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Description
🔍 Before submitting the issue
- I have searched among the existing issues
- I am using a Python virtual environment
🐞 Description of the bug
For some reason the results from PyMAPDL-reader are not the same as from mapdl in batch mode, though the stress order of magnitude is somewhat similar.
PyMAPDL-Reader Software and Environment Report
Date: Tue Dec 20 16:54:15 2022 CET
OS : Linux
CPU(s) : 24
Machine : x86_64
Architecture : 64bit
RAM : 1511.6 GiB
Environment : Python
File system : xfs
GPU Details : error
Python 3.7.13 (default, Apr 28 2022, 08:00:21) [GCC 8.2.0]
pyvista : 0.37.0
vtk : 9.2.2
numpy : 1.21.6
appdirs : 1.4.4
ansys.mapdl.reader : 0.52.4
tqdm : 4.64.1
matplotlib : 3.5.3
ansys.mapdl.core : 0.63.4
scipy : 1.7.3
example output:
PyMAPDL:
1086208 -0.53896 -4.5807 -0.43128E-001-0.95561 0.18610 0.17292E-001
1119277 7.6786 -54.789 9.1757 -13.006 8.5357 -6.9634
1119278 4.7530 -73.017 8.5624 -4.3764 -0.73627E-002 -2.2960
1119279 3.6917 -67.506 8.3602 2.9245 0.59262 -1.8712
1119280 6.1982 -75.804 3.4671 4.7029 -9.1468 0.43384
1119281 9.2134 -68.473 4.5270 -7.7405 -19.154 -2.3560
1119282 -2.2331 -82.818 -0.80377 -0.80763 -4.6933 -0.82316
1119283 -11.522 -223.40 -41.927 89.056 -114.62 -16.256
1119284 -4.2330 -68.573 -0.96242 1.3523 -7.9288 -1.9489
1119285 7.4691 -71.456 10.541 -11.240 -11.949 -4.9047
mapdl:
1086208 -0.538961 -4.58073 -0.0431284 -0.955614 0.186102 0.0172916
1119277 0.936085 -74.7439 2.06109 -5.03342 -3.35435 -5.49832
1119278 0.585308 -84.0512 3.4786 -4.43145 -9.51501 -2.02587
1119279 2.5793 -79.4133 2.91215 -1.75299 -6.42161 -1.47082
1119280 2.9808 -89.1512 0.283342 -4.16926 -8.42763 -0.116176
1119281 7.15402 -74.3251 4.08113 -9.16976 -13.1968 -1.89268
1119282 -2.37682 -88.1327 0.234747 0.23904 -3.91442 0.441464
1119283 -4.29061 -172.119 -31.7608 84.6058 -99.442 -11.1323
1119284 -3.617 -67.7072 -0.313461 0.521451 -7.62063 -1.82923
1119285 1.89622 -83.4006 6.06942 0.206192 -11.354 -1.41076
📝 Steps to reproduce
I am extracting stress using PyMAPDL Reader (v2022, python 3.7, virtual environment). Reading a result file (generated by v18) into a Result Class, and then using "nodal_stress" method on the result class.
Then I compare the output with older output that was generated using an APDL script, using mapdl v18 in batch mode. Using the same result file. Using "PRNSOL,S,COMP".
Using only corner nodes on outside surfaces of solid-element components
💻 Which operating system are you using?
Linux
🐍 Which Python version are you using?
3.7
📦 Installed packages
aiohttp==3.8.3
aiosignal==1.3.1
ansys-api-mapdl==0.5.1
ansys-api-platform-instancemanagement==1.0.0b3
ansys-corba==0.1.1
ansys-dpf-core==0.7.1
ansys-dpf-gate==0.3.0
ansys-dpf-gatebin==0.3.0
ansys-dpf-post==0.2.5
ansys-grpc-dpf==0.7.0
ansys-mapdl-core==0.63.4
ansys-mapdl-reader==0.52.4
ansys-platform-instancemanagement==1.0.2
appdirs==1.4.4
async-timeout==4.0.2
asynctest==0.13.0
attrs==22.1.0
cachetools==5.2.0
certifi==2022.12.7
charset-normalizer==2.1.1
cycler==0.11.0
fonttools==4.38.0
frozenlist==1.3.3
geomdl==5.3.1
google-api-core==2.11.0
google-api-python-client==2.70.0
google-auth==2.15.0
google-auth-httplib2==0.1.0
googleapis-common-protos==1.57.0
grpcio==1.51.1
httplib2==0.21.0
idna==3.4
imageio==2.22.4
importlib-metadata==5.1.0
kiwisolver==1.4.4
matplotlib==3.5.3
multidict==6.0.3
numpy==1.21.6
packaging==22.0
pexpect==4.8.0
Pillow==9.3.0
pooch==1.6.0
protobuf==3.20.3
protoc-gen-swagger==0.1.0
psutil==5.9.4
ptyprocess==0.7.0
pyasn1==0.4.8
pyasn1-modules==0.2.8
pyiges==0.2.1
pyparsing==3.0.9
python-dateutil==2.8.2
pyvista==0.37.0
requests==2.28.1
rsa==4.9
scipy==1.7.3
scooby==0.7.0
six==1.16.0
tqdm==4.64.1
typing_extensions==4.4.0
uritemplate==4.1.1
urllib3==1.26.13
vtk==9.2.2
wslink==1.9.2
yarl==1.8.2
zipp==3.11.0