.00051815 0.0032753 55.592 0 0
|
| 83 |
+
165 0.21289 0.45241 0.227 0.4455 0.0077 0.15242 -0.067054 -0.13687 0.087253 -0.042745 0.00031727 -0.0028213 47.267 0 0
|
| 84 |
+
38 0.19857 -0.45888 0.18406 -0.46489 0.00941 0.1892 -0.072404 0.1748 0.11972 0.049592 0.00074328 0.0035246 66.912 0 0
|
| 85 |
+
166 0.227 0.4455 0.24088 0.43815 0.00668 0.13216 -0.06184 -0.1168 0.084954 -0.044981 0.00036305 -0.0025411 52.144 0 0
|
| 86 |
+
39 0.18406 -0.46489 0.16937 -0.47044 0.01064 0.21736 -0.076832 0.20333 0.12854 0.048569 0.00081212 0.0039566 71.427 0 0
|
| 87 |
+
167 0.24088 0.43815 0.25452 0.43037 0.00643 0.12067 -0.059788 -0.10482 0.088144 -0.050276 0.00044539 -0.0024361 48.486 0 0
|
| 88 |
+
40 0.16937 -0.47044 0.15451 -0.47553 0.01112 0.22393 -0.072535 0.21186 0.13566 0.046446 0.00099149 0.0040572 75.425 0 0
|
| 89 |
+
168 0.25452 0.43037 0.26791 0.42216 0.00578 0.1105 -0.057735 -0.094214 0.073582 -0.045091 0.00024892 -0.0021881 41.631 0 0
|
| 90 |
+
41 0.15451 -0.47553 0.1395 -0.48015 0.01314 0.265 -0.077919 0.25328 0.15434 0.047482 0.0012004 0.0047242 84.402 0 0
|
| 91 |
+
169 0.26791 0.42216 0.28104 0.41354 0.00523 0.096878 -0.053188 -0.080972 0.065036 -0.042721 0.0001861 -0.0019429 37.871 0 0
|
| 92 |
+
42 0.1395 -0.48015 0.12434 -0.48429 0.01426 0.28605 -0.075482 0.27592 0.15979 0.043712 0.0013242 0.0050205 89.121 0 0
|
| 93 |
+
170 0.28104 0.41354 0.29389 0.40451 0.00482 0.086442 -0.049705 -0.070722 0.055391 -0.038929 8.9312e-05 -0.0017223 33.753 0 0
|
| 94 |
+
43 0.12434 -0.48429 0.10907 -0.48796 0.01579 0.32355 -0.075531 0.31461 0.18603 0.044662 0.0017357 0.0056432 108.11 0 0
|
| 95 |
+
171 0.29389 0.40451 0.30645 0.39508 0.00402 0.073891 -0.044365 -0.059089 0.04379 -0.032879 -9.0365e-06 -0.0014446 24.081 0 0
|
| 96 |
+
44 0.10907 -0.48796 0.093691 -0.49114 0.0163 0.33841 -0.068625 0.33138 0.18684 0.038693 0.0018569 0.0058129 106.51 0 0
|
| 97 |
+
172 0.30645 0.39508 0.31871 0.38526 0.00384 0.071852 -0.044925 -0.056076 0.045243 -0.036246 4.9886e-06 -0.0014501 24.929 0 0
|
| 98 |
+
45 0.093691 -0.49114 0.078217 -0.49384 0.01822 0.38101 -0.065507 0.37534 0.21127 0.036873 0.0022896 0.0064748 126.53 0 0
|
| 99 |
+
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| 103 |
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| 108 |
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| 110 |
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| 209 |
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128 -0.33066 0.37506 -0.31871 0.38526 0.11625 2.5875 1.6804 -1.9675 0.40217 0.34349 0.032712 -0.025509 674.04 0 0
|
CylinderKnMa/Kn0p38/simulation0830_Kn0p38Ma4p9/surf/Surf_300000.vtu
ADDED
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@@ -0,0 +1,38 @@
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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="400" NumberOfCells="200" >
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| 5 |
+
<PointData>
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| 6 |
+
</PointData>
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| 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" />
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| 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" />
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| 13 |
+
<DataArray type="Float64" Name="f_2[1]" format="appended" RangeMin="0.00148" RangeMax="0.22568" offset="4512" />
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| 14 |
+
<DataArray type="Float64" Name="f_2[2]" format="appended" RangeMin="0.026957" RangeMax="5.056" offset="6480" />
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| 15 |
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<DataArray type="Float64" Name="f_2[3]" format="appended" RangeMin="-0.077919" RangeMax="5.0554" offset="8536" />
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| 16 |
+
<DataArray type="Float64" Name="f_2[4]" format="appended" RangeMin="-2.113" RangeMax="2.1274" offset="10624" />
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| 17 |
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<DataArray type="Float64" Name="f_2[5]" format="appended" RangeMin="-4.3551e-05" RangeMax="0.46653" offset="12700" />
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| 18 |
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<DataArray type="Float64" Name="f_2[6]" format="appended" RangeMin="-0.43817" RangeMax="0.42247" offset="14800" />
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| 19 |
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<DataArray type="Float64" Name="f_2[7]" format="appended" RangeMin="-0.00066787" RangeMax="0.079417" offset="16916" />
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| 20 |
+
<DataArray type="Float64" Name="f_2[8]" format="appended" RangeMin="-0.026848" RangeMax="0.027222" offset="19060" />
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| 21 |
+
<DataArray type="Float64" Name="f_2[9]" format="appended" RangeMin="5.3545" RangeMax="1236.2" offset="21204" />
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| 22 |
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<DataArray type="Float64" Name="f_2[10]" format="appended" RangeMin="0" RangeMax="0" offset="22680" />
|
| 23 |
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<DataArray type="Float64" Name="f_2[11]" format="appended" RangeMin="0" RangeMax="0" offset="22732" />
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| 24 |
+
</CellData>
|
| 25 |
+
<Points>
|
| 26 |
+
<DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="0.49999998503" RangeMax="0.50000001255" offset="22784" />
|
| 27 |
+
</Points>
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| 28 |
+
<Cells>
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| 29 |
+
<DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="24112" />
|
| 30 |
+
<DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="25016" />
|
| 31 |
+
<DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="25508" />
|
| 32 |
+
</Cells>
|
| 33 |
+
</Piece>
|
| 34 |
+
</UnstructuredGrid>
|
| 35 |
+
<AppendedData encoding="base64">
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sJENWvC4Mio/WfpJ7dwGsvNUPTFUiIWTsPK6+IQa104X+n/JjwNSnBROzLuJ8hYJLCzEe1X/GbLRakIiO9eyXHv2JiLxt1BPlwYBSQska5jImTHNIk+mBVxBxclpBTDYF7QatggYTqYhxIdaqBrFwqOKMlKpDGk4tfR5uppwBkeT2DvnrmQhv7un9KS4bBzTJTel3ruPiW3sxrlIOzvLhSnJhlN25MKcyH82GvnuqnAqwYSpXaLqkEPLqerOt38LvoYMGd6SL8FB7aCXFvxgddpF+tAMlCFeM1VJm3cHrR7JdnwPv4lwlJ3V/8T18vMZvuAwh926d7goth9rGFka/VAWW+3xQs/CsRJja3x/b7djI5NrYjJxkg4/KjqiCTIOG8LYT1RAX6JNUGa2GzCxryck1CNAihcv51WLTG0ML4/FajPtN1Pu31uGhy/tfW8n14E5OSEoQGpArKt73Va8BP84JsxGXBLOy7V0aETIWRBh53YivPRmYiuVAWaXdKS2dAx+/9I3EVVysqCSv1hjm4lC37TuiBA908e1JYS+4qFfcfZEbxMOJGY5OnCEPNfGHriUa8DBLspaTOw+u+/iIPOR5B5UdzeFBfo2D9ZE9PCxPaBF2lOWBwC9nHQ8zCQkK6SlcZJ93pC4u4KK37dneVhku3CQYgyrNHFD9tW1vR3EwypfNMg7c3EhHTF824vQKp+wyqUZE8mUa04AEQtvMLl493giwV6kF1oOsue9t5806aFrxJ1AL4emSi1Ira/EpX9+F4V2DFkKQXltWNTzmhFcNvTkhVyHHbYw5Ws5Gu3KHaNcyNogzghIbnCvhsJHRdHhRBarH1llEV93Hq4kd/3RGl4F3TLdhsdo9ND0P0RRcdReo6y4KCbgD2t1f1J1/K0H51RXKz+SKkeQ0ddSEcfsb3i1cEq5oefhXITwzqfnTDwtgaZuY1bMiHyNR/AXKwwC5n2pGugmykKd+FekG+Ox93Z4N94OqSj6PM/FKu3l7nHsGPLsVpW7OsFCetsX8oDELfFa1KlNRGrno47JDKWDtoSUrUq9gzg6kmTAUuXs/bQsDl5/Ybyn4nASTqzdyOiiX8ETPZonprnhES2bRg67GYmjaJ8/8cgx2m8682UyJQiaf/rN0vGM07uzqpmG/aIb1JI0G9TnBhaJo64vEL77nMBdOOotmgZ4FwheCMFCY1BFg4Q+dOQL84FNKG6q56Y1CXSN3UVcvcMR7XsuWn4I9f228Pb75qTt081WZn1td8UzjPSl1xBm9zKXp99kOoC+RPrGq4DjixxdRkkj2GHbsoxVN2kH2n3GvXqY1hFdesVTkWmGnEX1kZ6oVXq9t3ScVbTbvw0Kri8Ljpo7hS6BzGTXOdN6H/6uTjIUJw0PbNlngaX/daIi8JcKLJsUE+v7P50/BjGU5n1fyoT+bUGqGA/JeCxhC5Pl78N2vv98B0Rs+a0YaKGjyWLgPdCv8CyrI+Co=AQAAAACAAABABgAA8gUAAA==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AQAAAACAAABABgAACwYAAA==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AQAAAACAAABABgAAAwYAAA==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AQAAAACAAABABgAAHwYAAA==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AQAAAACAAABABgAANQYAAA==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AQAAAACAAABABgAANAYAAA==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AQAAAACAAABABgAAPwQAAA==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AQAAAACAAABABgAAFQAAAA==eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAABABgAAFQAAAA==eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAADAEgAA0gMAAA==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AQAAAACAAABABgAAXwEAAA==eJwtxVFEHAAAANBKkpzkJEmSJMlJkiRJkiRJkiQnSXKSJEmSJEmSJEmSZGYmmUmSJEmSJEkyMzOTzCRJkmT20Xs/LybqXazjHO8EB5zoJAed7BSnOs3pznCms5ztHOc6zyHnu8CFLnKxS1zqMpe7wpWucrVrXOs617vBjW5ys1vc6rDb3O4Od7rLEXe7x73uc78HPOghD3vEox7zuCc86SlPe8aznvO8F7zoJS97xate8wd/9Cd/9ro3/MVfvektb3vHu97zvg986CMf+8SnPvO5L3zpK1/7m7/7h3/6l3/7xrf+47++870f/OgnP/vFr37zP0dFvxfjWMc53gkOONFJDjrZKU51mtOd4UxnOds5znWeQ853gQtd5GKXuNRlLneFK13late41nWud4Mb3eRmt7jVYbe53R3udJcj7naPe93nfg940EMe9ohHPeZxT3jSU572jGc95/9sSVRSAQAAAACAAADIAAAADAAAAA==eJxjZh4eAADsVAJZ
|
| 37 |
+
</AppendedData>
|
| 38 |
+
</VTKFile>
|
CylinderKnMa/Kn0p38/simulation0830_Kn0p38Ma4p9/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
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| 7 |
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| 8 |
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AQAAAACAAADgLgAA4SEAAA==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AgAAAACAAACAOwAABRMAABMJAAA=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|
| 26 |
+
</AppendedData>
|
| 27 |
+
</VTKFile>
|
CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/Lambda/Lambda_2_300000.vtu
ADDED
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@@ -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="606" NumberOfCells="500" >
|
| 5 |
+
<PointData>
|
| 6 |
+
</PointData>
|
| 7 |
+
<CellData>
|
| 8 |
+
<DataArray type="Float64" Name="id" format="appended" RangeMin="11501" RangeMax="12060" offset="0" />
|
| 9 |
+
<DataArray type="Float64" Name="xc" format="appended" RangeMin="-4.9522" RangeMax="4.5174" offset="948" />
|
| 10 |
+
<DataArray type="Float64" Name="yc" format="appended" RangeMin="4.5714" RangeMax="4.9524" offset="1992" />
|
| 11 |
+
<DataArray type="Float64" Name="c_6[1]" format="appended" RangeMin="0.024885" RangeMax="0.036454" offset="2124" />
|
| 12 |
+
<DataArray type="Float64" Name="c_6[2]" format="appended" RangeMin="0.26016" RangeMax="0.38111" offset="5568" />
|
| 13 |
+
</CellData>
|
| 14 |
+
<Points>
|
| 15 |
+
<DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="4.5238846488" RangeMax="7.0710678119" offset="8952" />
|
| 16 |
+
</Points>
|
| 17 |
+
<Cells>
|
| 18 |
+
<DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="11332" />
|
| 19 |
+
<DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="15036" />
|
| 20 |
+
<DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="16012" />
|
| 21 |
+
</Cells>
|
| 22 |
+
</Piece>
|
| 23 |
+
</UnstructuredGrid>
|
| 24 |
+
<AppendedData encoding="base64">
|
| 25 |
+
_AQAAAACAAACgDwAAtQIAAA==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AQAAAACAAACgDwAATwAAAA==eJy7vOexiKynkMPlUXqUHqUxaM6fC9I3rxqlR+lRGhut7FXdrM8jPEqP0qM0Ftp2duj81bmj9Cg9SmOji68LfXI8P0qP0qM0NhoAXjcwVw==AQAAAACAAACgDwAABAoAAA==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AQAAAACAAACgDwAA2AkAAA==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|
| 26 |
+
</AppendedData>
|
| 27 |
+
</VTKFile>
|
CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/Lambda/Lambda_300000.pvtu
ADDED
|
@@ -0,0 +1,21 @@
|
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|
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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="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/Kn0p38/simulation0831_Kn0p38Ma5p0/Lambda/Lambda_3_300000.vtu
ADDED
|
@@ -0,0 +1,27 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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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="96" NumberOfCells="75" >
|
| 5 |
+
<PointData>
|
| 6 |
+
</PointData>
|
| 7 |
+
<CellData>
|
| 8 |
+
<DataArray type="Float64" Name="id" format="appended" RangeMin="11601" RangeMax="12075" offset="0" />
|
| 9 |
+
<DataArray type="Float64" Name="xc" format="appended" RangeMin="4.613" RangeMax="5.9522" offset="208" />
|
| 10 |
+
<DataArray type="Float64" Name="yc" format="appended" RangeMin="4.5714" RangeMax="4.9524" offset="416" />
|
| 11 |
+
<DataArray type="Float64" Name="c_6[1]" format="appended" RangeMin="0.020319" RangeMax="0.036275" offset="512" />
|
| 12 |
+
<DataArray type="Float64" Name="c_6[2]" format="appended" RangeMin="0.21242" RangeMax="0.37924" offset="1348" />
|
| 13 |
+
</CellData>
|
| 14 |
+
<Points>
|
| 15 |
+
<DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="6.426979272" RangeMax="7.8102496759" offset="2180" />
|
| 16 |
+
</Points>
|
| 17 |
+
<Cells>
|
| 18 |
+
<DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="2596" />
|
| 19 |
+
<DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="3140" />
|
| 20 |
+
<DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="3388" />
|
| 21 |
+
</Cells>
|
| 22 |
+
</Piece>
|
| 23 |
+
</UnstructuredGrid>
|
| 24 |
+
<AppendedData encoding="base64">
|
| 25 |
+
_AQAAAACAAABYAgAAiQAAAA==eJwtx9s1AwEAANHpwzuVaCIIitkKEKIHBOki+hDx6AJn7/zcM1XDw/q4/x5HB/bk2dKzZ89ePHv1bOXZu2cbzz4823r26dmXZ9+e/fidt/F3Rwe259m+ZweeHXp25NnEs6lnJ56denbm2cyzc88uPLv0V/7asxvP5p7denbn2cKze//nL3yyhvI=AQAAAACAAABYAgAAiAAAAA==eJw7eGqh67ZiIYeMza+Kt14Vcvi0ISB7lrmww6yZICDs4Nj06PiM38IOZ+o99tfGijgUZ0x8W7NfxOFf6vcniYqiDkv9HIQTm0UdDHyWcbk9FXW4bvLewtVdzCHRKNRAa6WYA6f0vDhNbnGHyRIsYXy54g7WjL4tvOfFHQ6O2jus7QUAd63urQ==AQAAAACAAABYAgAANgAAAA==eJy7vOexiKynkMNlOtOcPxekb15Ff1rZq7pZn0eY7rTt7ND5q3PpTxdfF/rkeJ7+NADFJe2aAQAAAACAAABYAgAAYQIAAA==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AQAAAACAAACABAAAJQEAAA==eJw9zj1KwnEAh/Efzs3ewLGxMTCkGwReoE1q8QThBcLojeKPiiAkgiQEQUMvB5CWCFrcXBoCL5DP8Hyf6TM+rXq/ufNx3izbvhuX8cneTVw7vIuvj6p493gYv3fHcbs3iX/7D/HZaBbXH+fx9G0RH3w+xV+r57jz9xKX8hq3tv/7y4v8a/41/5p/zb/mX/Ov+df8a/41/5p/zb/mX/Ov+T/9ucq/5l/zr/nX/Gv+Nf+af82/5l/zr/nX/Gv+Nf+a/2p9m3/Nv+Zf86/51/xr/jX/mn/Nv+Zf86/51/xr/jX/y819/jX/mn/Nv+Zf86/51/xr/jX/mn/Nv+Zf86/51/yXMsi/5l/zr/nX/Gv+Nf+af82/5l/zr/nX/Gv+Nf/6H0+7Z2I=AQAAAACAAABgCQAAhgEAAA==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eJwtxRF0QgEAAMD2XhAEQfAhCIIgCIJgEARBEATBIAiCIAiCIBgEQRAEQRAEQRAMgiAYBEEQBINBEARBEATdyYVDbxFHHXPcgRNOOuW0M84657w/XXDRJZddcdU1f7nuhptuue2Ou+65728PPPTIY0889cxzL7z0ymv/eOOtd/713gcfffLZf/73xVfffPfDT4c+3oUdcdQxxx044aRTTjvjF05rIJU=AQAAAACAAABLAAAADAAAAA==eJzj5KQaAABkfQKk
|
| 26 |
+
</AppendedData>
|
| 27 |
+
</VTKFile>
|
CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/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/Kn0p38/simulation0831_Kn0p38Ma5p0/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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|
|
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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 0.38
|
| 13 |
+
variable Ma equal 5.0
|
| 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/Kn0p38/simulation0831_Kn0p38Ma5p0/cylinder.surf
ADDED
|
@@ -0,0 +1,410 @@
|
|
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|
|
|
|
|
|
|
|
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CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/gas.species
ADDED
|
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
| 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/Kn0p38/simulation0831_Kn0p38Ma5p0/gas.vhs
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 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/Kn0p38/simulation0831_Kn0p38Ma5p0/grid/Grid_0_300000.vtu
ADDED
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The diff for this file is too large to render.
See raw diff
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CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/grid/Grid_1_300000.vtu
ADDED
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|
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CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/grid/Grid_2_300000.vtu
ADDED
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|
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_AQAAAACAAACgDwAAtQIAAA==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AQAAAACAAACgDwAATwAAAA==eJy7vOexiKynkMPlUXqUHqUxaM6fC9I3rxqlR+lRGhut7FXdrM8jPEqP0qM0Ftp2duj81bmj9Cg9SmOji68LfXI8P0qP0qM0NhoAXjcwVw==AQAAAACAAACgDwAAsgYAAA==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AQAAAACAAACgDwAAhAoAAA==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AQAAAACAAACgDwAATgkAAA==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AQAAAACAAACgDwAA5w0AAA==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AQAAAACAAACgDwAA2g0AAA==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AQAAAACAAACgDwAAGwAAAA==eJztwTEBAAAAwqD1T20MH6AAAACAtwEPoAABAQAAAACAAACgDwAAGwAAAA==eJztwTEBAAAAwqD1T20MH6AAAACAtwEPoAABAQAAAACAAABoHAAA5wYAAA==eJxF1Hto1XUYx/EldmNZDMTKiopCCLLbGGV4dE2iWjAqWuLCkpL9UWSXRdiFhq2lbDblRIYVEf1TEVTIsJKmdqGCiiFi0QVMIs4fhRQJNsLI9+D9eQ4ceP33g+f7PO+2ttf3nvbZ1u6247/7/3w1/u6X7fF1+7bF73zyQrxgx9Z4wxvPx380x+KVIxvjT4eejRev3RBf/vZT8dyxx+If73sofv/m++LnLl0b3znvrvjKwyvjk6dvjX9+7+Z4x9br400PL49X37Yk7uzsjE+dvzg+eGRRPHnggnhs58J4zUvz4671p8ftq06JDy2ZEz/Q9c8efdbR3+PPPzwYP/jE/vicpV/GXxzbFT+y5934vA1vxF/1bIsfnTsWL9v8ZPziGffGfzR74xULropf3n52/Oe5J8QT3ft266U3vB7vf+Wu3TXbmSl9y+SBj2s+Ew2957JLltUbjcZzx3bGK0dacf+y05br/3ZdHL95dWN5fas/nrliXbzvjpF40Ytb4if2vxJPd7wVX3zLZLx+Ym/87TffxBe2/xA/dtNv8dcb/4rP/+JYfO2cE7v12gvbu2ueHfFHd58Z//r0efG81y6Kr5m6JL7n58vjzf92xR8sXBofWtITt6+6Me5a3xeveen2eGznQDx5YE188MhgfOr8B+LOzqF49W2Px5seHo5XffVMfPj70XiktSk+6+h4/O5JW+IVC5px2/F2NaZfmDXt0rRL0y5NuzTt0rRL0y5NuzTt0rRL0y5NuzTt0rRL0y5NuzTt0rRL0y5NuzTt0rRL0y5NuzTt0rRL0y5NuzTt0rRL0y5NuzTt0rRL0y5NuzTt0rRL0y5NuzTt0rRL0656u96YdmnapWmXpl2admnaVbOdmdK0q+Yz0dC0q95oNKZdtUutmHZp2qVpV32rP6ZdmnZp2qVpl6ZdmnZp2qVpl6ZdmnZp2qVpl6ZdmnbVPDti2qVpl6ZdmnZp2qVpl6ZdtXs9Me2qt+iLaVft9kBMu+oWBmPaVbczFNOuurXhmHZp2qVpV93CeEy7aiebMe1a99O2WdMuTbs07dK0S9MuTbs07dK0S9MuTbs07dK0S9MuTbs07dK0S9MuTbs07dK0S9MuTbs07dK0S9MuTbs07dK0S9MuTbs07dK0S9MuTbs07dK0S9MuTbs07dK0S9MuTbs07aq3641pl6ZdmnZp2qVpl6ZdNduZKU27aj4TDU276o1GY9pVu9SKaZemXZp21bf6Y9qlaZemXZp2adqlaZemXZp2adqlaZemXZp2adqlaVfNsyOmXZp2adqlaZemXZp2adpVu9cT0656i76YdtVuD8S0q25hMKZddTtDMe2qWxuOaZemXZp21S2Mx7SrdrIZ067XWttnTbs07dK0S9MuTbs07dK0S9MuTbs07dK0S9MuTbs07dK0S9MuTbs07dK0S9MuTbs07dK0S9MuTbs07dK0S9MuTbs07dK0S9MuTbs07dK0S9MuTbs07dK0S9MuTbs07dK0q96uN6ZdmnZp2qVpl6ZdmnbVbGemNO2q+Uw0NO2qNxqNaVftUiumXZp2adpV3+qPaZemXZp2adqlaZemXZp2adqlaZemXZp2adqlaZemXTXPjph2adqlaZemXZp2adqlaVftXk9Mu+ot+mLaVbs9ENOuuoXBmHbV7QzFtKtubTimXZp2adpVtzAe067ayWZMu6b/fnXWtEvTLk27NO3StEvTLk27NO3StEvTLk27NO3StEvTLk27NO3StEvTLk27NO3StEvTLk27NO3StEvTLk27NO3StEvTLk27NO3StEvTLk27NO3StEvTLk27NO3StEvTLk276u16Y9qlaZemXZp2adqlaVfNdmZK066az0RD0656o9GYdtUutWLapWmXpl31rf6YdmnapWmXpl2admnapWmXpl2admnapWmXpl2admnaVfPsiGmXpl2admnapWmXpl2adtXu9cS0q96iL6ZdtdsDMe2qWxiMaVfdzlBMu+rWhmPapWmXpl11C+Mx7aqdbMa06/h/1rRL0y5NuzTt0rRL0y5NuzTt0rRL0y5NuzTt0rRL0y5NuzTt0rRL0y5NuzTt0rRL0y5NuzTt0rRL0y5NuzTt0rRL0y5NuzTt0rRL0y5NuzTt0rRL0y5NuzTt0rRL0y5Nu+rtemPapWmXpl2admnapWlXzXZmStOums9EQ9OueqPRmHbVLrVi2qVpl6Zd9a3+mHZp2qVpl6ZdmnZp2qVpl6ZdmnZp2qVpl6ZdmnZp2lXz7Ihpl6ZdmnZp2qVpl6ZdmnbV7vXEtKveoi+mXbXbAzHtqlsYjGlX3c5QTLvq1oZj2qVpl6ZddQvjMe2qnWzG/wNxdAkZAQAAAACAAACAPgAAxwoAAA==eJxd21UTAEQZRmF26e7u7u7u7m5QUUBAQEGQ7g6DxgADDEJJk7IRpEUJKRNUFGkU8MJ9Lr53b96ZM+cPnG9mJ5jg/6+N3X/sR4L3sQeEh0849sDw8InGfjQ8fOKxB4WHTzL24PDwScceEh4+2diPhYdPPvbQ8PApxh4WHj7l2MPDw6ca+/Hw8KnHfiI8fJqxR4SHTzv2yPDw6cZ+Mjx8+rFHhYfPMPbo8PAZx34qPHymsceEh8889tjw8FnGHhcePuvY48PDZxt7Qnj47GNPDA+fY+xJ4eFzjj05PHyusaeEh8899tTw8HnGnhYePu/Y08PD5xt7Rnj4/GPPDA9fYOxZ4eELjj07PHyhseeEhy889tzw8EXGnhcevujY88PDFxt7QXj44mMvDA9fYuynw8OXHPuZ8PClxn42PHzpsZ8LD19m7EXh4cuOvTg8fLmxl4SHLz/20vDwFcZeFh6+4tjLw8NXGntFePjKY68MD19l7OfDw1cd+4Xw8NXGfjE8fPWxXwoPX2PsVeHha469Ojx8rbFfDg9fe+xXwsPXGfvV8PB1x34tPHy9sdeEh68/9trw8A3Gfj08fMOx3wgP32jsN8PDNx77rfDwTcZeFx6+6djrw8M3G3tDePjmY28MD99i7LfDw7cc+53w8K3G3hQevvXYm8PDtxl7S3j4tmNvDQ/fbuxt4eHbj709PHyHsd8ND99x7PfCw3ca+/3w8J3H/iA8fJexPwwP33Xsj8LDdxt7R3j47mPvDA/fY+xd4eF7jr07PHyvsfeEh+899sfh4fuM/Ul4+L5jfxoe/oGxPwsP/+DYn4eHf2jsL8LD9xv7y/DwD4+9NzydoSfuG/ur4Hri/vBwPfHr8HA98UB4uJ54MDxcTzwUHq4nHg4P1xOPhIfriUfDw/XEY+HheuI34eF64vHwcD3x2/BwPfG78HA98UR4uJ54MjxcTzwVHq4nng4P1xO/Dw/XE8+Eh+uJZ8PD9cRz4eF64vnwcD3xQni4nvhDeLie+GN4+Mlj/xQerif+HB6uJ/4SHq4n/hoerideDA/XEy+Fh+uJv4WH64m/h4friX+Eh+uJl8PD9cQ/w8P1xL/Cw/XEK+HheuLf4eF64tXwcD3xWni4nng9PFxPvBEerifeDA/XE2+Fh+uJt8PD9cQ74eF64j/h4Xriv+HheuLd8HA98V54uJ54PzxcTziIvR9cT7RWPVxP9FY9XE9M2KqH64mJWvXwq8dO3KqH64lJWvVwPTFpqx6uJyZr1cP1xOSteriemKJVD9cTU7bq4XpiqlY9XE9M3aqH64lpWvVwPTFtqx6uJ6Zr1cP1xPSteriemKFVD9cTM7bq4XpiplY9XE/M3KqH64lZWvVwPTFrqx6uJ2Zr1cP1xOyteriemKNVD9cTc7bq4XpirlY9XE/M3aqH64l5WvVwPTFvqx6uJ+Zr1cP1xPyterieWKBVD9cTC7bq4XpioVY9/O6xC7fq4XpikVY9XE8s2qqH64nFWvVwPbF4qx6uJ5Zo1cP1xJKterieWKpVD9cTS7fq4bpjmVY9naEnlht82Va5nli+VQ/XEyu06uF6YsVWPVxPrNSqh+uJlVv1cD2xSqseridWbdXD9cRqrXq4nli9VQ/XE2u06uF6Ys1WPVxPrNWqh+uJtVv1cD2xTqserifWbdXD9cR6rXq4nli/VQ/XExu06uF6YsNWPVxPbNSqhz83duNWPfz5sZu06uF6YtNWPVxPbNaqh+uJzVv1cD2xRaserie2bNXD9cRWrXq4nti6VQ/XE9u06uF6YttWPVxPbNeqh+uJ7Vv1cD2xQ6serid2bNXD9cROrXq4nti5VQ/XE7u06uF6YtdWPVxP7Naqh+uJ3Vv1cD2xR6serif2bNXD9cRerXq4nti7VQ/XE/u06uF6Yt9WPVxPfKBVD9cTH2zVw/XEh1r1cD2xX6seric+3KqH64mPtOrhemL/8HA9cUB4uJ44MDxcT3w0PFxPHBQericODg/XE4eEh+uJj4WH64lDw8P1xGHh4Xri8PBwPfHx8HA98YnwcD1xRHi4njgyPFxPfDI8XE8cFR6uJ44OD9cTnwoP1xPHhIfriWPDw/XEceHheuL48HA9cUJ4uJ44MTxcT5wUHq4nTg4P1xOnhIfriVPDw/XEaeHheuL08HA9cUZ4uJ44MzxcT5wVHq4nzg4P1xPnhIfriXPDw/XEeeHheuL88HA9cUF4uJ64MDxcT3w6PFxPfCY8XE98NjxcT3wuPFx3XBSeztATl4y9OLieuDQ8XE9cFh6uJy4PD9cTV4SH64krw8P1xOfDw/XEF8LD9cQXw8P1xJfCw/XEVeHheuLq8HA98eXwcD3xlfBwPfHV8HA98bXwcD1xTXi4nrg2PFxPfD08XE98IzxcT3wzPFxPfCs8XE9cFx6uJ64PD9cTN4SH64kbw8P1xLfDw/XEd8LD9cRN4eF64ubwcD1xS3i4nrg1PFxP3BYeriduDw/XE98ND9cT3wsP1xPfDw/XEz8ID9cTPwwP1xM/Cg/XE3eEh+uJO8PD9cRd4eF64u7wcD1xT3i4nvhxeLie+El4uJ74aXi4nvhZeLie+Hl4uJ74RXi4nvhleLieuDc8XE/8KjxcT9wXHq4n7g8P1xO/Dg/XEw+Eh+uJB8PD9cRD4eF64uHwcD3xSHi4nng0PFxPPBYerid+Ex6uJx4PD9cTvw0P1xO/Cw/XE0+Eh+uJJ8PD9cRT4eF64unwcD3x+/BwPfFMeLieeDY8XE88Fx6uJ54PD9cTL4SH64k/hIfriT+Gh+uJP4WH64k/h4frib+Eh+uJv4aH64kXw8P1xEvh4Xrib+HheuLv4eF64h/h4Xri5fBwPfHP8HA98a/wcD3xSni4nvh3eLieeDU8XE+8Fh6uJ14PD9cTb4SH64k3w8N1x1vh6Qw98c7Yt4Prif+Eh+uJ/4aH64l3w8P1xHvh4Xri/fBwPeFDyvvB9UTr1cP1RO/Vw/XEhL16uJ6YqFcP1xMT9+rhemKSXj1cT0zaq4fricl69XA9MXmvHq4npujVw/XElL16uJ6YqlcP1xNT9+rhemKaXj1cT0zbq4friel69XA9MX2vHq4nZujVw/XEjL16uJ6YqVcP1xMz9+rhemKWXj1cT8zaq4fridl69XA9MXuvHq4n5ujVw/XEnL16uJ6Yq1cP1xNz9+rhemKeXj1cT8zbq4frifl69XA9MX+vHq4nFujVw/XEgr16uJ5YqFcP1xML9+rhemKRXj1cTyzaq4fricV69XA9sXivHq4nlujVw/XEkr16uJ5YqlcP1xNL9+rhemKZXj1cTyzbq4frieV69XA9sXyvHq4nVujVw/XEir16uJ5YqVcP1xMr9+rhemKVXj1cT6zaq4fridV69XA9sXqvHq4n1ujVw/XEmr16uJ5Yq1cP1xNr9+rhemKdXj1cT6zbq4frifV69XA9sX6vHq4nNujVw/XEhr16uJ7YqFcP1xMb9+rhemKTXj1cT2zaq4fric169XA9sXmvHq4ntujVw/XElr16uJ7YqlcP1xNb9+rhemKbXj1cT2zbq4frie169XA9sX2vHq4ndujVw/XEjr16uJ7YqVcP1xM79+rhemKXXj1cT+zaq4frid169XA9sXuvHq4n9ujVw/XEnr16uJ7Yq1cP1x179+r9Dyrg49M=AQAAAACAAACgDwAAyAIAAA==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AQAAAACAAAD0AQAADgAAAA==eJzj5BwFIw0AADZFEZU=
|
| 34 |
+
</AppendedData>
|
| 35 |
+
</VTKFile>
|
CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/grid/Grid_300000.pvtu
ADDED
|
@@ -0,0 +1,29 @@
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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/Kn0p38/simulation0831_Kn0p38Ma5p0/grid/Grid_3_300000.vtu
ADDED
|
@@ -0,0 +1,35 @@
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|
|
|
|
|
| 1 |
+
<?xml version="1.0"?>
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|
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| 6 |
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|
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|
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|
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|
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|
| 34 |
+
</AppendedData>
|
| 35 |
+
</VTKFile>
|
CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/grid/final-grid.dat
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/log.sparta
ADDED
|
@@ -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 0.38
|
| 17 |
+
variable Ma equal 5.0
|
| 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 0.38*${L}
|
| 23 |
+
variable mfp equal 0.38*1
|
| 24 |
+
variable cpmfp equal 4
|
| 25 |
+
variable nden equal 1.0/sqrt(2.0)/${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}*${Kn})
|
| 29 |
+
variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.38/${cpmfp}*${Kn})
|
| 30 |
+
variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.38/4*${Kn})
|
| 31 |
+
variable nden equal 1.0/sqrt(2.0)/3.1415926536/4.17e-10/4.17e-10/(0.38/4*0.38)
|
| 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*${sos}
|
| 38 |
+
variable vo equal 5*307.815564238681
|
| 39 |
+
variable vx equal ${vo}*cos(${theta}*2*PI/360)
|
| 40 |
+
variable vx equal 1539.07782119341*cos(${theta}*2*PI/360)
|
| 41 |
+
variable vx equal 1539.07782119341*cos(0*2*PI/360)
|
| 42 |
+
variable vy equal ${vo}*sin(${theta}*2*PI/360)
|
| 43 |
+
variable vy equal 1539.07782119341*sin(${theta}*2*PI/360)
|
| 44 |
+
variable vy equal 1539.07782119341*sin(0*2*PI/360)
|
| 45 |
+
variable ppc equal 30
|
| 46 |
+
variable xncells equal (${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)/0.38*${cpmfp}
|
| 50 |
+
variable xncells equal (6--5)/0.38*4
|
| 51 |
+
variable yncells equal (${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)/0.38*${cpmfp}
|
| 55 |
+
variable yncells equal (5--5)/0.38*4
|
| 56 |
+
variable Fnum equal ${nden}*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
|
| 57 |
+
variable Fnum equal 3.58555028535087e+19*(${xmax}-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
|
| 58 |
+
variable Fnum equal 3.58555028535087e+19*(6-${xmin})*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
|
| 59 |
+
variable Fnum equal 3.58555028535087e+19*(6--5)*(${ymax}-${ymin})/${ppc}/${xncells}/${yncells}
|
| 60 |
+
variable Fnum equal 3.58555028535087e+19*(6--5)*(5-${ymin})/${ppc}/${xncells}/${yncells}
|
| 61 |
+
variable Fnum equal 3.58555028535087e+19*(6--5)*(5--5)/${ppc}/${xncells}/${yncells}
|
| 62 |
+
variable Fnum equal 3.58555028535087e+19*(6--5)*(5--5)/30/${xncells}/${yncells}
|
| 63 |
+
variable Fnum equal 3.58555028535087e+19*(6--5)*(5--5)/30/115.789473684211/${yncells}
|
| 64 |
+
variable Fnum equal 3.58555028535087e+19*(6--5)*(5--5)/30/115.789473684211/105.263157894737
|
| 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}/${xncells}/10/4
|
| 68 |
+
variable tstep equal (--5+6)/1539.07782119341/${xncells}/10/4
|
| 69 |
+
variable tstep equal (--5+6)/1539.07782119341/115.789473684211/10/4
|
| 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 3.58555028535087e+19
|
| 81 |
+
global fnum ${Fnum}
|
| 82 |
+
global fnum 1.07865304417638e+16
|
| 83 |
+
timestep ${tstep}
|
| 84 |
+
timestep 1.54313184641853e-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 115.789473684211 ${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 115.789473684211 105.263157894737 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 53265 child grid cells
|
| 100 |
+
CPU time = 0.0887773 secs
|
| 101 |
+
create/ghost percent = 1.2613 98.7387
|
| 102 |
+
balance_grid rcb cell
|
| 103 |
+
Balance grid migrated 53160 cells
|
| 104 |
+
CPU time = 0.0816815 secs
|
| 105 |
+
reassign/sort/migrate/ghost percent = 62.2038 0.0346345 9.31674 28.4448
|
| 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 1539.07782119341 ${vy} 0.0 temp ${To}
|
| 110 |
+
mixture air Ar vstream 1539.07782119341 0 0.0 temp ${To}
|
| 111 |
+
mixture air Ar vstream 1539.07782119341 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 |
+
336 0 = cells overlapping surfs, overlap cells with unmarked corner pts
|
| 121 |
+
47589 5340 336 = cells outside/inside/overlapping surfs
|
| 122 |
+
336 = surf cells with 1,2,etc splits
|
| 123 |
+
109.215 109.215 = cell-wise and global flow volume
|
| 124 |
+
CPU time = 0.104141 secs
|
| 125 |
+
read/check/sort/surf2grid/ghost/inout/particle percent = 33.2013 21.1166 2.61309 21.382 21.687 5.51421 0.144198
|
| 126 |
+
surf2grid time = 0.0222675 secs
|
| 127 |
+
map/comm1/comm2/comm3/comm4/split percent = 13.2586 24.4611 5.2827 1.82973 12.0089 6.99823
|
| 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 988 cells
|
| 133 |
+
CPU time = 0.0372722 secs
|
| 134 |
+
reassign/sort/migrate/ghost percent = 8.93933 0.0860696 24.4898 66.4848
|
| 135 |
+
create_particles air n 0
|
| 136 |
+
WARNING: Created unexpected # of particles: 363039 versus 363040 (../create_particles.cpp:346)
|
| 137 |
+
Created 363039 particles
|
| 138 |
+
CPU time = 0.0117585 secs
|
| 139 |
+
stats 10000
|
| 140 |
+
stats_style step cpu np nattempt ncoll nscoll npave nscollave
|
| 141 |
+
run 200000
|
| 142 |
+
Memory usage per proc in Mbytes:
|
| 143 |
+
particles (ave,min,max) = 1.6084 0 1.6875
|
| 144 |
+
grid (ave,min,max) = 2.88342 1.51379 4.32629
|
| 145 |
+
surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
|
| 146 |
+
total (ave,min,max) = 4.51242 3.22189 6.03439
|
| 147 |
+
Step CPU Np Natt Ncoll Nscoll Npave Nscollave
|
| 148 |
+
0 0 363039 0 0 0 0 0
|
| 149 |
+
10000 10.715744 405617 5510 4808 11 385262.8 13.6933
|
| 150 |
+
20000 23.168004 406526 5494 4832 8 396037.64 13.8213
|
| 151 |
+
30000 34.742759 406506 5603 4881 13 399455.81 13.8431
|
| 152 |
+
40000 46.305382 407136 5527 4763 14 401395.18 13.873825
|
| 153 |
+
50000 57.474304 406547 5541 4820 20 402487.44 13.88534
|
| 154 |
+
60000 69.947566 406562 5590 4890 18 403169.46 13.878167
|
| 155 |
+
70000 83.886985 406586 5475 4788 20 403623.17 13.869243
|
| 156 |
+
80000 95.520532 407136 5592 4877 10 404046.62 13.883325
|
| 157 |
+
90000 107.00026 406709 5670 4937 13 404372.86 13.885833
|
| 158 |
+
100000 118.2772 406496 5526 4800 10 404636.21 13.88519
|
| 159 |
+
110000 130.85421 407303 5599 4895 12 404862.84 13.900064
|
| 160 |
+
120000 143.13501 406638 5490 4779 14 405066.91 13.898433
|
| 161 |
+
130000 155.27139 406175 5625 4946 13 405164.87 13.896569
|
| 162 |
+
140000 166.88632 406472 5590 4892 12 405262.38 13.900671
|
| 163 |
+
150000 178.1726 406343 5459 4784 14 405381.62 13.902693
|
| 164 |
+
160000 190.55526 406026 5606 4867 17 405468.44 13.90325
|
| 165 |
+
170000 202.94851 405824 5558 4848 13 405525.67 13.905
|
| 166 |
+
180000 214.41525 407332 5614 4881 15 405583.29 13.903411
|
| 167 |
+
190000 225.92802 406561 5486 4767 11 405629.99 13.903253
|
| 168 |
+
200000 237.06025 407497 5634 4936 10 405697.67 13.905595
|
| 169 |
+
Loop time of 237.061 on 128 procs for 200000 steps with 407497 particles
|
| 170 |
+
|
| 171 |
+
MPI task timing breakdown:
|
| 172 |
+
Section | min time | avg time | max time |%varavg| %total
|
| 173 |
+
---------------------------------------------------------------
|
| 174 |
+
Move | 0.02208 | 10.034 | 64.466 | 417.3 | 4.23
|
| 175 |
+
Coll | 0.27641 | 8.1183 | 70.279 | 390.7 | 3.42
|
| 176 |
+
Sort | 0.092778 | 1.6589 | 12.12 | 173.3 | 0.70
|
| 177 |
+
Comm | 56.946 | 90.071 | 100.8 | 90.5 | 37.99
|
| 178 |
+
Modify | 0.017966 | 0.1073 | 2.0342 | 92.1 | 0.05
|
| 179 |
+
Output | 0.0052381 | 0.0091026 | 0.011423 | 0.9 | 0.00
|
| 180 |
+
Other | | 127.1 | | | 53.60
|
| 181 |
+
|
| 182 |
+
Particle moves = 81139534856 (81.1B)
|
| 183 |
+
Cells touched = 84776043676 (84.8B)
|
| 184 |
+
Particle comms = 186355958 (186M)
|
| 185 |
+
Boundary collides = 0 (0K)
|
| 186 |
+
Boundary exits = 17891659 (17.9M)
|
| 187 |
+
SurfColl checks = 171494442 (171M)
|
| 188 |
+
SurfColl occurs = 2781119 (2.78M)
|
| 189 |
+
Surf reactions = 0 (0K)
|
| 190 |
+
Collide attempts = 1273306800 (1.27B)
|
| 191 |
+
Collide occurs = 999557561 (1e+03M)
|
| 192 |
+
Reactions = 0 (0K)
|
| 193 |
+
Particles stuck = 0
|
| 194 |
+
Axisymm bad moves = 0
|
| 195 |
+
|
| 196 |
+
Particle-moves/CPUsec/proc: 2.67401e+06
|
| 197 |
+
Particle-moves/step: 405698
|
| 198 |
+
Cell-touches/particle/step: 1.04482
|
| 199 |
+
Particle comm iterations/step: 1
|
| 200 |
+
Particle fraction communicated: 0.00229673
|
| 201 |
+
Particle fraction colliding with boundary: 0
|
| 202 |
+
Particle fraction exiting boundary: 0.000220505
|
| 203 |
+
Surface-checks/particle/step: 0.00211357
|
| 204 |
+
Surface-collisions/particle/step: 3.42758e-05
|
| 205 |
+
Surf-reactions/particle/step: 0
|
| 206 |
+
Collision-attempts/particle/step: 0.0156928
|
| 207 |
+
Collisions/particle/step: 0.012319
|
| 208 |
+
Reactions/particle/step: 0
|
| 209 |
+
|
| 210 |
+
Particles: 3183.57 ave 22143 max 0 min
|
| 211 |
+
Histogram: 84 16 5 11 2 6 0 1 1 2
|
| 212 |
+
Cells: 416.133 ave 417 max 415 min
|
| 213 |
+
Histogram: 1 0 0 0 0 109 0 0 0 18
|
| 214 |
+
GhostCell: 10796.4 ave 19812 max 593 min
|
| 215 |
+
Histogram: 21 9 14 8 17 3 6 4 16 30
|
| 216 |
+
EmptyCell: 74.8203 ave 218 max 0 min
|
| 217 |
+
Histogram: 40 1 16 7 26 15 8 11 2 2
|
| 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) = 1.66113 0 3.375
|
| 246 |
+
grid (ave,min,max) = 2.88342 1.51379 4.32629
|
| 247 |
+
surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
|
| 248 |
+
total (ave,min,max) = 4.70511 3.36171 6.17471
|
| 249 |
+
Step CPU Np Natt Ncoll Nscoll Npave Nscollave
|
| 250 |
+
200000 0 407497 5634 4936 0 0 0
|
| 251 |
+
210000 22.379207 406730 5448 4790 15 406845.44 13.9434
|
| 252 |
+
220000 42.885702 405896 5391 4715 24 406769.45 13.9144
|
| 253 |
+
230000 63.625546 406561 5563 4850 10 406698.04 13.912067
|
| 254 |
+
240000 85.919824 406973 5574 4875 15 406690.64 13.91015
|
| 255 |
+
250000 106.83458 407413 5582 4921 8 406727.51 13.93164
|
| 256 |
+
260000 127.35024 406400 5549 4863 12 406771.89 13.934533
|
| 257 |
+
270000 149.63751 406952 5568 4844 17 406803.47 13.935743
|
| 258 |
+
280000 170.36821 406540 5489 4820 7 406826.88 13.936775
|
| 259 |
+
290000 190.77407 406410 5621 4890 18 406800.76 13.9278
|
| 260 |
+
300000 212.84209 406296 5464 4766 13 406775.46 13.92883
|
| 261 |
+
Loop time of 212.842 on 128 procs for 100000 steps with 406296 particles
|
| 262 |
+
|
| 263 |
+
MPI task timing breakdown:
|
| 264 |
+
Section | min time | avg time | max time |%varavg| %total
|
| 265 |
+
---------------------------------------------------------------
|
| 266 |
+
Move | 0.01142 | 5.0602 | 32.365 | 294.9 | 2.38
|
| 267 |
+
Coll | 0.13828 | 4.1093 | 36.803 | 280.9 | 1.93
|
| 268 |
+
Sort | 0.052136 | 0.84212 | 5.9037 | 122.0 | 0.40
|
| 269 |
+
Comm | 32.99 | 50.057 | 55.902 | 62.5 | 23.52
|
| 270 |
+
Modify | 1.9345 | 13.854 | 85.417 | 449.6 | 6.51
|
| 271 |
+
Output | 0.032275 | 0.033744 | 0.036344 | 0.5 | 0.02
|
| 272 |
+
Other | | 138.9 | | | 65.25
|
| 273 |
+
|
| 274 |
+
Particle moves = 40677545625 (40.7B)
|
| 275 |
+
Cells touched = 42499664707 (42.5B)
|
| 276 |
+
Particle comms = 93356457 (93.4M)
|
| 277 |
+
Boundary collides = 0 (0K)
|
| 278 |
+
Boundary exits = 8967523 (8.97M)
|
| 279 |
+
SurfColl checks = 85776106 (85.8M)
|
| 280 |
+
SurfColl occurs = 1392883 (1.39M)
|
| 281 |
+
Surf reactions = 0 (0K)
|
| 282 |
+
Collide attempts = 641246687 (641M)
|
| 283 |
+
Collide occurs = 503364128 (503M)
|
| 284 |
+
Reactions = 0 (0K)
|
| 285 |
+
Particles stuck = 0
|
| 286 |
+
Axisymm bad moves = 0
|
| 287 |
+
|
| 288 |
+
Particle-moves/CPUsec/proc: 1.49309e+06
|
| 289 |
+
Particle-moves/step: 406775
|
| 290 |
+
Cell-touches/particle/step: 1.04479
|
| 291 |
+
Particle comm iterations/step: 1
|
| 292 |
+
Particle fraction communicated: 0.00229504
|
| 293 |
+
Particle fraction colliding with boundary: 0
|
| 294 |
+
Particle fraction exiting boundary: 0.000220454
|
| 295 |
+
Surface-checks/particle/step: 0.00210868
|
| 296 |
+
Surface-collisions/particle/step: 3.42421e-05
|
| 297 |
+
Surf-reactions/particle/step: 0
|
| 298 |
+
Collision-attempts/particle/step: 0.0157641
|
| 299 |
+
Collisions/particle/step: 0.0123745
|
| 300 |
+
Reactions/particle/step: 0
|
| 301 |
+
|
| 302 |
+
Particles: 3174.19 ave 22221 max 0 min
|
| 303 |
+
Histogram: 84 16 6 10 2 6 0 2 0 2
|
| 304 |
+
Cells: 416.133 ave 417 max 415 min
|
| 305 |
+
Histogram: 1 0 0 0 0 109 0 0 0 18
|
| 306 |
+
GhostCell: 10796.4 ave 19812 max 593 min
|
| 307 |
+
Histogram: 21 9 14 8 17 3 6 4 16 30
|
| 308 |
+
EmptyCell: 74.8203 ave 218 max 0 min
|
| 309 |
+
Histogram: 40 1 16 7 26 15 8 11 2 2
|
| 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 = 53265
|
| 316 |
+
CPU time = 0.00781818 secs
|
| 317 |
+
write_surf surf/geom.surf
|
| 318 |
+
surf elements = 200
|
| 319 |
+
CPU time = 0.0017339 secs
|
CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/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/Kn0p38/simulation0831_Kn0p38Ma5p0/output/grid.300000.dat
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/output/lambdakn.300000.dat
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/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 0.00176 0.036549 -0.036544 0.00057409 1.8282e-05 0.0011638 -0.00057373 2.7297e-05 8.0155 0 0
|
| 11 |
+
129 -0.31871 0.38526 -0.30645 0.39508 0.11401 2.6161 1.6357 -2.0417 0.4327 0.34666 0.032489 -0.026625 683.24 0 0
|
| 12 |
+
2 0.49975 -0.015705 0.49901 -0.031395 0.00187 0.037891 -0.037848 0.0017849 0.00011285 0.0023929 -0.00059273 6.5622e-05 8.467 0 0
|
| 13 |
+
130 -0.30645 0.39508 -0.29389 0.40451 0.10669 2.4438 1.4673 -1.9543 0.4422 0.33201 0.029993 -0.025481 640.54 0 0
|
| 14 |
+
3 0.49901 -0.031395 0.49778 -0.047054 0.00182 0.038604 -0.038485 0.0030288 -0.00010518 -0.0013364 -0.00060615 2.6583e-05 7.805 0 0
|
| 15 |
+
131 -0.29389 0.40451 -0.28104 0.41354 0.1037 2.3651 1.3599 -1.935 0.44416 0.31216 0.028337 -0.02549 630.75 0 0
|
| 16 |
+
4 0.49778 -0.047054 0.49606 -0.062667 0.00171 0.035129 -0.034917 0.0038548 -0.00016271 -0.0014738 -0.000551 3.74e-05 7.7968 0 0
|
| 17 |
+
132 -0.28104 0.41354 -0.26791 0.42216 0.0992 2.2668 1.2445 -1.8946 0.44888 0.29486 0.026599 -0.025128 620.27 0 0
|
| 18 |
+
5 0.49606 -0.062667 0.49384 -0.078217 0.00188 0.039919 -0.039521 0.0056247 0.00076094 0.0053467 -0.00060882 0.00017233 7.9681 0 0
|
| 19 |
+
133 -0.26791 0.42216 -0.25452 0.43037 0.09171 2.1104 1.1027 -1.7994 0.45953 0.2816 0.024538 -0.02384 594.02 0 0
|
| 20 |
+
6 0.49384 -0.078217 0.49114 -0.093691 0.00186 0.036495 -0.035952 0.0062746 -0.00014637 -0.00083867 -0.00056701 8.5384e-05 8.1065 0 0
|
| 21 |
+
134 -0.25452 0.43037 -0.24088 0.43815 0.08685 1.9641 0.97313 -1.7061 0.44428 0.25341 0.022264 -0.022818 526.36 0 0
|
| 22 |
+
7 0.49114 -0.093691 0.48796 -0.10907 0.00177 0.035571 -0.034832 0.0072133 0.00087959 0.0042474 -0.00053329 0.00018002 6.1365 0 0
|
| 23 |
+
135 -0.24088 0.43815 -0.227 0.4455 0.0817 1.8499 0.86561 -1.6349 0.45047 0.23851 0.020672 -0.021933 503.91 0 0
|
| 24 |
+
8 0.48796 -0.10907 0.48429 -0.12434 0.00179 0.036393 -0.035387 0.0084957 -0.00032581 -0.0013571 -0.00056095 0.00011213 8.7396 0 0
|
| 25 |
+
136 -0.227 0.4455 -0.21289 0.45241 0.07679 1.7476 0.76882 -1.5694 0.4306 0.21095 0.01884 -0.021337 473.66 0 0
|
| 26 |
+
9 0.48429 -0.12434 0.48015 -0.1395 0.00153 0.031612 -0.030492 0.0083416 0.00011891 0.00043465 -0.00047708 0.00013785 7.2184 0 0
|
| 27 |
+
137 -0.21289 0.45241 -0.19857 0.45888 0.07407 1.686 0.6938 -1.5366 0.4594 0.20743 0.018114 -0.020878 479.72 0 0
|
| 28 |
+
10 0.48015 -0.1395 0.47553 -0.15451 0.00169 0.03575 -0.03417 0.010512 0.0010761 0.0034979 -0.00051982 0.00022006 6.7259 0 0
|
| 29 |
+
138 -0.19857 0.45888 -0.18406 0.46489 0.06937 1.5802 0.60473 -1.4599 0.44636 0.18489 0.01651 -0.020028 447 0 0
|
| 30 |
+
11 0.47553 -0.15451 0.47044 -0.16937 0.00152 0.031006 -0.029334 0.010043 0.00034653 0.0010121 -0.00045532 0.00017365 7.6508 0 0
|
| 31 |
+
139 -0.18406 0.46489 -0.16937 0.47044 0.06485 1.4667 0.51843 -1.372 0.43662 0.16499 0.015001 -0.018959 419.53 0 0
|
| 32 |
+
12 0.47044 -0.16937 0.46489 -0.18406 0.00193 0.036979 -0.034592 0.013071 0.0025781 0.0068228 -0.00050285 0.00031248 8.0853 0 0
|
| 33 |
+
140 -0.16937 0.47044 -0.15451 0.47553 0.06081 1.3801 0.44704 -1.3057 0.43613 0.14932 0.013872 -0.018164 402.35 0 0
|
| 34 |
+
13 0.46489 -0.18406 0.45888 -0.19857 0.00132 0.025474 -0.023535 0.0097487 0.0022817 0.0055086 -0.00033384 0.00023965 5.3107 0 0
|
| 35 |
+
141 -0.15451 0.47553 -0.1395 0.48015 0.05808 1.3157 0.38687 -1.2575 0.44103 0.13568 0.013004 -0.017621 382.19 0 0
|
| 36 |
+
14 0.45888 -0.19857 0.45241 -0.21289 0.00148 0.02858 -0.026048 0.011761 0.0023838 0.0052795 -0.00037171 0.00026767 7.3374 0 0
|
| 37 |
+
142 -0.1395 0.48015 -0.12434 0.48429 0.05274 1.1795 0.31123 -1.1376 0.39403 0.1078 0.011078 -0.016176 344.3 0 0
|
| 38 |
+
15 0.45241 -0.21289 0.4455 -0.227 0.00158 0.028641 -0.025721 0.0126 0.004458 0.0090998 -0.00033398 0.00034085 7.6886 0 0
|
| 39 |
+
143 -0.12434 0.48429 -0.10907 0.48796 0.05113 1.1505 0.26857 -1.1187 0.41698 0.10011 0.010768 -0.015999 333.4 0 0
|
| 40 |
+
16 0.4455 -0.227 0.43815 -0.24088 0.00167 0.031511 -0.027848 0.014745 0.0050904 0.0096141 -0.00035746 0.00038261 9.6001 0 0
|
| 41 |
+
144 -0.10907 0.48796 -0.093691 0.49114 0.04646 1.0407 0.21104 -1.0191 0.39235 0.081253 0.0094777 -0.014731 307.83 0 0
|
| 42 |
+
17 0.43815 -0.24088 0.43037 -0.25452 0.00165 0.03252 -0.028248 0.016112 0.0056436 0.0098942 -0.00035505 0.00040849 8.7847 0 0
|
| 43 |
+
145 -0.093691 0.49114 -0.078217 0.49384 0.04374 0.9789 0.1683 -0.96432 0.38654 0.067462 0.0087151 -0.014087 296.19 0 0
|
| 44 |
+
18 0.43037 -0.25452 0.42216 -0.26791 0.00175 0.031742 -0.027065 0.016585 0.0071138 0.011609 -0.00031338 0.00044285 8.8203 0 0
|
| 45 |
+
146 -0.078217 0.49384 -0.062667 0.49606 0.04005 0.88912 0.12528 -0.88025 0.34035 0.048439 0.0073137 -0.013066 255.32 0 0
|
| 46 |
+
19 0.42216 -0.26791 0.41354 -0.28104 0.00174 0.031559 -0.026377 0.017326 0.0097262 0.014807 -0.00026154 0.00050473 10.465 0 0
|
| 47 |
+
147 -0.062667 0.49606 -0.047054 0.49778 0.03733 0.83608 0.091746 -0.83103 0.3716 0.041025 0.0072779 -0.012409 263.16 0 0
|
| 48 |
+
20 0.41354 -0.28104 0.40451 -0.29389 0.00192 0.034983 -0.028622 0.020116 0.010756 0.015304 -0.00028062 0.00055635 9.131 0 0
|
| 49 |
+
148 -0.047054 0.49778 -0.031395 0.49901 0.03497 0.77446 0.060763 -0.77207 0.33696 0.026519 0.0062472 -0.011711 243.27 0 0
|
| 50 |
+
21 0.40451 -0.29389 0.39508 -0.30645 0.00189 0.036432 -0.029134 0.021875 0.014579 0.019418 -0.00022862 0.00064859 11.851 0 0
|
| 51 |
+
149 -0.031395 0.49901 -0.015705 0.49975 0.03252 0.70809 0.033355 -0.7073 0.32147 0.01516 0.0055733 -0.010872 208.88 0 0
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| 52 |
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| 53 |
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150 -0.015705 0.49975 0 0.5 0.02926 0.63366 0.0099531 -0.63358 0.29514 0.0046364 0.0047921 -0.009879 197.48 0 0
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| 54 |
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23 0.38526 -0.31871 0.37506 -0.33066 0.00242 0.043349 -0.032963 0.028153 0.019286 0.022581 -0.00021483 0.0007969 15.017 0 0
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| 55 |
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151 0 0.5 0.015705 0.49975 0.02794 0.61197 -0.0096125 -0.6119 0.29579 -0.0046467 0.0044951 -0.0096843 194.99 0 0
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| 56 |
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| 57 |
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152 0.015705 0.49975 0.031395 0.49901 0.02524 0.54693 -0.025764 -0.54632 0.2691 -0.01269 0.0038222 -0.0087806 171.47 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 0.02457 0.53405 -0.041901 -0.5324 0.27395 -0.021561 0.0036449 -0.0087013 170.45 0 0
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| 60 |
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| 61 |
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154 0.047054 0.49778 0.062667 0.49606 0.02105 0.45375 -0.049791 -0.45101 0.24128 -0.026637 0.0030078 -0.0075025 153.73 0 0
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| 62 |
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| 63 |
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155 0.062667 0.49606 0.078217 0.49384 0.01942 0.42133 -0.059365 -0.41712 0.23718 -0.033756 0.002793 -0.0070821 141.52 0 0
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| 64 |
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157 0.093691 0.49114 0.10907 0.48796 0.01608 0.33874 -0.068692 -0.3317 0.20185 -0.041801 0.0020916 -0.0058667 121.53 0 0
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| 69 |
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| 70 |
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| 71 |
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159 0.12434 0.48429 0.1395 0.48015 0.01426 0.2962 -0.078159 -0.2857 0.17655 -0.048299 0.0015455 -0.0052462 102.46 0 0
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| 74 |
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| 77 |
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| 78 |
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163 0.18406 0.46489 0.19857 0.45888 0.00907 0.18845 -0.072119 -0.17411 0.11638 -0.048205 0.0006952 -0.003492 67.994 0 0
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| 80 |
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| 81 |
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| 83 |
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| 84 |
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167 0.24088 0.43815 0.25452 0.43037 0.00654 0.12792 -0.06338 -0.11112 0.090266 -0.051487 0.0004223 -0.0025541 51.5 0 0
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| 88 |
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| 92 |
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| 93 |
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| 94 |
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43 0.12434 -0.48429 0.10907 -0.48796 0.01586 0.33103 -0.077277 0.32188 0.1954 0.046911 0.0018554 0.0057928 116.23 0 0
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| 101 |
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| 103 |
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48 0.047054 -0.49778 0.031395 -0.49901 0.02319 0.50468 -0.039597 0.50312 0.24886 0.019586 0.003287 0.0082103 158.57 0 0
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| 106 |
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| 107 |
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| 108 |
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| 109 |
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| 110 |
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| 111 |
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| 113 |
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| 114 |
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| 115 |
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55 -0.062667 -0.49606 -0.078217 -0.49384 0.03902 0.87259 0.12295 0.86388 0.37538 -0.053424 0.0078274 0.01273 275 0 0
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| 121 |
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| 122 |
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| 124 |
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| 132 |
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62 -0.16937 -0.47044 -0.18406 -0.46489 0.06466 1.4738 0.52094 1.3786 0.44158 -0.16686 0.015119 0.019033 419.99 0 0
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| 149 |
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| 151 |
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| 152 |
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| 153 |
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| 154 |
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| 155 |
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74 -0.33066 -0.37506 -0.34227 -0.36448 0.12431 2.8425 1.913 2.1024 0.42174 -0.38376 0.036673 0.026995 742.53 0 0
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| 156 |
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| 157 |
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| 158 |
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77 -0.36448 -0.34227 -0.37506 -0.33066 0.14095 3.2315 2.3901 2.1748 0.38061 -0.41828 0.04352 0.02759 836.01 0 0
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| 159 |
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| 160 |
+
79 -0.38526 -0.31871 -0.39508 -0.30645 0.15012 3.4354 2.6811 2.148 0.32915 -0.41085 0.047283 0.027286 867.83 0 0
|
| 161 |
+
80 -0.39508 -0.30645 -0.40451 -0.29389 0.15724 3.636 2.9077 2.1831 0.31791 -0.42342 0.050665 0.027641 941.64 0 0
|
| 162 |
+
81 -0.40451 -0.29389 -0.41354 -0.28104 0.16427 3.7826 3.0948 2.175 0.3015 -0.42899 0.053346 0.027426 965.04 0 0
|
| 163 |
+
82 -0.41354 -0.28104 -0.42216 -0.26791 0.16994 3.9189 3.2754 2.1516 0.29065 -0.44247 0.056014 0.026845 1018 0 0
|
| 164 |
+
83 -0.42216 -0.26791 -0.43037 -0.25452 0.17416 4.0273 3.4338 2.1043 0.2552 -0.41644 0.057945 0.026511 1028.8 0 0
|
| 165 |
+
84 -0.43037 -0.25452 -0.43815 -0.24088 0.17984 4.1163 3.5756 2.0395 0.23316 -0.40877 0.059825 0.025614 1034.3 0 0
|
| 166 |
+
85 -0.43815 -0.24088 -0.4455 -0.227 0.18649 4.3003 3.8005 2.0122 0.22834 -0.43126 0.063282 0.024833 1082.7 0 0
|
| 167 |
+
86 -0.4455 -0.227 -0.45241 -0.21289 0.19216 4.4254 3.9742 1.9469 0.20808 -0.42474 0.065692 0.023909 1125.6 0 0
|
| 168 |
+
87 -0.45241 -0.21289 -0.45888 -0.19857 0.19162 4.3929 4.0037 1.8077 0.16845 -0.37307 0.065533 0.022535 1095.7 0 0
|
| 169 |
+
88 -0.45888 -0.19857 -0.46489 -0.18406 0.20081 4.5811 4.2324 1.7531 0.14261 -0.34428 0.068719 0.022129 1122.4 0 0
|
| 170 |
+
89 -0.46489 -0.18406 -0.47044 -0.16937 0.20051 4.6262 4.3276 1.6353 0.13186 -0.34896 0.070046 0.020204 1182.6 0 0
|
| 171 |
+
90 -0.47044 -0.16937 -0.47553 -0.15451 0.20588 4.7409 4.4853 1.5356 0.11451 -0.33447 0.07225 0.018867 1198.1 0 0
|
| 172 |
+
91 -0.47553 -0.15451 -0.48015 -0.1395 0.20869 4.8184 4.6053 1.4168 0.089081 -0.28956 0.073737 0.017706 1224.5 0 0
|
| 173 |
+
92 -0.48015 -0.1395 -0.48429 -0.12434 0.21035 4.8679 4.6954 1.2845 0.074818 -0.27349 0.074927 0.01588 1222.3 0 0
|
| 174 |
+
93 -0.48429 -0.12434 -0.48796 -0.10907 0.21359 4.9333 4.797 1.1517 0.068274 -0.28438 0.076421 0.013623 1253 0 0
|
| 175 |
+
94 -0.48796 -0.10907 -0.49114 -0.093691 0.2208 5.0638 4.9586 1.0269 0.042825 -0.20679 0.078559 0.012881 1257.4 0 0
|
| 176 |
+
95 -0.49114 -0.093691 -0.49384 -0.078217 0.21928 5.0872 5.0115 0.87464 0.030478 -0.17463 0.079196 0.010995 1293.9 0 0
|
| 177 |
+
96 -0.49384 -0.078217 -0.49606 -0.062667 0.22132 5.1144 5.0634 0.72063 0.026373 -0.18531 0.079947 0.0084085 1298.4 0 0
|
| 178 |
+
97 -0.49606 -0.062667 -0.49778 -0.047054 0.22509 5.1931 5.1617 0.56986 0.015139 -0.13713 0.081315 0.0067971 1316.2 0 0
|
| 179 |
+
98 -0.49778 -0.047054 -0.49901 -0.031395 0.22472 5.1636 5.1477 0.40513 0.0071158 -0.090415 0.080968 0.0049434 1287 0 0
|
| 180 |
+
99 -0.49901 -0.031395 -0.49975 -0.015705 0.22693 5.2418 5.236 0.24692 0.0033007 -0.069991 0.082295 0.0027791 1307.7 0 0
|
| 181 |
+
100 -0.49975 -0.015705 -0.5 0 0.22779 5.2677 5.267 0.082741 3.0847e-05 -0.0019636 0.082731 0.0012688 1328.9 0 0
|
| 182 |
+
101 -0.5 0 -0.49975 0.015705 0.22512 5.2036 5.2029 -0.081734 0.00046489 0.029593 0.081732 -0.000819 1298.4 0 0
|
| 183 |
+
102 -0.49975 0.015705 -0.49901 0.031395 0.22721 5.2193 5.2135 -0.24586 0.0021928 0.046499 0.081925 -0.0031315 1298.1 0 0
|
| 184 |
+
103 -0.49901 0.031395 -0.49778 0.047054 0.22825 5.2687 5.2525 -0.41338 0.0089825 0.11413 0.082643 -0.0047003 1316.2 0 0
|
| 185 |
+
104 -0.49778 0.047054 -0.49606 0.062667 0.22203 5.1441 5.1131 -0.56449 0.010588 0.095909 0.080479 -0.0073601 1291.9 0 0
|
| 186 |
+
105 -0.49606 0.062667 -0.49384 0.078217 0.22316 5.1847 5.133 -0.73053 0.022912 0.16099 0.080985 -0.0089459 1315.9 0 0
|
| 187 |
+
106 -0.49384 0.078217 -0.49114 0.093691 0.22346 5.1363 5.0598 -0.88308 0.02924 0.16754 0.079935 -0.011239 1279.5 0 0
|
| 188 |
+
107 -0.49114 0.093691 -0.48796 0.10907 0.21994 5.072 4.9667 -1.0285 0.05346 0.25815 0.078853 -0.012101 1272.1 0 0
|
| 189 |
+
108 -0.48796 0.10907 -0.48429 0.12434 0.21861 5.0213 4.8826 -1.1722 0.057787 0.2407 0.0776 -0.014631 1243.4 0 0
|
| 190 |
+
109 -0.48429 0.12434 -0.48015 0.1395 0.21376 4.9201 4.7457 -1.2983 0.067693 0.24744 0.075605 -0.016506 1219.1 0 0
|
| 191 |
+
110 -0.48015 0.1395 -0.47553 0.15451 0.20968 4.8125 4.5998 -1.4151 0.098763 0.32104 0.073801 -0.017184 1194.6 0 0
|
| 192 |
+
111 -0.47553 0.15451 -0.47044 0.16937 0.20465 4.7216 4.467 -1.5294 0.10451 0.30523 0.071806 -0.019228 1183.5 0 0
|
| 193 |
+
112 -0.47044 0.16937 -0.46489 0.18406 0.20012 4.6324 4.3333 -1.6374 0.1341 0.35488 0.070171 -0.020145 1192 0 0
|
| 194 |
+
113 -0.46489 0.18406 -0.45888 0.19857 0.20027 4.5938 4.2441 -1.758 0.14385 0.34728 0.068923 -0.022158 1147.6 0 0
|
| 195 |
+
114 -0.45888 0.19857 -0.45241 0.21289 0.19362 4.4896 4.0918 -1.8475 0.17673 0.3914 0.067047 -0.022872 1160.8 0 0
|
| 196 |
+
115 -0.45241 0.21289 -0.4455 0.227 0.18828 4.3066 3.8674 -1.8946 0.20849 0.42558 0.064021 -0.023075 1091.5 0 0
|
| 197 |
+
116 -0.4455 0.227 -0.43815 0.24088 0.18534 4.2616 3.7663 -1.9941 0.2187 0.41305 0.062593 -0.024835 1098.5 0 0
|
| 198 |
+
117 -0.43815 0.24088 -0.43037 0.25452 0.17753 4.0833 3.5469 -2.0231 0.24578 0.4309 0.059573 -0.025009 1046.2 0 0
|
| 199 |
+
118 -0.43037 0.25452 -0.42216 0.26791 0.1756 4.0193 3.427 -2.1001 0.24846 0.40544 0.057732 -0.026618 1011.9 0 0
|
| 200 |
+
119 -0.42216 0.26791 -0.41354 0.28104 0.16839 3.8983 3.2582 -2.1403 0.27492 0.41853 0.055496 -0.027044 1000.1 0 0
|
| 201 |
+
120 -0.41354 0.28104 -0.40451 0.29389 0.16219 3.7385 3.0586 -2.1496 0.31335 0.44585 0.052965 -0.026762 957.56 0 0
|
| 202 |
+
121 -0.40451 0.29389 -0.39508 0.30645 0.15884 3.6417 2.9122 -2.1865 0.31963 0.42571 0.050763 -0.027658 938.53 0 0
|
| 203 |
+
122 -0.39508 0.30645 -0.38526 0.31871 0.1527 3.5283 2.7536 -2.2061 0.3406 0.42513 0.048602 -0.027973 918.66 0 0
|
| 204 |
+
123 -0.38526 0.31871 -0.37506 0.33066 0.14531 3.342 2.5413 -2.1704 0.35882 0.42012 0.045552 -0.027493 870.18 0 0
|
| 205 |
+
124 -0.37506 0.33066 -0.36448 0.34227 0.14076 3.2314 2.3901 -2.1748 0.35736 0.39274 0.043155 -0.027992 839.26 0 0
|
| 206 |
+
125 -0.36448 0.34227 -0.35355 0.35355 0.13412 3.0807 2.2123 -2.1439 0.40147 0.41428 0.041055 -0.027167 817.66 0 0
|
| 207 |
+
126 -0.35355 0.35355 -0.34227 0.36448 0.12872 2.9642 2.0628 -2.1287 0.39345 0.38128 0.038581 -0.027447 783.43 0 0
|
| 208 |
+
127 -0.34227 0.36448 -0.33066 0.37506 0.12493 2.8616 1.9259 -2.1165 0.43502 0.39584 0.037084 -0.027028 772.22 0 0
|
| 209 |
+
128 -0.33066 0.37506 -0.31871 0.38526 0.11977 2.758 1.7912 -2.0972 0.42672 0.36445 0.034837 -0.027216 750.8 0 0
|
CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/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/Kn0p38/simulation0831_Kn0p38Ma5p0/runmpirun64.sh
ADDED
|
@@ -0,0 +1,18 @@
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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/Kn0p38/simulation0831_Kn0p38Ma5p0/slurm-28428809.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 53265 child grid cells
|
| 6 |
+
CPU time = 0.0887773 secs
|
| 7 |
+
create/ghost percent = 1.2613 98.7387
|
| 8 |
+
Balance grid migrated 53160 cells
|
| 9 |
+
CPU time = 0.0816815 secs
|
| 10 |
+
reassign/sort/migrate/ghost percent = 62.2038 0.0346345 9.31674 28.4448
|
| 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 |
+
336 0 = cells overlapping surfs, overlap cells with unmarked corner pts
|
| 18 |
+
47589 5340 336 = cells outside/inside/overlapping surfs
|
| 19 |
+
336 = surf cells with 1,2,etc splits
|
| 20 |
+
109.214731023047 109.214731023047 = cell-wise and global flow volume
|
| 21 |
+
CPU time = 0.104141 secs
|
| 22 |
+
read/check/sort/surf2grid/ghost/inout/particle percent = 33.2013 21.1166 2.61309 21.382 21.687 5.51421 0.144198
|
| 23 |
+
surf2grid time = 0.0222675 secs
|
| 24 |
+
map/comm1/comm2/comm3/comm4/split percent = 13.2586 24.4611 5.2827 1.82973 12.0089 6.99823
|
| 25 |
+
Balance grid migrated 988 cells
|
| 26 |
+
CPU time = 0.0372722 secs
|
| 27 |
+
reassign/sort/migrate/ghost percent = 8.93933 0.0860696 24.4898 66.4848
|
| 28 |
+
Creating particles ...
|
| 29 |
+
WARNING: Created unexpected # of particles: 363039 versus 363040 (../create_particles.cpp:346)
|
| 30 |
+
Created 363039 particles
|
| 31 |
+
CPU time = 0.0117585 secs
|
| 32 |
+
Memory usage per proc in Mbytes:
|
| 33 |
+
particles (ave,min,max) = 1.6084 0 1.6875
|
| 34 |
+
grid (ave,min,max) = 2.88342 1.51379 4.32629
|
| 35 |
+
surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
|
| 36 |
+
total (ave,min,max) = 4.51242 3.22189 6.03439
|
| 37 |
+
Step CPU Np Natt Ncoll Nscoll Npave Nscollave
|
| 38 |
+
0 0 363039 0 0 0 0 0
|
| 39 |
+
10000 10.715744 405617 5510 4808 11 385262.8 13.6933
|
| 40 |
+
20000 23.168004 406526 5494 4832 8 396037.64 13.8213
|
| 41 |
+
30000 34.742759 406506 5603 4881 13 399455.81 13.8431
|
| 42 |
+
40000 46.305382 407136 5527 4763 14 401395.18 13.873825
|
| 43 |
+
50000 57.474304 406547 5541 4820 20 402487.44 13.88534
|
| 44 |
+
60000 69.947566 406562 5590 4890 18 403169.46 13.878167
|
| 45 |
+
70000 83.886985 406586 5475 4788 20 403623.17 13.869243
|
| 46 |
+
80000 95.520532 407136 5592 4877 10 404046.62 13.883325
|
| 47 |
+
90000 107.00026 406709 5670 4937 13 404372.86 13.885833
|
| 48 |
+
100000 118.2772 406496 5526 4800 10 404636.21 13.88519
|
| 49 |
+
110000 130.85421 407303 5599 4895 12 404862.84 13.900064
|
| 50 |
+
120000 143.13501 406638 5490 4779 14 405066.91 13.898433
|
| 51 |
+
130000 155.27139 406175 5625 4946 13 405164.87 13.896569
|
| 52 |
+
140000 166.88632 406472 5590 4892 12 405262.38 13.900671
|
| 53 |
+
150000 178.1726 406343 5459 4784 14 405381.62 13.902693
|
| 54 |
+
160000 190.55526 406026 5606 4867 17 405468.44 13.90325
|
| 55 |
+
170000 202.94851 405824 5558 4848 13 405525.67 13.905
|
| 56 |
+
180000 214.41525 407332 5614 4881 15 405583.29 13.903411
|
| 57 |
+
190000 225.92802 406561 5486 4767 11 405629.99 13.903253
|
| 58 |
+
200000 237.06025 407497 5634 4936 10 405697.67 13.905595
|
| 59 |
+
Loop time of 237.061 on 128 procs for 200000 steps with 407497 particles
|
| 60 |
+
|
| 61 |
+
MPI task timing breakdown:
|
| 62 |
+
Section | min time | avg time | max time |%varavg| %total
|
| 63 |
+
---------------------------------------------------------------
|
| 64 |
+
Move | 0.02208 | 10.034 | 64.466 | 417.3 | 4.23
|
| 65 |
+
Coll | 0.27641 | 8.1183 | 70.279 | 390.7 | 3.42
|
| 66 |
+
Sort | 0.092778 | 1.6589 | 12.12 | 173.3 | 0.70
|
| 67 |
+
Comm | 56.946 | 90.071 | 100.8 | 90.5 | 37.99
|
| 68 |
+
Modify | 0.017966 | 0.1073 | 2.0342 | 92.1 | 0.05
|
| 69 |
+
Output | 0.0052381 | 0.0091026 | 0.011423 | 0.9 | 0.00
|
| 70 |
+
Other | | 127.1 | | | 53.60
|
| 71 |
+
|
| 72 |
+
Particle moves = 81139534856 (81.1B)
|
| 73 |
+
Cells touched = 84776043676 (84.8B)
|
| 74 |
+
Particle comms = 186355958 (186M)
|
| 75 |
+
Boundary collides = 0 (0K)
|
| 76 |
+
Boundary exits = 17891659 (17.9M)
|
| 77 |
+
SurfColl checks = 171494442 (171M)
|
| 78 |
+
SurfColl occurs = 2781119 (2.78M)
|
| 79 |
+
Surf reactions = 0 (0K)
|
| 80 |
+
Collide attempts = 1273306800 (1.27B)
|
| 81 |
+
Collide occurs = 999557561 (1e+03M)
|
| 82 |
+
Gas reactions = 0 (0K)
|
| 83 |
+
Particles stuck = 0
|
| 84 |
+
Axisymm bad moves = 0
|
| 85 |
+
|
| 86 |
+
Particle-moves/CPUsec/proc: 2.67401e+06
|
| 87 |
+
Particle-moves/step: 405698
|
| 88 |
+
Cell-touches/particle/step: 1.04482
|
| 89 |
+
Particle comm iterations/step: 1
|
| 90 |
+
Particle fraction communicated: 0.00229673
|
| 91 |
+
Particle fraction colliding with boundary: 0
|
| 92 |
+
Particle fraction exiting boundary: 0.000220505
|
| 93 |
+
Surface-checks/particle/step: 0.00211357
|
| 94 |
+
Surface-collisions/particle/step: 3.42758e-05
|
| 95 |
+
Surface-reactions/particle/step: 0
|
| 96 |
+
Collision-attempts/particle/step: 0.0156928
|
| 97 |
+
Collisions/particle/step: 0.012319
|
| 98 |
+
Gas-reactions/particle/step: 0
|
| 99 |
+
|
| 100 |
+
Particles: 3183.57 ave 22143 max 0 min
|
| 101 |
+
Histogram: 84 16 5 11 2 6 0 1 1 2
|
| 102 |
+
Cells: 416.133 ave 417 max 415 min
|
| 103 |
+
Histogram: 1 0 0 0 0 109 0 0 0 18
|
| 104 |
+
GhostCell: 10796.4 ave 19812 max 593 min
|
| 105 |
+
Histogram: 21 9 14 8 17 3 6 4 16 30
|
| 106 |
+
EmptyCell: 74.8203 ave 218 max 0 min
|
| 107 |
+
Histogram: 40 1 16 7 26 15 8 11 2 2
|
| 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) = 1.66113 0 3.375
|
| 114 |
+
grid (ave,min,max) = 2.88342 1.51379 4.32629
|
| 115 |
+
surf (ave,min,max) = 0.0205994 0.0205994 0.0205994
|
| 116 |
+
total (ave,min,max) = 4.70511 3.36171 6.17471
|
| 117 |
+
Step CPU Np Natt Ncoll Nscoll Npave Nscollave
|
| 118 |
+
200000 0 407497 5634 4936 0 0 0
|
| 119 |
+
210000 22.379207 406730 5448 4790 15 406845.44 13.9434
|
| 120 |
+
220000 42.885702 405896 5391 4715 24 406769.45 13.9144
|
| 121 |
+
230000 63.625546 406561 5563 4850 10 406698.04 13.912067
|
| 122 |
+
240000 85.919824 406973 5574 4875 15 406690.64 13.91015
|
| 123 |
+
250000 106.83458 407413 5582 4921 8 406727.51 13.93164
|
| 124 |
+
260000 127.35024 406400 5549 4863 12 406771.89 13.934533
|
| 125 |
+
270000 149.63751 406952 5568 4844 17 406803.47 13.935743
|
| 126 |
+
280000 170.36821 406540 5489 4820 7 406826.88 13.936775
|
| 127 |
+
290000 190.77407 406410 5621 4890 18 406800.76 13.9278
|
| 128 |
+
300000 212.84209 406296 5464 4766 13 406775.46 13.92883
|
| 129 |
+
Loop time of 212.842 on 128 procs for 100000 steps with 406296 particles
|
| 130 |
+
|
| 131 |
+
MPI task timing breakdown:
|
| 132 |
+
Section | min time | avg time | max time |%varavg| %total
|
| 133 |
+
---------------------------------------------------------------
|
| 134 |
+
Move | 0.01142 | 5.0602 | 32.365 | 294.9 | 2.38
|
| 135 |
+
Coll | 0.13828 | 4.1093 | 36.803 | 280.9 | 1.93
|
| 136 |
+
Sort | 0.052136 | 0.84212 | 5.9037 | 122.0 | 0.40
|
| 137 |
+
Comm | 32.99 | 50.057 | 55.902 | 62.5 | 23.52
|
| 138 |
+
Modify | 1.9345 | 13.854 | 85.417 | 449.6 | 6.51
|
| 139 |
+
Output | 0.032275 | 0.033744 | 0.036344 | 0.5 | 0.02
|
| 140 |
+
Other | | 138.9 | | | 65.25
|
| 141 |
+
|
| 142 |
+
Particle moves = 40677545625 (40.7B)
|
| 143 |
+
Cells touched = 42499664707 (42.5B)
|
| 144 |
+
Particle comms = 93356457 (93.4M)
|
| 145 |
+
Boundary collides = 0 (0K)
|
| 146 |
+
Boundary exits = 8967523 (8.97M)
|
| 147 |
+
SurfColl checks = 85776106 (85.8M)
|
| 148 |
+
SurfColl occurs = 1392883 (1.39M)
|
| 149 |
+
Surf reactions = 0 (0K)
|
| 150 |
+
Collide attempts = 641246687 (641M)
|
| 151 |
+
Collide occurs = 503364128 (503M)
|
| 152 |
+
Gas reactions = 0 (0K)
|
| 153 |
+
Particles stuck = 0
|
| 154 |
+
Axisymm bad moves = 0
|
| 155 |
+
|
| 156 |
+
Particle-moves/CPUsec/proc: 1.49309e+06
|
| 157 |
+
Particle-moves/step: 406775
|
| 158 |
+
Cell-touches/particle/step: 1.04479
|
| 159 |
+
Particle comm iterations/step: 1
|
| 160 |
+
Particle fraction communicated: 0.00229504
|
| 161 |
+
Particle fraction colliding with boundary: 0
|
| 162 |
+
Particle fraction exiting boundary: 0.000220454
|
| 163 |
+
Surface-checks/particle/step: 0.00210868
|
| 164 |
+
Surface-collisions/particle/step: 3.42421e-05
|
| 165 |
+
Surface-reactions/particle/step: 0
|
| 166 |
+
Collision-attempts/particle/step: 0.0157641
|
| 167 |
+
Collisions/particle/step: 0.0123745
|
| 168 |
+
Gas-reactions/particle/step: 0
|
| 169 |
+
|
| 170 |
+
Particles: 3174.19 ave 22221 max 0 min
|
| 171 |
+
Histogram: 84 16 6 10 2 6 0 2 0 2
|
| 172 |
+
Cells: 416.133 ave 417 max 415 min
|
| 173 |
+
Histogram: 1 0 0 0 0 109 0 0 0 18
|
| 174 |
+
GhostCell: 10796.4 ave 19812 max 593 min
|
| 175 |
+
Histogram: 21 9 14 8 17 3 6 4 16 30
|
| 176 |
+
EmptyCell: 74.8203 ave 218 max 0 min
|
| 177 |
+
Histogram: 40 1 16 7 26 15 8 11 2 2
|
| 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 = 53265
|
| 184 |
+
CPU time = 0.00781818 secs
|
| 185 |
+
Writing surface file ...
|
| 186 |
+
surf elements = 200
|
| 187 |
+
CPU time = 0.0017339 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 0:00:08 (wall clock time)
|
| 195 |
+
|
| 196 |
+
Processing 4 grid chunk(s).
|
| 197 |
+
Completed grid chunk number: 3
|
| 198 |
+
Completed grid chunk number: 1
|
| 199 |
+
Completed grid chunk number: 2
|
| 200 |
+
Completed grid chunk number: 0
|
| 201 |
+
|
| 202 |
+
Done in 0:00:08 (wall clock time)
|
| 203 |
+
|
| 204 |
+
Processing SPARTA surface information.
|
| 205 |
+
Processing dump result file: ['./output/surf.300000.dat']
|
CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/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="0.00132" RangeMax="0.22825" offset="4512" />
|
| 14 |
+
<DataArray type="Float64" Name="f_2[2]" format="appended" RangeMin="0.025474" RangeMax="5.2687" offset="6488" />
|
| 15 |
+
<DataArray type="Float64" Name="f_2[3]" format="appended" RangeMin="-0.080484" RangeMax="5.267" offset="8524" />
|
| 16 |
+
<DataArray type="Float64" Name="f_2[4]" format="appended" RangeMin="-2.2061" RangeMax="2.2044" offset="10636" />
|
| 17 |
+
<DataArray type="Float64" Name="f_2[5]" format="appended" RangeMin="-0.00032581" RangeMax="0.48277" offset="12700" />
|
| 18 |
+
<DataArray type="Float64" Name="f_2[6]" format="appended" RangeMin="-0.44247" RangeMax="0.44585" offset="14764" />
|
| 19 |
+
<DataArray type="Float64" Name="f_2[7]" format="appended" RangeMin="-0.00060882" RangeMax="0.082731" offset="16880" />
|
| 20 |
+
<DataArray type="Float64" Name="f_2[8]" format="appended" RangeMin="-0.027992" RangeMax="0.028209" offset="19016" />
|
| 21 |
+
<DataArray type="Float64" Name="f_2[9]" format="appended" RangeMin="4.9638" RangeMax="1328.9" offset="21164" />
|
| 22 |
+
<DataArray type="Float64" Name="f_2[10]" format="appended" RangeMin="0" RangeMax="0" offset="22620" />
|
| 23 |
+
<DataArray type="Float64" Name="f_2[11]" format="appended" RangeMin="0" RangeMax="0" offset="22672" />
|
| 24 |
+
</CellData>
|
| 25 |
+
<Points>
|
| 26 |
+
<DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="0.49999998503" RangeMax="0.50000001255" offset="22724" />
|
| 27 |
+
</Points>
|
| 28 |
+
<Cells>
|
| 29 |
+
<DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="24052" />
|
| 30 |
+
<DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="24956" />
|
| 31 |
+
<DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="25448" />
|
| 32 |
+
</Cells>
|
| 33 |
+
</Piece>
|
| 34 |
+
</UnstructuredGrid>
|
| 35 |
+
<AppendedData encoding="base64">
|
| 36 |
+
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AQAAAACAAABABgAA4wUAAA==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AQAAAACAAABABgAAHQYAAA==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AQAAAACAAABABgAA+AUAAA==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AQAAAACAAABABgAA+AUAAA==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AQAAAACAAABABgAAHwYAAA==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AQAAAACAAABABgAALgYAAA==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AQAAAACAAABABgAANwYAAA==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AQAAAACAAABABgAAMAQAAA==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AQAAAACAAABABgAAFQAAAA==eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAABABgAAFQAAAA==eJxjYBgFo2AUjIJRMApIBwAGQAABAQAAAACAAADAEgAA0gMAAA==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AQAAAACAAABABgAAXwEAAA==eJwtxVFEHAAAANBKkpzkJEmSJMlJkiRJkiRJkiQnSXKSJEmSJEmSJEmSZGYmmUmSJEmSJEkyMzOTzCRJkmT20Xs/LybqXazjHO8EB5zoJAed7BSnOs3pznCms5ztHOc6zyHnu8CFLnKxS1zqMpe7wpWucrVrXOs617vBjW5ys1vc6rDb3O4Od7rLEXe7x73uc78HPOghD3vEox7zuCc86SlPe8aznvO8F7zoJS97xate8wd/9Cd/9ro3/MVfvektb3vHu97zvg986CMf+8SnPvO5L3zpK1/7m7/7h3/6l3/7xrf+47++870f/OgnP/vFr37zP0dFvxfjWMc53gkOONFJDjrZKU51mtOd4UxnOds5znWeQ853gQtd5GKXuNRlLneFK13late41nWud4Mb3eRmt7jVYbe53R3udJcj7naPe93nfg940EMe9ohHPeZxT3jSU572jGc95/9sSVRSAQAAAACAAADIAAAADAAAAA==eJxjZh4eAADsVAJZ
|
| 37 |
+
</AppendedData>
|
| 38 |
+
</VTKFile>
|
CylinderKnMa/Kn0p38/simulation0831_Kn0p38Ma5p0/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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AQAAAACAAADgLgAABSIAAA==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AgAAAACAAACAOwAABRMAABMJAAA=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|
| 26 |
+
</AppendedData>
|
| 27 |
+
</VTKFile>
|
CylinderKnMa/Kn0p38/simulation0832_Kn0p38Ma5p1/Lambda/Lambda_2_300000.vtu
ADDED
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@@ -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="606" NumberOfCells="500" >
|
| 5 |
+
<PointData>
|
| 6 |
+
</PointData>
|
| 7 |
+
<CellData>
|
| 8 |
+
<DataArray type="Float64" Name="id" format="appended" RangeMin="11501" RangeMax="12060" offset="0" />
|
| 9 |
+
<DataArray type="Float64" Name="xc" format="appended" RangeMin="-4.9522" RangeMax="4.5174" offset="948" />
|
| 10 |
+
<DataArray type="Float64" Name="yc" format="appended" RangeMin="4.5714" RangeMax="4.9524" offset="1992" />
|
| 11 |
+
<DataArray type="Float64" Name="c_6[1]" format="appended" RangeMin="0.026936" RangeMax="0.0366" offset="2124" />
|
| 12 |
+
<DataArray type="Float64" Name="c_6[2]" format="appended" RangeMin="0.2816" RangeMax="0.38264" offset="5536" />
|
| 13 |
+
</CellData>
|
| 14 |
+
<Points>
|
| 15 |
+
<DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="4.5238846488" RangeMax="7.0710678119" offset="8912" />
|
| 16 |
+
</Points>
|
| 17 |
+
<Cells>
|
| 18 |
+
<DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="11292" />
|
| 19 |
+
<DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="14996" />
|
| 20 |
+
<DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="15972" />
|
| 21 |
+
</Cells>
|
| 22 |
+
</Piece>
|
| 23 |
+
</UnstructuredGrid>
|
| 24 |
+
<AppendedData encoding="base64">
|
| 25 |
+
_AQAAAACAAACgDwAAtQIAAA==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AQAAAACAAACgDwAATwAAAA==eJy7vOexiKynkMPlUXqUHqUxaM6fC9I3rxqlR+lRGhut7FXdrM8jPEqP0qM0Ftp2duj81bmj9Cg9SmOji68LfXI8P0qP0qM0NhoAXjcwVw==AQAAAACAAACgDwAA6wkAAA==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AQAAAACAAACgDwAA0QkAAA==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AQAAAACAAABoHAAA5wYAAA==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AQAAAACAAACgDwAAyAIAAA==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AQAAAACAAAD0AQAADgAAAA==eJzj5BwFIw0AADZFEZU=
|
| 26 |
+
</AppendedData>
|
| 27 |
+
</VTKFile>
|
CylinderKnMa/Kn0p38/simulation0832_Kn0p38Ma5p1/Lambda/Lambda_300000.pvtu
ADDED
|
@@ -0,0 +1,21 @@
|
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|
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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="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/Kn0p38/simulation0832_Kn0p38Ma5p1/Lambda/Lambda_3_300000.vtu
ADDED
|
@@ -0,0 +1,27 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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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="96" NumberOfCells="75" >
|
| 5 |
+
<PointData>
|
| 6 |
+
</PointData>
|
| 7 |
+
<CellData>
|
| 8 |
+
<DataArray type="Float64" Name="id" format="appended" RangeMin="11601" RangeMax="12075" offset="0" />
|
| 9 |
+
<DataArray type="Float64" Name="xc" format="appended" RangeMin="4.613" RangeMax="5.9522" offset="208" />
|
| 10 |
+
<DataArray type="Float64" Name="yc" format="appended" RangeMin="4.5714" RangeMax="4.9524" offset="416" />
|
| 11 |
+
<DataArray type="Float64" Name="c_6[1]" format="appended" RangeMin="0.020294" RangeMax="0.036319" offset="512" />
|
| 12 |
+
<DataArray type="Float64" Name="c_6[2]" format="appended" RangeMin="0.21216" RangeMax="0.3797" offset="1348" />
|
| 13 |
+
</CellData>
|
| 14 |
+
<Points>
|
| 15 |
+
<DataArray type="Float32" Name="Points" NumberOfComponents="3" format="appended" RangeMin="6.426979272" RangeMax="7.8102496759" offset="2180" />
|
| 16 |
+
</Points>
|
| 17 |
+
<Cells>
|
| 18 |
+
<DataArray type="Int64" Name="connectivity" format="appended" RangeMin="" RangeMax="" offset="2596" />
|
| 19 |
+
<DataArray type="Int64" Name="offsets" format="appended" RangeMin="" RangeMax="" offset="3140" />
|
| 20 |
+
<DataArray type="UInt8" Name="types" format="appended" RangeMin="" RangeMax="" offset="3388" />
|
| 21 |
+
</Cells>
|
| 22 |
+
</Piece>
|
| 23 |
+
</UnstructuredGrid>
|
| 24 |
+
<AppendedData encoding="base64">
|
| 25 |
+
_AQAAAACAAABYAgAAiQAAAA==eJwtx9s1AwEAANHpwzuVaCIIitkKEKIHBOki+hDx6AJn7/zcM1XDw/q4/x5HB/bk2dKzZ89ePHv1bOXZu2cbzz4823r26dmXZ9+e/fidt/F3Rwe259m+ZweeHXp25NnEs6lnJ56denbm2cyzc88uPLv0V/7asxvP5p7denbn2cKze//nL3yyhvI=AQAAAACAAABYAgAAiAAAAA==eJw7eGqh67ZiIYeMza+Kt14Vcvi0ISB7lrmww6yZICDs4Nj06PiM38IOZ+o99tfGijgUZ0x8W7NfxOFf6vcniYqiDkv9HIQTm0UdDHyWcbk9FXW4bvLewtVdzCHRKNRAa6WYA6f0vDhNbnGHyRIsYXy54g7WjL4tvOfFHQ6O2jus7QUAd63urQ==AQAAAACAAABYAgAANgAAAA==eJy7vOexiKynkMNlOtOcPxekb15Ff1rZq7pZn0eY7rTt7ND5q3PpTxdfF/rkeJ7+NADFJe2aAQAAAACAAABYAgAAYAIAAA==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AQAAAACAAABYAgAAXgIAAA==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eJw9zj1KwnEAh/Efzs3ewLGxMTCkGwReoE1q8QThBcLojeKPiiAkgiQEQUMvB5CWCFrcXBoCL5DP8Hyf6TM+rXq/ufNx3izbvhuX8cneTVw7vIuvj6p493gYv3fHcbs3iX/7D/HZaBbXH+fx9G0RH3w+xV+r57jz9xKX8hq3tv/7y4v8a/41/5p/zb/mX/Ov+df8a/41/5p/zb/mX/Ov+T/9ucq/5l/zr/nX/Gv+Nf+af82/5l/zr/nX/Gv+Nf+a/2p9m3/Nv+Zf86/51/xr/jX/mn/Nv+Zf86/51/xr/jX/y819/jX/mn/Nv+Zf86/51/xr/jX/mn/Nv+Zf86/51/yXMsi/5l/zr/nX/Gv+Nf+af82/5l/zr/nX/Gv+Nf/6H0+7Z2I=AQAAAACAAABgCQAAhgEAAA==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eJwtxRF0QgEAAMD2XhAEQfAhCIIgCIJgEARBEATBIAiCIAiCIBgEQRAEQRAEQRAMgiAYBEEQBINBEARBEATdyYVDbxFHHXPcgRNOOuW0M84657w/XXDRJZddcdU1f7nuhptuue2Ou+65728PPPTIY0889cxzL7z0ymv/eOOtd/713gcfffLZf/73xVfffPfDT4c+3oUdcdQxxx044aRTTjvjF05rIJU=AQAAAACAAABLAAAADAAAAA==eJzj5KQaAABkfQKk
|
| 26 |
+
</AppendedData>
|
| 27 |
+
</VTKFile>
|
CylinderKnMa/Kn0p38/simulation0832_Kn0p38Ma5p1/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/Kn0p38/simulation0832_Kn0p38Ma5p1/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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|
|
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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 0.38
|
| 13 |
+
variable Ma equal 5.1
|
| 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/Kn0p38/simulation0832_Kn0p38Ma5p1/cylinder.surf
ADDED
|
@@ -0,0 +1,410 @@
|
|
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|
|
|
|
|
|
|
|
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