[Gmsh] Stress on Gauss Points
Max Orok
morok at mevex.com
Thu Feb 14 01:31:51 CET 2019
Hi Gaetano,
Here is a small python script that tries to plot these data along with the
mesh results file.
I assumed the node forces were for the given elements, in the order gmsh is
expecting.
Here are some pictures -> hopefully it is something like you were
predicting.
To an outsider, they look pretty good!
[image: image.png]
[image: image.png]
Sincerely,
Max
On Wed, Feb 13, 2019 at 8:02 AM Gaetano Camarda <gaetano_18 at live.it> wrote:
>
>
> Hello, I have an issue with postprocessing on Gmsh, I created a mesh on
> Gmsh, and I’ve imported it on Matlab, for some analysis,
>
> now I have the displacement of my mesh and I’m able to import it on the
> .msh file and post-processing the view on Gmsh.
>
> I have also 2 matrix, one with stress calculated on Gauss Points (I used
> 2) and one with nodal force of the element in each row.
>
> I would like to view the stress and nodal force in Gmsh, as I do with
> displacement. But I do not know how to do it.
>
> I’ve worked with Hexahedral.
>
> I’m attatching also the file of the mesh, and the files with stress on
> gauss point and nodal forces.
>
>
>
> (please remove .txt from 10cm.msh)
>
> Inviato da Posta <https://go.microsoft.com/fwlink/?LinkId=550986> per
> Windows 10
>
>
> _______________________________________________
> gmsh mailing list
> gmsh at onelab.info
> http://onelab.info/mailman/listinfo/gmsh
>
--
Max Orok
Contractor
www.mevex.com
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-43.348 -159.79 -159.77 302.01 285.51 0.69693
-10.43 -147.72 -146.27 579.19 258.11 1.4707
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38.784 -22.934 -22.854 311.93 275.8 2.601
68.783 -17.669 -12.275 588.62 248.4 5.4886
97.476 -7.8473 -8.2284 614.04 527.64 8.1459
57.685 17.106 10.624 280.01 581.96 6.4607
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53.797 9.6144 5.156 297.89 564.83 5.8962
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-35.244 -2.4408 -22.348 643.7 37.414 1.5683
24.735 20.676 2.5802 1086.9 42.477 1.303
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-31.893 -12.075 -1.949 34.673 642.93 1.9189
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24.76 12.372 3.8614 55.167 1082.7 3.4033
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59.485 -10.842 -23.093 -8.6227 1087.1 2.8645
24.557 -25.797 -38.014 20.416 643.32 1.9007
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57.913 -14.27 -24.592 104.02 1111.6 2.8814
-20.905 -149.31 -152.59 1.364 1087.1 0.76755
-55.851 -164.28 -167.56 30.403 643.44 0.50929
-56.654 -165.36 -168.12 142.42 668.01 0.51381
-21.418 -150.27 -153.03 114.09 1111.7 0.77208
-47.784 4.5774 -1.155 92.288 379.13 1.517
-60.131 0.030011 -3.9661 100.02 101.93 0.51469
-47.38 2.6309 0.63938 377.07 108.83 1.3828
-35.21 7.1025 3.3747 369.21 386.18 2.3851
-69.963 -33.075 -37.434 96.188 375.11 1.7666
-82.099 -37.411 -39.752 103.92 97.853 0.63787
-69.538 -35.253 -35.336 380.92 104.76 1.647
-57.579 -30.992 -33.094 373.06 382.16 2.7757
6.0555 -45.673 -48.715 72.724 379.52 1.4653
7.955 -44.142 -45.51 98.633 102.55 0.53863
4.898 -48.1 -47.615 375.99 127.96 1.3752
3.8378 -49.271 -50.459 350.76 404.31 2.3018
-70.002 -173.55 -174.36 72.54 379.75 0.39262
-69.021 -172.94 -173.3 98.449 103.03 0.14432
-71.061 -174.52 -174.39 376.05 128.44 0.36848
-71.202 -174.77 -175.09 350.82 404.55 0.61677
53.797 9.6144 5.156 288.94 576.22 5.8962
-7.2121 -15.623 -17.961 287.14 297.96 2.6427
48.994 -0.83093 3.3386 564.69 295.27 3.7031
108.88 23.924 25.972 566.4 575.43 6.9566
57.685 17.106 10.624 306.83 559.09 6.4607
-0.46836 -5.2761 -5.8288 305.02 280.51 3.1224
55.61 9.2194 15.343 582.25 277.81 6.0868
112.64 31.118 31.313 583.97 558.3 9.4251
69.178 -12.383 -18.079 247.54 588.13 5.2584
38.784 -22.934 -22.854 274.9 311.04 2.601
68.783 -17.669 -12.275 552.43 338.43 5.4886
97.476 -7.8473 -8.2284 527.01 613.41 8.1459
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-43.348 -159.79 -159.77 284.82 301.33 0.69693
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21.433 -134.73 -134.83 536.45 604.19 2.1827
-21.395 3.7215 -15.656 633.03 155.28 2.4743
-35.244 -2.4408 -22.348 640.81 43.729 1.5683
24.735 20.676 2.5802 1084.3 38.667 1.303
38.701 26.888 9.3233 1076.9 151.44 2.2091
-27.315 -17.768 -13.897 636.87 137.72 2.7288
-39.328 -22.095 -16.308 644.66 26.204 2.1616
21.159 2.2073 9.1291 1088.2 21.142 3.1198
33.29 6.5848 11.59 1080.8 133.88 3.6871
23.075 -38.068 -28.304 614.95 169.51 2.2256
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57.324 -24.388 -13.925 1058.7 197.98 3.3346
-56.952 -167.87 -165.26 615.04 159.58 0.59635
-56.843 -167.57 -164.36 639.93 49.897 0.50269
-21.762 -152.8 -149.41 1083.3 79.172 0.79983
-22.32 -153.3 -150.49 1058.7 188.04 0.8935
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58.813 10.342 16.714 -582.16 279.6 -6.6493
0.40106 -5.1405 -5.4541 -305.61 281.38 -3.3783
58.409 16.916 10.061 -307.35 559.1 -6.7212
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53.52 8.5494 2.1322 -289.37 576.77 -6.5403
-21.024 -152.84 -150.23 -1058.6 188.83 -0.87699
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-55.926 -167.61 -165.14 -615.22 160.64 -0.61874
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23.548 -38.542 -29.295 -615.21 170.64 -2.3092
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-20.887 -149.32 -152.61 -1.4234 1089.2 -0.86987
57.916 -14.46 -24.733 -104.37 1113.7 -3.3629
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24.798 -25.68 -37.731 -20.5 645.61 -2.2408
59.45 -10.929 -23.213 8.5271 1089.1 -3.2464
36.317 13.855 7.6105 -165.79 1091 -4.2118
-27.086 -13.167 -19.059 -163.86 647.52 -3.035
-39.119 -14.962 -23.207 -53.147 640.1 -2.8589
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44.435 18.122 30.405 -147.59 1094.8 -4.069
-18.851 -8.7837 4.0073 -145.67 651.46 -3.1607
-31.287 -11.518 -0.54382 -34.82 644.05 -2.907
32.478 15.592 26.059 -37.014 1087.5 -3.8153
-70.303 -174.46 -174.64 -351.02 406.92 -0.72287
-69.813 -174.05 -173.76 -376.16 131.06 -0.44955
-68.64 -172.76 -173.03 -98.479 105.54 -0.21463
-69.726 -173.43 -174.16 -72.595 382.04 -0.48796
4.7269 -49.153 -49.849 -351.06 406.87 -2.6978
6.1793 -47.779 -46.722 -376.2 130.85 -1.6777
8.4724 -43.882 -44.865 -98.689 105.32 -0.80102
6.4238 -45.511 -48.248 -72.804 381.99 -1.8211
-57.74 -31.574 -32.536 -373.62 383.81 -3.4963
-69.941 -35.836 -34.543 -381.19 106.84 -2.1704
-81.747 -37.107 -38.466 -104 99.333 -1.0427
-69.677 -32.901 -36.516 -96.34 376.35 -2.3686
-35.196 6.1082 4.9279 -369.65 387.79 -3.7028
-47.331 1.9119 3.0749 -377.22 110.78 -2.2883
-59.004 0.95089 -0.7153 -100.07 103.27 -1.1166
-47 5.0912 1.0816 -92.408 380.33 -2.5312
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53.901 2.435 8.2486 -576.42 289.11 -6.4529
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53.52 8.5494 2.1322 -297.46 564.29 -6.5403
115.24 31.722 31.552 -557.4 583.48 -9.9922
58.813 10.342 16.714 -558.9 307.23 -6.6493
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58.409 16.916 10.061 -279.49 581.96 -6.7212
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69.629 -17.912 -12.725 -588.65 247.42 -5.3009
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-9.3577 -145.96 -147.44 -329.16 561.18 -1.4344
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32.95 26.748 15.053 -1086.9 36.881 -3.4793
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-26.682 -18.063 -13.282 -647.12 163.74 -2.9677
58.184 -24.39 -14.659 -1112.6 104 -3.273
59.688 -22.92 -11.261 -1088 -8.7903 -3.0305
24.95 -37.115 -25.941 -644.5 20.099 -2.0668
23.548 -38.542 -29.295 -669.3 132.19 -2.3092
-21.024 -152.84 -150.23 -1112.7 114 -0.87699
-20.578 -152.43 -149.31 -1088 1.2389 -0.81203
-55.583 -167.25 -164.25 -644.49 30.128 -0.55379
-55.926 -167.61 -165.14 -669.29 142.19 -0.61874
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-18.851 -8.7837 4.0073 -157.16 633.05 -3.1607
-31.287 -11.518 -0.54382 -46.324 640.46 -2.907
32.478 15.592 26.059 -44.13 1083.8 -3.8153
36.317 13.855 7.6105 -137.05 1080.2 -4.2118
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24.762 12.265 3.6672 -25.802 1087.6 -4.0356
57.916 -14.46 -24.733 -198.46 1057.6 -3.3629
23.321 -29.186 -39.227 -170.17 614.29 -2.3573
24.798 -25.68 -37.731 -60.643 638.9 -2.2408
59.45 -10.929 -23.213 -89.671 1082.1 -3.2464
-21.317 -150.28 -153.03 -188.52 1057.6 -0.90109
-56.041 -165.13 -167.82 -160.23 614.3 -0.63165
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-20.887 -149.32 -152.61 -79.72 1082.1 -0.86987
-35.196 6.1082 4.9279 -387.43 369.29 -3.7028
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4.7269 -49.153 -49.849 -406.02 350.2 -2.6978
6.1793 -47.779 -46.722 -380.88 72.013 -1.6777
8.4724 -43.882 -44.865 -104.17 97.537 -0.80102
6.4238 -45.511 -48.248 -130.05 375.09 -1.8211
-70.303 -174.46 -174.64 -406.06 350.16 -0.72287
-69.813 -174.05 -173.76 -380.92 71.795 -0.44955
-68.64 -172.76 -173.03 -104.38 97.319 -0.21463
-69.726 -173.43 -174.16 -130.26 375.04 -0.48796
-------------- next part --------------
import gmsh
import math
model = gmsh.model
factory = model.occ
# spin up gmsh API
gmsh.initialize()
gmsh.option.setNumber("General.Terminal", 1)
# read in the stresses as arrays of floats
# -> assume 15 sigdigs is enough
with open("gauss-stress.txt") as file:
six_stresses = [[float(val) for val in line.split()] for line in file]
# have to repeat stress values to properly call the addModelData function
# -> it expects vector of length 9 instead of the vector of length six we've
# read in so far
#
# want to take the each array in six_stresses ([sx, sy, sz, sxy, sxz, syz])
# and transform it to an array like this: [sx, sxy, sxz, sxy, sy, syz, sxz, syz, sz]
# there is probably a better way to do this...
stress_tensor = []
for stress_line in six_stresses:
(sx, sy, sz, sxy, sxz, syz) = tuple(stress_line)
stress_tensor.append([sx, sxy, sxz, sxy, sy, syz, sxz, syz, sz])
# read in the node forces
node_forces = []
data_stride = 3
with open("nodal-forces.txt") as file:
elt_forces = [[float(val) for val in line.split()] for line in file]
# remove elt number (not needed here)
for sublist in elt_forces:
sublist.pop(0)
# transpose elt forces (array of arrays of 24 elts)
# to node forces (array of arrays of 3 elts)
flat_elt_forces = [forces for sublist in elt_forces for forces in sublist]
i = 0
while i < len(flat_elt_forces):
node_forces.append(flat_elt_forces[i:i + data_stride])
i = i + data_stride
# --
# import the mesh
gmsh.open("10cm.msh")
# find element & node tags
# -> exit if the type isn't hexa (5) as a quick precaution
(elt_types, elt_tags, node_tags) = gmsh.model.mesh.getElements()
hexa_type = 5 # (c.f. section 9.1 gmsh documentation)
if len(elt_types) != 1 or elt_types[0] != hexa_type:
quit()
# comes back as array of arrays, get the nodes as a bare array of ints
elt_tags = elt_tags[0]
node_tags = node_tags[0]
# --
# get the model name
model_names = gmsh.model.list()
curr_model = model_names[0]
# add the stress data
# make a stress view tag
stress_view_tag = gmsh.view.add("node stresses")
# (c.f. the gmsh.py header)
# >> def addModelData(tag, step, modelName, dataType, tags, data, time=0., numComponents=-1, partition=0)
gmsh.view.addModelData(stress_view_tag, 0, curr_model, "NodeData", node_tags, stress_tensor)
# make a view for the node forces
force_view_tag = gmsh.view.add("node forces")
# add the forces
gmsh.view.addModelData(force_view_tag, 0, curr_model, "NodeData", node_tags, node_forces)
# --
# output the data
out_filename = "10cm_data.msh"
# save as new mesh file
# first we save the stresses
# @arg False -> don't want to append for first view
gmsh.view.write(stress_view_tag, out_filename, False)
# node force output
# @arg True -> want to append (otherwise would overwrite the stress data)
gmsh.view.write(force_view_tag, out_filename, True)
# close gmsh
gmsh.finalize();
-------------- next part --------------
1 240.35 -46679 2954.6 -69667 1399 27953 9709 -23286 76483 79916 -71743 51212 -9502.5 12194 -37756 -79674 32524 -62639 -677.85 58345 -41234 69656 37247 -16974
2 9819.7 -29227 20174 -65597 -20238 45829 8565.6 -44803 55326 83906 -53598 29917 -11479 23837 -26542 -83990 24641 -50924 -6844 49962 -49245 65619 49425 -24536
3 -1.0991e+05 -26831 94364 -1.6481e+05 15694 1.3606e+05 1.3941e+05 6034.3 1.7851e+05 1.3455e+05 -36806 1.3952e+05 -1.1347e+05 -1098.3 -1.2614e+05 -1.6026e+05 11288 -1.6418e+05 1.4376e+05 22412 -1.4944e+05 1.3074e+05 9306.9 -1.0869e+05
4 -1.0066e+05 -10978 1.1286e+05 -1.6944e+05 -11177 1.5623e+05 1.3001e+05 -20355 1.5539e+05 1.3856e+05 -20005 1.1702e+05 -1.0875e+05 10503 -1.1516e+05 -1.6265e+05 10082 -1.519e+05 1.3957e+05 20603 -1.5816e+05 1.3337e+05 21327 -1.163e+05
5 1.0007e+05 -1.3539e+05 -6943.8 -1.3508e+05 -90320 3087.6 -1.3045e+05 -1.3129e+05 45912 1.6499e+05 -1.7376e+05 35551 96342 1.038e+05 -20882 -1.3894e+05 1.2088e+05 -30443 -1.2629e+05 1.6035e+05 -17525 1.6935e+05 1.4573e+05 -8758.4
6 1.1007e+05 -1.1685e+05 7938.1 -1.305e+05 -1.1293e+05 19107 -1.3978e+05 -1.5424e+05 19514 1.6062e+05 -1.5391e+05 8758.4 1.0132e+05 1.1472e+05 -10462 -1.3622e+05 1.1356e+05 -19363 -1.3144e+05 1.5222e+05 -17754 1.6591e+05 1.5743e+05 -7738.7
7 -9174.8 -71388 38490 -1.3941e+05 -30879 64993 6.9122e-11 -56147 1.0377e+05 1.3045e+05 -94905 79008 -7474.8 44370 -65508 -1.3021e+05 55769 -88748 16293 81972 -77887 1.3952e+05 71210 -54119
8 -271.17 -55160 54421 -1.4357e+05 -57825 82796 -16293 -81972 77887 1.2654e+05 -77327 52130 2979.6 55133 -55078 -1.2638e+05 54392 -76829 13951 79995 -80393 1.4303e+05 82764 -54933
9 11479 -26159 23455 -66000 -25356 49069 6844 -50031 50749 84371 -50568 25461 -9819.7 20770 -29823 -84393 29759 -54164 -8565.6 55190 -44667 66084 46396 -20079
10 9502.5 -37803 12241 -70316 -17473 37354 677.85 -41649 58760 80334 -62746 33023 -240.35 3317.7 -47042 -80323 51396 -72041 -9709 76707 -23510 70074 28250 1215.8
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