OP2 Demo¶
The iPython notebook for this demo can be found in: - docs:raw-latex:quick_start:raw-latex:demo:raw-latex:`op`2_demo.ipynb - https://github.com/SteveDoyle2/pyNastran/tree/master/docs/quick_start/demo/op2_demo.ipynb
Why use the OP2? Why not use the F06/PCH file?¶
Most people are comfortable with the F06. However, it’s: - Ironically, a lot harder to parse. The OP2 is very structured. - Much, much, much slower. We can read entire blocks of arrays with a single call. The data is already typed. - Much, much more memory inefficient because we aren’t appending strings onto lists and turning that into a numpy array.
F06 parsers get ridiculously hard when you start do complicated results, like: - single subcase buckling - superelements - SOL 200 optimization with sub-optimization - SPOINTs
The pyNastran OP2 Reader is fast, highly validated, and it supports most result types. The data in the OP2 is also more accurate because there is no rounding.
Validating an OP2¶
The test_op2 script is created when you run
python setup.py develop or python setup.py install on pyNastran.
Assuming it’s on your path (it’ll be in Python27:raw-latex:`Scripts `or
something similar), you can run:
>>> test_op2 -f solid_bending.op2
The -f tells us to print out solid_bending.test_op2.f06, which
can be compared to your F06 for a small file to build confidence in the
reader. It’s also useful when you want an F06 of your model without
rerunning Nastran just to see what’s in it.
If you have a large model, you can make test_op2 run much, much
faster. The -c flag disables double-reading of the OP2. By default,
test_op2 uses two different read methods (the old method and new
method) to ensure that results are read in properly. When running the
code, this is turned off, but is turned on for test_op2.
>>> test_op2 -fc solid_bending.op2
Import the packages¶
import os
import copy
import numpy as np
import pyNastran
pkg_path = pyNastran.__path__[0]
from pyNastran.utils import print_bad_path
from pyNastran.op2.op2 import read_op2
from pyNastran.utils import object_methods, object_attributes
import pandas as pd
Sets default precision of real numbers for pandas output¶
pd.set_option('precision', 3)
np.set_printoptions(precision=3, threshold=20)
As with the BDF, we can use the long form and the short form. However,
the long form for the OP2 doesn’t really add anything. So, let’s
just use the short form.
Besides massive speed improvements in the OP2 relative to v0.7, this
version adds pandas dataframe support.
#op2_filename = r'D:\work\pynastran_0.8.0\models\iSat\ISat_Launch_Sm_Rgd.op2'
#op2_filename = r'D:\work\pynastran_0.8.0\models\iSat\ISat_Launch_Sm_4pt.op2'
op2_filename = os.path.abspath(os.path.join(pkg_path, '..', 'models', 'iSat', 'ISat_Launch_Sm_4pt.op2'))
assert os.path.exists(op2_filename), print_bad_path(op2_filename)
# define the input file with a file path
op2 = read_op2(op2_filename, build_dataframe=True, debug=False)
INFO: fname=op2_scalar.py lineNo=1176 op2_filename = 'f:\work\pynastran\pynastran\master3\models\iSat\ISat_Launch_Sm_4pt.op2'
OP2 Introspection¶
The get_op2_stats() function lets you quickly understand what in an
op2.
print(op2.get_op2_stats())
GridPointWeight: reference_point=0
mass=[ 1.7746 1.7746 1.7746]
cg =[-1.02627e-17 -2.53061 -18.4676]
[-0.0338509 -1.63349e-17 -18.4676]
[-0.0338509 -2.53061 -2.18142e-19]
IS =[ 705.69 -1.56671 0.141187]
[ -1.56671 621.838 135.836]
[ 0.141187 135.836 415.861]
IQ =[ 689.183 ]
[ 348.384 ]
[ 705.821]
Q = [ 0.0884636 0.00159685 0.996078]
[ -0.892013 -0.444886 0.0799345]
[ 0.443269 -0.895586 -0.0379318]
eigenvectors[1]
isubcase = 1
type=RealEigenvectorArray ntimes=167 nnodes=5379
data: [t1, t2, t3, r1, r2, r3] shape=[167, 5379, 6] dtype=float32
gridTypes
sort1
modes = [ 1 2 3 ..., 165 166 167]
eigrs = [ 2.758e+03 3.568e+03 9.686e+03 ..., 6.163e+06 6.170e+06
6.230e+06]
mode_cycles = [1112674317 1114566525 1120195719 ..., 1159407589 1159413465 1159462558]
cbar_force[1]
type=RealCBarForceArray ntimes=167 nelements=827
data: [ntimes, nnodes, 8] where 8=[bending_moment_a1, bending_moment_a2, bending_moment_b1, bending_moment_b2, shear1, shear2, axial, torque]
data.shape = (167, 827, 8)
element name: CBAR-34
sort1
modes = [ 1 2 3 ..., 165 166 167]
eigrs = [ 2.758e+03 3.568e+03 9.686e+03 ..., 6.163e+06 6.170e+06
6.230e+06]
cycles = [ 8.358 9.507 15.663 ..., 395.101 395.329 397.237]
ctria3_stress[1]
type=RealPlateStressArray ntimes=167 nelements=32 nnodes_per_element=1 nlayers=2 ntotal=64
data: [ntimes, ntotal, 8] where 8=[fiber_distance, oxx, oyy, txy, angle, omax, omin, von_mises]
data.shape=(167L, 64L, 8L)
element type: CTRIA3
s_code: 1
sort1
modes = [ 1 2 3 ..., 165 166 167]
eigrs = [ 2.758e+03 3.568e+03 9.686e+03 ..., 6.163e+06 6.170e+06
6.230e+06]
mode2s = [ 2 3 4 ..., 166 167 1159462558]
cycles = [ 2.803e-45 4.204e-45 5.605e-45 ..., 2.326e-43 2.340e-43
2.496e+03]
cquad4_stress[1]
type=RealPlateStressArray ntimes=167 nelements=4580 nnodes_per_element=1 nlayers=2 ntotal=9160
data: [ntimes, ntotal, 8] where 8=[fiber_distance, oxx, oyy, txy, angle, omax, omin, von_mises]
data.shape=(167L, 9160L, 8L)
element type: CQUAD4
s_code: 1
sort1
modes = [ 1 2 3 ..., 165 166 167]
eigrs = [ 2.758e+03 3.568e+03 9.686e+03 ..., 6.163e+06 6.170e+06
6.230e+06]
mode2s = [ 2 3 4 ..., 166 167 1159462558]
cycles = [ 2.803e-45 4.204e-45 5.605e-45 ..., 2.326e-43 2.340e-43
2.496e+03]
eigenvalues[ISAT_SM_LAUNCH_4PT MODES TO 400 HZ]
type=RealEigenvalues neigenvalues=167
title, extraction_order, eigenvalues, radians, cycles, generalized_mass, generalized_stiffness
If that’s too long...¶
print(op2.get_op2_stats(short=True))
GridPointWeight: ref_point=0 mass=1.7746; [reference_point, M0, S, mass, cg, IS, IQ, Q]
eigenvectors[1]
cbar_force[1]
ctria3_stress[1]
cquad4_stress[1]
eigenvalues[u'ISAT_SM_LAUNCH_4PT MODES TO 400 HZ']
Acccessing the Eigenvectors object¶
Eigenvectors are the simplest object. They use the same class as for displacements, velocity, acceleration, SPC Forces, MPC Forces, Applied Loads, etc. These are all node-based tables with TX, TY, TZ, RX, RY, RZ. Results are in the analysis coordinate frame (CD), which is defined by the GRID card.
Numpy-based Approach¶
We’ll first show off the standard numpy based results on a transient
case. Static results are the same, except that you’ll always use the 0th
index for the “time” index.
The tutorial is intetionally just accessing the objects in a very clear, though inefficient way. The OP2 objects can take full advantage of the numpy operations.
# what modes did we analyze: 1 to 167
print("loadcases = %s" % op2.eigenvectors.keys())
# get subcase 1
eig1 = op2.eigenvectors[1]
modes = eig1.modes
times = eig1._times # the generic version of modes
print("modes = %s\n" % modes)
print("times = %s\n" % times)
imode2 = 1 # corresponds to mode 2
mode2 = eig1.data[imode2, :, :]
print('first 10 nodes and grid types\nNid Gridtype\n%s' % eig1.node_gridtype[:10, :])
node_ids = eig1.node_gridtype[:, 0]
index_node10 = np.where(node_ids == 10)[0] # we add the [0] because it's 1d
mode2_node10 = mode2[index_node10]
print("translation mode2_node10 = %s" % eig1.data[imode2, index_node10, :3].ravel())
print("rotations mode2_node10 = %s" % eig1.data[imode2, index_node10, 3:].ravel())
loadcases = [1]
modes = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167]
times = [ 1. 2. 3. ..., 165. 166. 167.]
first 10 nodes and grid types
Nid Gridtype
[[ 1 1]
[ 2 1]
[ 3 1]
[ 4 1]
[ 5 1]
[ 6 1]
[ 7 1]
[ 8 1]
[ 9 1]
[10 1]]
translation mode2_node10 = [ 1.696e-05 7.937e-03 1.510e-03]
rotations mode2_node10 = [ -2.241e-04 1.228e-06 -1.187e-06]
Pandas-based Approach¶
If you like pandas, you can access all the OP2 objects, which is very useful within the Jupyter Notebook. Different objects will look differently, but you can change the layout.
If you’re trying to learn pandas, there are many tutorials online, such as: http://pandas.pydata.org/pandas-docs/stable/10min.html
or a very long, but good video:
from IPython.display import YouTubeVideo
YouTubeVideo('5JnMutdy6Fw')
#https://www.youtube.com/watch?v=5JnMutdy6Fw
# get subcase 1
eig1 = op2.eigenvectors[1]
eig1.data_frame
| Mode | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | ... | 158 | 159 | 160 | 161 | 162 | 163 | 164 | 165 | 166 | 167 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| EigenvalueReal | 2757.896 | 3568.136 | 9685.530 | 16154.883 | 16278.047 | 16668.713 | 18248.492 | 18591.637 | 18617.254 | 31930.465 | ... | 5782436.500 | 5860846.500 | 5920603.000 | 6020617.500 | 6035178.000 | 6037030.000 | 6102521.500 | 6162773.500 | 6169898.500 | 6229584.500 | |
| Freq | 8.358 | 9.507 | 15.663 | 20.229 | 20.306 | 20.548 | 21.500 | 21.701 | 21.716 | 28.440 | ... | 382.715 | 385.301 | 387.260 | 390.518 | 390.990 | 391.050 | 393.165 | 395.101 | 395.329 | 397.237 | |
| Radians | 52.516 | 59.734 | 98.415 | 127.102 | 127.585 | 129.107 | 135.087 | 136.351 | 136.445 | 178.691 | ... | 2404.670 | 2420.919 | 2433.229 | 2453.695 | 2456.660 | 2457.037 | 2470.328 | 2482.493 | 2483.928 | 2495.914 | |
| NodeID | Item | |||||||||||||||||||||
| 1 | t1 | 5.548e-03 | 4.671e-06 | -1.818e-04 | -5.670e-02 | 1.722e-04 | -4.175e-02 | 8.632e-05 | -1.341e-03 | 1.582e-03 | -2.428e-01 | ... | 5.723e-02 | -5.369e-02 | -3.838e-02 | -1.326e-01 | -1.973e-02 | 0.028 | 0.033 | -0.104 | -6.919e-02 | -1.904e-02 |
| t2 | -2.133e-04 | 5.699e-03 | 2.392e-02 | 5.801e-04 | -1.812e-04 | 1.971e-04 | -6.526e-05 | -3.563e-02 | -3.164e-02 | -1.292e-02 | ... | -3.090e-01 | -3.746e-01 | -5.840e-02 | -2.385e-02 | -5.889e-02 | 0.015 | 0.177 | -0.010 | 5.252e-02 | 1.187e-01 | |
| t3 | 8.469e-04 | 1.512e-03 | 7.038e-03 | -8.160e-03 | -1.385e-03 | -6.209e-03 | 1.004e-04 | -9.286e-03 | -7.856e-03 | -3.743e-02 | ... | -4.535e-02 | 1.271e-01 | 2.550e-01 | -1.792e-01 | -1.136e-03 | 0.042 | -0.037 | 0.263 | 2.141e-01 | -1.473e-01 | |
| r1 | 8.399e-06 | -2.241e-04 | -1.035e-03 | -4.509e-05 | 6.317e-05 | -9.634e-06 | 2.518e-06 | 1.322e-03 | 1.172e-03 | 5.440e-04 | ... | -3.061e-02 | -9.829e-04 | 2.993e-02 | -3.527e-02 | 1.148e-04 | 0.007 | -0.053 | -0.004 | 2.357e-02 | -3.403e-02 | |
| r2 | 2.507e-04 | 1.228e-06 | -8.742e-06 | -2.571e-03 | 6.180e-06 | -1.767e-03 | 3.812e-06 | -5.683e-05 | 5.614e-05 | -1.004e-02 | ... | -1.174e-02 | 1.241e-03 | 1.025e-02 | -3.112e-02 | -4.135e-03 | 0.011 | 0.026 | 0.009 | 7.311e-03 | -9.083e-04 | |
| r3 | 5.261e-05 | -1.187e-06 | -1.986e-04 | -1.310e-04 | -2.860e-05 | -4.676e-05 | -1.092e-07 | -1.774e-04 | 1.806e-04 | 1.011e-03 | ... | 4.109e-05 | 2.184e-02 | 2.495e-03 | 8.832e-02 | 1.660e-02 | -0.030 | -0.100 | 0.022 | 2.547e-02 | -5.581e-03 | |
| 2 | t1 | 5.548e-03 | 4.671e-06 | -1.818e-04 | -5.670e-02 | 1.722e-04 | -4.175e-02 | 8.632e-05 | -1.341e-03 | 1.582e-03 | -2.428e-01 | ... | 5.723e-02 | -5.369e-02 | -3.838e-02 | -1.326e-01 | -1.973e-02 | 0.028 | 0.033 | -0.104 | -6.919e-02 | -1.904e-02 |
| t2 | -1.081e-04 | 5.696e-03 | 2.353e-02 | 3.180e-04 | -2.384e-04 | 1.036e-04 | -6.548e-05 | -3.598e-02 | -3.128e-02 | -1.090e-02 | ... | -3.090e-01 | -3.309e-01 | -5.341e-02 | 1.528e-01 | -2.568e-02 | -0.045 | -0.022 | 0.034 | 1.035e-01 | 1.075e-01 | |
| t3 | 3.455e-04 | 1.510e-03 | 7.055e-03 | -3.018e-03 | -1.398e-03 | -2.676e-03 | 9.274e-05 | -9.172e-03 | -7.968e-03 | -1.735e-02 | ... | -2.187e-02 | 1.246e-01 | 2.345e-01 | -1.170e-01 | 7.135e-03 | 0.020 | -0.090 | 0.244 | 1.995e-01 | -1.454e-01 | |
| r1 | 8.399e-06 | -2.241e-04 | -1.035e-03 | -4.509e-05 | 6.317e-05 | -9.634e-06 | 2.518e-06 | 1.322e-03 | 1.172e-03 | 5.440e-04 | ... | -3.061e-02 | -9.829e-04 | 2.993e-02 | -3.527e-02 | 1.148e-04 | 0.007 | -0.053 | -0.004 | 2.357e-02 | -3.403e-02 | |
| r2 | 2.507e-04 | 1.228e-06 | -8.742e-06 | -2.571e-03 | 6.180e-06 | -1.767e-03 | 3.812e-06 | -5.683e-05 | 5.614e-05 | -1.004e-02 | ... | -1.174e-02 | 1.241e-03 | 1.025e-02 | -3.112e-02 | -4.135e-03 | 0.011 | 0.026 | 0.009 | 7.311e-03 | -9.083e-04 | |
| r3 | 5.261e-05 | -1.187e-06 | -1.986e-04 | -1.310e-04 | -2.860e-05 | -4.676e-05 | -1.092e-07 | -1.774e-04 | 1.806e-04 | 1.011e-03 | ... | 4.109e-05 | 2.184e-02 | 2.495e-03 | 8.832e-02 | 1.660e-02 | -0.030 | -0.100 | 0.022 | 2.547e-02 | -5.581e-03 | |
| 3 | t1 | 6.169e-03 | 7.911e-06 | -2.160e-04 | -6.310e-02 | 1.897e-04 | -4.617e-02 | 9.580e-05 | -1.466e-03 | 1.704e-03 | -2.679e-01 | ... | 2.695e-02 | -6.243e-02 | -6.576e-03 | -2.369e-01 | -3.571e-02 | 0.065 | 0.135 | -0.079 | -5.365e-02 | -2.056e-02 |
| t2 | -2.295e-04 | 6.255e-03 | 2.639e-02 | 6.019e-04 | -2.806e-04 | 1.856e-04 | -7.132e-05 | -3.892e-02 | -3.453e-02 | -1.453e-02 | ... | -1.994e-01 | -3.102e-01 | -1.168e-01 | 1.054e-01 | -4.058e-02 | -0.023 | 0.200 | 0.023 | 1.385e-02 | 1.724e-01 | |
| t3 | 8.457e-04 | 1.512e-03 | 7.034e-03 | -8.138e-03 | -1.386e-03 | -6.198e-03 | 1.003e-04 | -9.286e-03 | -7.856e-03 | -3.736e-02 | ... | -4.493e-02 | 1.259e-01 | 2.542e-01 | -1.777e-01 | -1.024e-03 | 0.042 | -0.038 | 0.262 | 2.140e-01 | -1.467e-01 | |
| r1 | 8.883e-06 | -2.240e-04 | -1.036e-03 | -5.241e-05 | 6.649e-05 | -6.664e-06 | 2.507e-06 | 1.321e-03 | 1.174e-03 | 5.725e-04 | ... | -3.039e-02 | 2.253e-04 | 2.894e-02 | -3.716e-02 | -4.793e-04 | 0.008 | -0.047 | -0.006 | 2.042e-02 | -3.308e-02 | |
| r2 | 2.507e-04 | 1.229e-06 | -8.748e-06 | -2.571e-03 | 6.181e-06 | -1.767e-03 | 3.812e-06 | -5.683e-05 | 5.614e-05 | -1.004e-02 | ... | -1.174e-02 | 1.238e-03 | 1.025e-02 | -3.111e-02 | -4.135e-03 | 0.011 | 0.026 | 0.009 | 7.308e-03 | -9.065e-04 | |
| r3 | 4.657e-05 | 2.289e-06 | -8.563e-06 | -2.151e-05 | 8.189e-06 | 1.310e-05 | -1.439e-07 | -1.571e-04 | 1.600e-04 | 1.240e-03 | ... | 6.409e-03 | -2.870e-02 | 6.276e-03 | -3.529e-02 | -1.277e-02 | 0.016 | 0.091 | -0.024 | -3.187e-02 | 1.810e-03 | |
| 4 | t1 | 6.169e-03 | 7.956e-06 | -2.157e-04 | -6.310e-02 | 1.907e-04 | -4.617e-02 | 9.580e-05 | -1.466e-03 | 1.704e-03 | -2.679e-01 | ... | 2.726e-02 | -6.325e-02 | -6.637e-03 | -2.366e-01 | -3.568e-02 | 0.065 | 0.135 | -0.079 | -5.359e-02 | -2.070e-02 |
| t2 | -1.295e-04 | 6.253e-03 | 2.619e-02 | 4.724e-04 | -3.533e-04 | 1.577e-04 | -7.179e-05 | -3.925e-02 | -3.419e-02 | -1.184e-02 | ... | -1.877e-01 | -3.177e-01 | -1.326e-01 | 1.642e-01 | -3.435e-02 | -0.035 | 0.187 | 0.006 | 6.929e-04 | 1.884e-01 | |
| t3 | 3.469e-04 | 1.510e-03 | 7.059e-03 | -3.040e-03 | -1.396e-03 | -2.688e-03 | 9.276e-05 | -9.173e-03 | -7.968e-03 | -1.742e-02 | ... | -2.215e-02 | 1.256e-01 | 2.349e-01 | -1.179e-01 | 7.068e-03 | 0.020 | -0.089 | 0.243 | 1.992e-01 | -1.457e-01 | |
| r1 | 7.731e-06 | -2.241e-04 | -1.037e-03 | -3.840e-05 | 6.177e-05 | -1.181e-05 | 2.531e-06 | 1.322e-03 | 1.169e-03 | 5.129e-04 | ... | -3.086e-02 | -3.467e-03 | 3.029e-02 | -3.335e-02 | 6.161e-04 | 0.007 | -0.058 | -0.003 | 2.650e-02 | -3.497e-02 | |
| r2 | 2.507e-04 | 1.229e-06 | -8.746e-06 | -2.571e-03 | 6.177e-06 | -1.767e-03 | 3.812e-06 | -5.682e-05 | 5.614e-05 | -1.004e-02 | ... | -1.174e-02 | 1.238e-03 | 1.026e-02 | -3.112e-02 | -4.135e-03 | 0.011 | 0.026 | 0.010 | 7.313e-03 | -9.084e-04 | |
| r3 | 4.712e-05 | 2.923e-07 | 5.697e-05 | -2.570e-05 | 3.632e-06 | 1.221e-05 | -1.684e-07 | -1.412e-04 | 1.769e-04 | 1.298e-03 | ... | 1.457e-02 | -1.664e-02 | 4.624e-03 | -3.608e-02 | -1.077e-02 | 0.016 | 0.083 | -0.026 | -3.403e-02 | 3.453e-04 | |
| 5 | t1 | 6.801e-03 | 1.081e-05 | -2.255e-04 | -6.955e-02 | 2.031e-04 | -5.058e-02 | 1.054e-04 | -1.626e-03 | 1.863e-03 | -2.930e-01 | ... | -1.463e-03 | -4.748e-02 | 1.290e-02 | -2.882e-01 | -4.040e-02 | 0.084 | 0.165 | -0.056 | -3.263e-02 | -2.358e-02 |
| t2 | -2.553e-04 | 6.819e-03 | 2.910e-02 | 8.055e-04 | -4.971e-04 | 2.453e-04 | -7.785e-05 | -4.223e-02 | -3.750e-02 | -1.564e-02 | ... | -1.560e-01 | -3.697e-01 | -2.080e-01 | 1.525e-01 | -5.946e-02 | -0.022 | 0.442 | 0.012 | -6.531e-02 | 2.889e-01 | |
| t3 | 8.469e-04 | 1.512e-03 | 7.038e-03 | -8.160e-03 | -1.385e-03 | -6.209e-03 | 1.004e-04 | -9.286e-03 | -7.856e-03 | -3.743e-02 | ... | -4.535e-02 | 1.271e-01 | 2.550e-01 | -1.792e-01 | -1.136e-03 | 0.042 | -0.037 | 0.263 | 2.141e-01 | -1.473e-01 | |
| r1 | 8.399e-06 | -2.241e-04 | -1.035e-03 | -4.509e-05 | 6.317e-05 | -9.634e-06 | 2.518e-06 | 1.322e-03 | 1.172e-03 | 5.440e-04 | ... | -3.061e-02 | -9.829e-04 | 2.993e-02 | -3.527e-02 | 1.148e-04 | 0.007 | -0.053 | -0.004 | 2.357e-02 | -3.403e-02 | |
| r2 | 2.507e-04 | 1.228e-06 | -8.742e-06 | -2.571e-03 | 6.180e-06 | -1.767e-03 | 3.812e-06 | -5.683e-05 | 5.614e-05 | -1.004e-02 | ... | -1.174e-02 | 1.241e-03 | 1.025e-02 | -3.112e-02 | -4.135e-03 | 0.011 | 0.026 | 0.009 | 7.311e-03 | -9.083e-04 | |
| r3 | 5.261e-05 | -1.187e-06 | -1.986e-04 | -1.310e-04 | -2.860e-05 | -4.676e-05 | -1.092e-07 | -1.774e-04 | 1.806e-04 | 1.011e-03 | ... | 4.109e-05 | 2.184e-02 | 2.495e-03 | 8.832e-02 | 1.660e-02 | -0.030 | -0.100 | 0.022 | 2.547e-02 | -5.581e-03 | |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 5629 | t1 | -7.413e-05 | -8.245e-05 | -3.907e-04 | 3.482e-03 | 3.748e-05 | 2.988e-04 | -2.694e-06 | 2.441e-05 | 1.075e-03 | 2.742e-03 | ... | 4.748e-04 | 5.261e-03 | -4.662e-02 | 5.886e-02 | -6.227e-03 | -0.017 | 0.162 | -0.557 | 6.614e-01 | -1.042e-01 |
| t2 | -4.452e-05 | -2.089e-04 | -5.165e-03 | 2.748e-04 | -1.754e-04 | 4.173e-04 | -3.617e-06 | -1.361e-04 | 1.100e-04 | 8.914e-04 | ... | 2.047e-01 | 6.117e-02 | -5.444e-02 | -1.529e-02 | -1.469e-02 | 0.023 | 0.183 | 0.290 | -3.938e-01 | 3.587e-01 | |
| t3 | -1.283e-04 | 1.048e-03 | 8.982e-03 | 5.709e-04 | -1.808e-04 | 1.258e-03 | 5.577e-06 | -5.649e-03 | -5.097e-03 | 7.869e-03 | ... | -1.857e-01 | -2.785e-02 | 6.353e-02 | 5.410e-02 | 2.473e-02 | -0.030 | -0.234 | 0.069 | 6.091e-02 | -3.214e-01 | |
| r1 | -3.005e-07 | 5.476e-05 | 6.343e-04 | 6.332e-06 | 2.491e-06 | 2.715e-06 | 5.464e-07 | -2.376e-04 | -2.019e-04 | -6.031e-05 | ... | -4.279e-04 | -3.524e-03 | 9.710e-04 | -6.896e-03 | 9.867e-04 | 0.001 | -0.014 | -0.008 | 2.789e-02 | -2.645e-02 | |
| r2 | 1.195e-05 | -1.468e-05 | -9.874e-05 | 2.887e-07 | 7.293e-06 | -1.234e-04 | 1.826e-07 | 7.492e-05 | 1.152e-04 | -9.475e-04 | ... | 2.369e-02 | 1.095e-03 | -8.118e-03 | -1.289e-02 | -1.785e-03 | 0.005 | 0.015 | -0.021 | 3.344e-02 | 3.849e-03 | |
| r3 | -2.865e-06 | 1.522e-05 | 6.912e-05 | -4.279e-06 | -4.743e-06 | 2.949e-05 | 1.857e-07 | -1.044e-04 | -6.757e-05 | -1.060e-04 | ... | 2.703e-02 | 1.362e-03 | -5.113e-03 | -1.492e-02 | -6.335e-04 | 0.005 | 0.001 | 0.027 | -1.418e-02 | 1.118e-02 | |
| 5630 | t1 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | ... | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000 | 0.000 | 0.000 | 0.000e+00 | 0.000e+00 |
| t2 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | ... | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000 | 0.000 | 0.000 | 0.000e+00 | 0.000e+00 | |
| t3 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | ... | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000 | 0.000 | 0.000 | 0.000e+00 | 0.000e+00 | |
| r1 | -1.815e-05 | -9.454e-05 | -3.223e-04 | -3.568e-05 | 1.340e-05 | -3.384e-05 | 1.329e-06 | 7.127e-04 | 4.621e-04 | -6.382e-04 | ... | -3.555e-02 | -8.501e-03 | 1.420e-02 | -1.374e-02 | 1.390e-04 | 0.004 | -0.017 | 0.004 | -2.480e-04 | -2.458e-03 | |
| r2 | -1.174e-04 | 8.335e-07 | -1.801e-05 | 1.328e-03 | 2.448e-05 | 7.252e-04 | -3.178e-07 | -1.708e-05 | -1.350e-05 | 3.852e-03 | ... | 6.103e-03 | -6.432e-03 | 1.082e-02 | -3.451e-02 | -4.203e-03 | 0.011 | 0.018 | -0.003 | 7.885e-03 | 2.321e-02 | |
| r3 | 1.512e-05 | 3.817e-05 | 2.898e-04 | -7.734e-06 | -1.064e-06 | -1.914e-06 | -6.212e-07 | -2.275e-04 | -1.247e-04 | 5.015e-04 | ... | 1.508e-02 | -1.308e-03 | 3.008e-03 | -9.727e-03 | 3.836e-04 | 0.001 | -0.003 | -0.030 | -3.103e-02 | -2.712e-02 | |
| 5631 | t1 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | ... | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000 | 0.000 | 0.000 | 0.000e+00 | 0.000e+00 |
| t2 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | ... | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000 | 0.000 | 0.000 | 0.000e+00 | 0.000e+00 | |
| t3 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | ... | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000 | 0.000 | 0.000 | 0.000e+00 | 0.000e+00 | |
| r1 | -9.862e-07 | 5.862e-05 | 5.579e-04 | 1.046e-05 | 6.905e-05 | 5.601e-06 | -1.679e-06 | -2.394e-04 | -2.043e-04 | -3.901e-05 | ... | 1.138e-03 | -1.261e-02 | 1.119e-02 | -1.439e-02 | 1.245e-03 | 0.004 | -0.024 | -0.012 | 4.048e-03 | 1.465e-02 | |
| r2 | 8.388e-06 | -1.919e-06 | -7.635e-06 | -2.048e-04 | -1.957e-07 | -2.855e-04 | 5.311e-07 | 6.254e-05 | -5.671e-05 | -2.159e-03 | ... | -2.994e-02 | -4.564e-03 | 1.167e-02 | -1.208e-02 | -2.319e-03 | 0.004 | 0.012 | -0.005 | -5.452e-03 | -5.399e-03 | |
| r3 | -4.235e-05 | 3.105e-06 | 1.132e-06 | 3.700e-04 | 3.678e-07 | 2.318e-04 | -3.299e-07 | -1.454e-05 | -9.195e-06 | 8.113e-04 | ... | 7.605e-03 | -3.327e-03 | 1.359e-02 | 8.849e-04 | -7.085e-04 | 0.002 | 0.011 | -0.018 | -1.781e-02 | -1.326e-02 | |
| 5632 | t1 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | ... | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000 | 0.000 | 0.000 | 0.000e+00 | 0.000e+00 |
| t2 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | ... | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000 | 0.000 | 0.000 | 0.000e+00 | 0.000e+00 | |
| t3 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | ... | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000 | 0.000 | 0.000 | 0.000e+00 | 0.000e+00 | |
| r1 | 1.756e-05 | -9.628e-05 | -3.117e-04 | 4.014e-05 | 1.268e-05 | 3.502e-05 | 1.054e-06 | 5.821e-04 | 6.400e-04 | 9.411e-04 | ... | 3.064e-02 | -2.242e-03 | 5.439e-04 | -1.809e-02 | 1.961e-04 | 0.005 | -0.016 | 0.004 | 1.558e-04 | -4.253e-03 | |
| r2 | -1.170e-04 | -2.698e-07 | 2.598e-05 | 1.325e-03 | -3.278e-05 | 7.227e-04 | -2.756e-06 | 1.174e-05 | 1.113e-05 | 3.844e-03 | ... | 1.025e-02 | 4.245e-03 | 2.363e-03 | -2.781e-02 | -4.249e-03 | 0.009 | 0.026 | 0.024 | 1.089e-02 | -1.333e-02 | |
| r3 | 1.548e-05 | -4.294e-05 | -2.770e-04 | -1.257e-05 | -3.928e-06 | -5.062e-06 | 3.049e-07 | 1.836e-04 | 2.254e-04 | 5.881e-04 | ... | 2.334e-02 | -1.135e-03 | 5.283e-03 | -1.865e-03 | -3.915e-03 | 0.002 | 0.024 | -0.032 | -2.891e-02 | -1.447e-02 | |
| 5633 | t1 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | ... | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000 | 0.000 | 0.000 | 0.000e+00 | 0.000e+00 |
| t2 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | ... | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000 | 0.000 | 0.000 | 0.000e+00 | 0.000e+00 | |
| t3 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | ... | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000e+00 | 0.000 | 0.000 | 0.000 | 0.000e+00 | 0.000e+00 | |
| r1 | -3.006e-07 | 5.476e-05 | 6.343e-04 | 6.334e-06 | 2.491e-06 | 2.716e-06 | 5.464e-07 | -2.376e-04 | -2.019e-04 | -6.030e-05 | ... | -4.279e-04 | -3.524e-03 | 9.710e-04 | -6.896e-03 | 9.867e-04 | 0.001 | -0.014 | -0.008 | 2.789e-02 | -2.645e-02 | |
| r2 | -1.723e-06 | 1.278e-06 | -1.805e-06 | 1.940e-04 | 3.380e-07 | -8.450e-06 | 3.548e-08 | -4.728e-05 | 4.650e-05 | -2.113e-04 | ... | 2.084e-02 | 1.171e-03 | -6.235e-03 | -1.349e-02 | -1.096e-03 | 0.005 | 0.006 | 0.005 | 4.639e-03 | 6.872e-03 | |
| r3 | 7.271e-06 | 3.394e-06 | -2.722e-06 | -1.478e-04 | 4.108e-07 | -5.572e-05 | 2.948e-07 | -1.384e-05 | -1.663e-05 | -6.516e-04 | ... | 2.914e-02 | 1.305e-03 | -6.509e-03 | -1.448e-02 | -1.144e-03 | 0.005 | 0.008 | 0.008 | 7.160e-03 | 8.942e-03 |
32274 rows × 167 columns
Accessing the plate stress/strain¶
Results are stored on a per element type basis.
The OP2 is the same as an F06, so CQUAD4 elements have centroidal-based results or centroidal-based as well as the results at the 4 corner nodes.
Be careful about what you’re accessing.
# element forces/stresses/strains are by element type consistent with the F06, so...
plate_stress = op2.cquad4_stress[1]
print("plate_stress_obj = %s" % type(plate_stress))
# the set of variables in the RealPlateStressArray
print("plate_stress = %s\n" % plate_stress.__dict__.keys())
# list of parameters that define the object (e.g. what is the nonlinear variable name
print("data_code_keys = %s\n" % plate_stress.data_code.keys())
# nonlinear variable name
name = plate_stress.data_code['name']
print("name = %r" % plate_stress.data_code['name'])
print("list-type variables = %s" % plate_stress.data_code['data_names'])
# the special loop parameter
# for modal analysis, it's "modes"
# for transient, it's "times"
# or be lazy and use "_times"
print("modes = %s" % plate_stress.modes) # name + 's'
# extra list-type parameter for modal analysis; see data_names
#print("mode_cycles =", plate_stress.mode_cycles)
plate_stress_obj = <class 'pyNastran.op2.tables.oes_stressStrain.real.oes_plates.RealPlateStressArray'>
plate_stress = ['_add_new_eid', '_add_new_node', 'subtitle', 'words', 's_code', 'is_built', 'stress_bits', 'load_set', 'itotal', '_add', '_ntotals', 'nnodes', 'sort_bits', 'isubcase', 'element_name', 'itime', 'nonlinear_factor', 'title', '_times', 'ntotal', 'approach_code', 'is_stress_flag', 'label', 'element_node', 'is_msc', 'num_wide', 'mode', 'format_code', 'device_code', 'modes', '_times_dtype', 'thermal_bits', 'mode2s', 'data_frame', 'mode2', 'dt', 'is_strain_flag', 'data', 'cycle', 'name', 'nelements', 'eigr', 'ielement', 'thermal', 'analysis_code', 'eigrs', 'table_code', 'element_type', 'table_name', 'data_code', 'isTransient', 'sort_code', 'cycles', 'ntimes', 'data_names']
data_code_keys = [u'subtitle', u'stress_bits', u'load_set', u'thermal', u's_code', u'sort_bits', u'isubcase', u'element_name', u'mode2', u'title', u'approach_code', u'is_stress_flag', u'label', u'is_msc', u'num_wide', u'format_code', u'device_code', u'_times_dtype', u'thermal_bits', u'nonlinear_factor', u'is_strain_flag', u'cycle', u'name', u'eigr', u'analysis_code', u'table_code', u'element_type', u'table_name', u'mode', u'sort_code', u'data_names']
name = u'mode'
list-type variables = [u'mode', u'eigr', u'mode2', u'cycle']
modes = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167]
Similar to the BDF, we can use object_attributes/methods¶
#print "attributes =", object_attributes(plate_stress)
print("methods = %s\n" % object_methods(plate_stress))
print('methods2= %s\n' % plate_stress.object_methods())
print("headers = %s\n" % plate_stress.get_headers())
methods = ['apply_data_code', 'approach_code_str', 'build', 'build_dataframe', 'cast_grid_type', 'code_information', 'eid_to_element_node_index', 'get_data_code', 'get_element_index', 'get_element_type', 'get_headers', 'get_nnodes_bilinear', 'get_stats', 'get_unsteady_value', 'is_bilinear', 'is_complex', 'is_curvature', 'is_fiber_distance', 'is_magnitude_phase', 'is_max_shear', 'is_real', 'is_sort1', 'is_sort2', 'is_strain', 'is_stress', 'is_thermal', 'is_von_mises', 'object_attributes', 'object_methods', 'print_data_members', 'print_table_code', 'recast_gridtype_as_string', 'set_table_type', 'update_data_code', 'update_dt', 'write_f06']
methods2= ['apply_data_code', 'approach_code_str', 'build', 'build_dataframe', 'cast_grid_type', 'code_information', 'eid_to_element_node_index', 'get_data_code', 'get_element_index', 'get_element_type', 'get_headers', 'get_nnodes_bilinear', 'get_stats', 'get_unsteady_value', 'is_bilinear', 'is_complex', 'is_curvature', 'is_fiber_distance', 'is_magnitude_phase', 'is_max_shear', 'is_real', 'is_sort1', 'is_sort2', 'is_strain', 'is_stress', 'is_thermal', 'is_von_mises', 'print_data_members', 'print_table_code', 'recast_gridtype_as_string', 'set_table_type', 'update_data_code', 'update_dt', 'write_f06']
headers = [u'fiber_distance', u'oxx', u'oyy', u'txy', u'angle', u'omax', u'omin', u'von_mises']
Number of Nodes on a CQUAD4¶
- For linear CQUAD4s, there is 1 centroidal stress at two locations
- For bilinear quads, there are 5 stresses at two locations (4 nodes + centroidal)
- node_id=0 indicates a centroidal quantity
- CTRIA3s are always centroidal
What sets this?¶
STRESS(real, sort1, BILIN) = ALL # bilinear cquad
STRESS(real, sort1, CENT) = ALL # linear quad
STRAIN(real, sort1, BILIN) = ALL # bilinear cquad
STRAIN(real, sort1, CENT) = ALL # linear quad
How do we know if we’re bilinear?¶
print("is_bilinear = %s\n" % plate_stress.is_bilinear())
What locations are chosen?¶
That depends on fiber distance/fiber curvature... - fiber_curvature - mean stress (oa) & slope (om)
$$ \sigma_{top} = \sigma_{alt} + \frac{t}{2} \sigma_{mean}$$
$$ \sigma_{btm} = \sigma_{alt} + \frac{t}{2} \sigma_{mean}$$
- fiber_distance - upper and lower surface stress (o_top; o_btm)
- If you have stress, fiber_distance is always returned regardless of your option.
What sets this?¶
STRAIN(real, sort1, FIBER) = ALL # fiber distance/default
STRAIN(real, sort1, STRCUR) = ALL # strain curvature
How do we know if we’re using fiber_distance?¶
print("is_fiber_distance = %s" % plate_stress.is_fiber_distance())
Accessing results¶
# element forces/stresses/strains are by element type consistent
# with the F06, so...
def abs_max_min(vals):
absvals = list(abs(vals))
maxval = max(absvals)
i = absvals.index(maxval)
return vals[i]
#-----------------------------
# again, we have linear quads, so two locations per element
print("element_node[:10, :] =\n%s..." % plate_stress.element_node[:10, :])
# lets get the stress for the first 3 CQUAD4 elements
eids = plate_stress.element_node[:, 0]
ueids = np.unique(eids)
print('ueids = %s' % ueids[:3])
# get the first index of the first 5 elements
ieids = np.searchsorted(eids, ueids[:3])
print('ieids = %s' % ieids)
# the easy way to slice data for linear plates
ieids5 = np.vstack([ieids, ieids + 1]).ravel()
ieids5.sort()
print('verify5:\n%s' % ieids5)
#-----------------------------
itime = 0 # static analysis / mode 1
if plate_stress.is_von_mises(): # True
ovm = plate_stress.data[itime, :, 7]
print('we have von mises data; ovm=%s\n' % ovm)
else:
omax_shear = plate_stress.data[itime, :, 7]
print('we have max shear data; omax_shear=%s\n' % omax_shear)
print("[layer1, layer2, ...] = %s" % ovm[ieids5])
ieid1000 = np.where(eids == 1000)[0]
print('ieid1000 = %s' % ieid1000)
ovm_mode6_eid1000 = ovm[ieid1000]
print("ovm_mode6_eid1000 = %s -> %s" % (ovm_mode6_eid1000, abs_max_min(ovm_mode6_eid1000)))
element_node[:10, :] =
[[1 0]
[1 0]
[2 0]
[2 0]
[3 0]
[3 0]
[4 0]
[4 0]
[5 0]
[5 0]]...
ueids = [1 2 3]
ieids = [0 2 4]
verify5:
[0 1 2 3 4 5]
we have von mises data; ovm=[ 54.222 5.041 13.143 ..., 2.34 6.146 7.368]
[layer1, layer2, ...] = [ 54.222 5.041 13.143 21.222 78.544 17.91 ]
ieid1000 = [1998 1999]
ovm_mode6_eid1000 = [ 90.618 94.09 ] -> 94.0905
# see the difference between "transient"/"modal"/"frequency"-style results
# and "nodal"/"elemental"-style results
# just change imode
imode = 5 # mode 6; could just as easily be dt
iele = 10 # element 10
ilayer = 1
ieid10 = np.where(eids == iele)[0][ilayer]
print('ieid10 = %s' % ieid10)
print(plate_stress.element_node[ieid10, :])
# headers = [u'fiber_distance', u'oxx', u'oyy', u'txy', u'angle', u'omax', u'omin', u'von_mises']
print("ps.modes = %s" % plate_stress.modes[imode])
print("ps.cycles = %s" % plate_stress.cycles[imode])
print("oxx = %s" % plate_stress.data[imode, ieid10, 1])
print("oyy = %s" % plate_stress.data[imode, ieid10, 2])
print("txy = %s" % plate_stress.data[imode, ieid10, 3])
print("omax = %s" % plate_stress.data[imode, ieid10, 5])
print("omin = %s" % plate_stress.data[imode, ieid10, 6])
print("ovm/max_shear = %s" % plate_stress.data[imode, ieid10, 7])
if plate_stress.is_fiber_distance():
print("fiber_distance = %s" % plate_stress.data[imode, ieid10, 0])
else:
print("curvature = %s" % plate_stress.data[imode, ieid10, 0])
ieid10 = 19
[10 0]
ps.modes = 6
ps.cycles = 9.80908925027e-45
oxx = -18.8701
oyy = -20.1605
txy = -8.30956
omax = -11.1807
omin = -27.8499
ovm/max_shear = 24.2743
fiber_distance = -0.4
from pyNastran.bdf.bdf import read_bdf
bdf_filename = os.path.abspath(os.path.join(pkg_path, '..', 'models', 'iSat', 'ISat_Launch_Sm_4pt.dat'))
model = read_bdf(bdf_filename, debug=False)
mass, cg, I = model.mass_properties()
WARNING: fname=shell.py lineNo=1434 PSHELL pid=1 midsurface: z1=0.400000006 z2=-0.400000006 t=0.035999998 not in range of -1.5t < zi < 1.5t
WARNING: fname=shell.py lineNo=1434 PSHELL pid=2 midsurface: z1=0.400000006 z2=-0.400000006 t=0.054000005 not in range of -1.5t < zi < 1.5t
WARNING: fname=shell.py lineNo=1434 PSHELL pid=3 midsurface: z1=0.400000006 z2=-0.400000006 t=0.017999999 not in range of -1.5t < zi < 1.5t
WARNING: fname=shell.py lineNo=1434 PSHELL pid=7 midsurface: z1=0.418000013 z2=-0.418000013 t=0.035999998 not in range of -1.5t < zi < 1.5t
WARNING: fname=shell.py lineNo=1434 PSHELL pid=34 midsurface: z1=0.194000006 z2=-0.194000006 t=0.0186 not in range of -1.5t < zi < 1.5t
WARNING: fname=shell.py lineNo=1434 PSHELL pid=37 midsurface: z1=0.308999985 z2=-0.308999985 t=0.0186 not in range of -1.5t < zi < 1.5t
WARNING: fname=shell.py lineNo=1434 PSHELL pid=38 midsurface: z1=0.284000009 z2=-0.284000009 t=0.0186 not in range of -1.5t < zi < 1.5t
WARNING: fname=shell.py lineNo=1434 PSHELL pid=46 midsurface: z1=0.199000001 z2=-0.199000001 t=0.0186 not in range of -1.5t < zi < 1.5t
Let’s print out the actual mass properties from the OP2 and get the same result as the F06¶
We need PARAM,POSTEXT,YES in out BDF to get the Grid Point Weight
Table
gpw = op2.grid_point_weight
#print(gpw.object_attributes())
print(gpw)
O U T P U T F R O M G R I D P O I N T W E I G H T G E N E R A T O R
0 REFERENCE POINT = 0
M O
* 1.774601E+00 1.402827E-19 2.212874E-19 -1.821217E-17 -3.277270E+01 4.490826E+00 *
* 1.402827E-19 1.774601E+00 -4.675622E-19 3.277270E+01 -2.898787E-17 -6.007191E-02 *
* 2.212874E-19 -4.675622E-19 1.774601E+00 -4.490826E+00 6.007191E-02 -3.871152E-19 *
* -1.821217E-17 3.277270E+01 -4.490826E+00 1.322289E+03 1.414696E+00 -1.250574E+00 *
* -3.277270E+01 -2.898787E-17 6.007191E-02 1.414696E+00 1.227074E+03 -2.187713E+02 *
* 4.490826E+00 -6.007191E-02 -3.871152E-19 -1.250574E+00 -2.187713E+02 4.272278E+02 *
S
* 1.000000E+00 0.000000E+00 0.000000E+00 *
* 0.000000E+00 1.000000E+00 0.000000E+00 *
* 0.000000E+00 0.000000E+00 1.000000E+00 *
DIRECTION
MASS AXIS SYSTEM (S) MASS X-C.G. Y-C.G. Z-C.G.
X 1.774601E+00 -1.026268E-17 -2.530611E+00 -1.846764E+01
Y 1.774601E+00 -3.385094E-02 -1.633486E-17 -1.846764E+01
Z 1.774601E+00 -3.385094E-02 -2.530611E+00 -2.181421E-19
I(S)
* 7.056896E+02 -1.566714E+00 1.411869E-01 *
* -1.566714E+00 6.218375E+02 1.358363E+02 *
* 1.411869E-01 1.358363E+02 4.158613E+02 *
I(Q)
* 6.891835E+02 *
* 3.483842E+02 *
* 7.058207E+02 *
Q
* 8.846355E-02 1.596853E-03 9.960781E-01 *
* -8.920128E-01 -4.448861E-01 7.993453E-02 *
* 4.432690E-01 -8.955857E-01 -3.793179E-02 *
PAGE 1
We can also write the full F06¶
import getpass
name = getpass.getuser()
os.chdir(os.path.join(r'C:\Users', name, 'Desktop'))
# write the F06 with Real/Imaginary or Magnitude/Phase
# only matters for complex results
op2.write_f06('isat.f06', is_mag_phase=False)
!head -n 40 isat.f06
F06:
grid_point_weight
RealEigenvalues case=u'ISAT_SM_LAUNCH_4PT MODES TO 400 HZ'
RealEigenvectorArray SUBCASE=1 SUBTITLE=
RealCBarForceArray SUBCASE=1 SUBTITLE= - CBAR-34
RealPlateStressArray SUBCASE=1 SUBTITLE= - CQUAD4
RealPlateStressArray SUBCASE=1 SUBTITLE= - CTRIA3
O U T P U T F R O M G R I D P O I N T W E I G H T G E N E R A T O R
0 REFERENCE POINT = 0
M O
* 1.774601E+00 1.402827E-19 2.212874E-19 -1.821217E-17 -3.277270E+01 4.490826E+00 *
* 1.402827E-19 1.774601E+00 -4.675622E-19 3.277270E+01 -2.898787E-17 -6.007191E-02 *
* 2.212874E-19 -4.675622E-19 1.774601E+00 -4.490826E+00 6.007191E-02 -3.871152E-19 *
* -1.821217E-17 3.277270E+01 -4.490826E+00 1.322289E+03 1.414696E+00 -1.250574E+00 *
* -3.277270E+01 -2.898787E-17 6.007191E-02 1.414696E+00 1.227074E+03 -2.187713E+02 *
* 4.490826E+00 -6.007191E-02 -3.871152E-19 -1.250574E+00 -2.187713E+02 4.272278E+02 *
S
* 1.000000E+00 0.000000E+00 0.000000E+00 *
* 0.000000E+00 1.000000E+00 0.000000E+00 *
* 0.000000E+00 0.000000E+00 1.000000E+00 *
DIRECTION
MASS AXIS SYSTEM (S) MASS X-C.G. Y-C.G. Z-C.G.
X 1.774601E+00 -1.026268E-17 -2.530611E+00 -1.846764E+01
Y 1.774601E+00 -3.385094E-02 -1.633486E-17 -1.846764E+01
Z 1.774601E+00 -3.385094E-02 -2.530611E+00 -2.181421E-19
I(S)
* 7.056896E+02 -1.566714E+00 1.411869E-01 *
* -1.566714E+00 6.218375E+02 1.358363E+02 *
* 1.411869E-01 1.358363E+02 4.158613E+02 *
I(Q)
* 6.891835E+02 *
* 3.483842E+02 *
* 7.058207E+02 *
Q
* 8.846355E-02 1.596853E-03 9.960781E-01 *
* -8.920128E-01 -4.448861E-01 7.993453E-02 *
* 4.432690E-01 -8.955857E-01 -3.793179E-02 *
1 ISAT_SM_LAUNCH_4PT MODES TO 400 HZ JANUARY 4, 2016 pyNastran v0.8.0+dev.82cefee PAGE 1
1 ISAT_SM_LAUNCH_4PT MODES TO 400 HZ JANUARY 4, 2016 pyNastran v0.8.0+dev.82cefee PAGE 2
DEFAULT
R E A L E I G E N V A L U E S
ISAT_SM_LAUNCH_4PT MODES TO 400 HZ
MODE EXTRACTION EIGENVALUE RADIANS CYCLES GENERALIZED GENERALIZED
NO. ORDER MASS STIFFNESS
#from IPython.display import display, Math, Latex
The mass results are different as pyNastran’s mass assumes point masses
\[m_{plates} = A * (rho * t + nsm)\]
\[m_{solid} = V * rho\]
\[m_{bars} = L * (rho * A + nsm)\]
\[I = m*r^2\]
The larger your model is and the further from the origin, the more accurate the result. For some applications (e.g. a weight breakdown), this is probably be fine.
print('cg =\n%s' % gpw.cg)
print('cg = %s' % cg)
cg =
[[ -1.026e-17 -2.531e+00 -1.847e+01]
[ -3.385e-02 -1.633e-17 -1.847e+01]
[ -3.385e-02 -2.531e+00 -2.181e-19]]
cg = [ -0.035 -2.623 -18.53 ]
It’s not like Nastran is perfect either.¶
Limitations¶
- You cannot do weight statements in Nastran by component/property/material.
- Everything is always summmed up (e.g. you can have different geometry in Subcase 2 and MPCs connecting physical geomtry, with other parts flying off into space).
These are things that pyNastran can do.
from pyNastran.bdf.bdf import read_bdf
bdf_filename = os.path.abspath(os.path.join(pkg_path, '..', 'models', 'iSat', 'ISat_Launch_Sm_4pt.dat'))
model = read_bdf(bdf_filename, debug=False)
WARNING: fname=shell.py lineNo=1434 PSHELL pid=1 midsurface: z1=0.400000006 z2=-0.400000006 t=0.035999998 not in range of -1.5t < zi < 1.5t
WARNING: fname=shell.py lineNo=1434 PSHELL pid=2 midsurface: z1=0.400000006 z2=-0.400000006 t=0.054000005 not in range of -1.5t < zi < 1.5t
WARNING: fname=shell.py lineNo=1434 PSHELL pid=3 midsurface: z1=0.400000006 z2=-0.400000006 t=0.017999999 not in range of -1.5t < zi < 1.5t
WARNING: fname=shell.py lineNo=1434 PSHELL pid=7 midsurface: z1=0.418000013 z2=-0.418000013 t=0.035999998 not in range of -1.5t < zi < 1.5t
WARNING: fname=shell.py lineNo=1434 PSHELL pid=34 midsurface: z1=0.194000006 z2=-0.194000006 t=0.0186 not in range of -1.5t < zi < 1.5t
WARNING: fname=shell.py lineNo=1434 PSHELL pid=37 midsurface: z1=0.308999985 z2=-0.308999985 t=0.0186 not in range of -1.5t < zi < 1.5t
WARNING: fname=shell.py lineNo=1434 PSHELL pid=38 midsurface: z1=0.284000009 z2=-0.284000009 t=0.0186 not in range of -1.5t < zi < 1.5t
WARNING: fname=shell.py lineNo=1434 PSHELL pid=46 midsurface: z1=0.199000001 z2=-0.199000001 t=0.0186 not in range of -1.5t < zi < 1.5t
Let’s get the breakdown by property ID¶
from six import iteritems
#help(model.mass_properties)
pid_to_eids_map = model.get_element_ids_dict_with_pids()
#print(pid_to_eids_map.keys())
print('pid, mass, cg, [ixx, iyy, izz, ixy, ixz]')
for pid, eids in sorted(iteritems(pid_to_eids_map)):
mass, cg, inertia = model.mass_properties(element_ids=eids, reference_point=[0., 0., 0.])
print('%-3s %-.6f %-38s %s' % (pid, mass, cg, inertia))
pid, mass, cg, [ixx, iyy, izz, ixy, ixz]
1 0.027278 [ 4.297e-15 2.980e-15 -2.000e+01] [ 1.461e+01 1.746e+01 4.384e+00 4.098e-17 1.450e-15 4.619e-16]
2 0.047993 [ -6.506e-16 2.530e-16 -2.000e+01] [ 3.723e+01 3.723e+01 1.245e+01 -3.469e-17 -5.690e-16 2.047e-16]
3 0.020998 [ 6.842e-17 -4.699e-16 -2.000e+01] [ 1.428e+01 1.231e+01 5.270e+00 2.992e-17 5.281e-16 1.011e-15]
4 0.012216 [ 0.043 0.438 -19.702] [ 7.090e+00 7.972e+00 2.021e+00 1.057e-02 -5.272e-03 -5.334e-02]
5 0.330158 [ 0. 2.2 -20. ] [ 1.970e+02 1.604e+02 4.335e+01 0.000e+00 4.441e-16 -1.453e+01]
7 0.027813 [ 6.578e-17 -1.143e-14 -2.000e+01] [ 1.927e+01 1.927e+01 9.438e+00 -3.408e-15 -2.069e-16 -1.751e-15]
8 0.081584 [ 0.000e+00 6.804e-16 -2.000e+01] [ 4.772e+01 4.772e+01 3.017e+01 -8.882e-16 0.000e+00 -8.882e-16]
9 0.012578 [ 0.000e+00 -7.585e-16 -2.000e+01] [ 7.788e+00 7.788e+00 3.064e+00 5.551e-17 -4.857e-17 -1.180e-16]
10 0.000236 [ 0.000e+00 -4.595e-16 -2.000e+01] [ 1.290e-01 1.290e-01 5.747e-02 -8.674e-19 -1.735e-18 -8.674e-19]
11 0.041700 [ -1.025 23.773 -12.016] [ 30.253 7.053 23.957 -1.053 0.776 -11.967]
12 0.000457 [ 0. -5.92 20.506] [ 0.221 0.205 0.016 0. 0. -0.054]
13 0.000000 [ 0. 0. 0.] [ 0. 0. 0. 0. 0. 0.]
14 0.000353 [ -2.305e-16 0.000e+00 1.439e+01] [ 7.655e-02 8.537e-02 8.821e-03 0.000e+00 -2.168e-18 0.000e+00]
15 0.000000 [ 0. 0. 0.] [ 0. 0. 0. 0. 0. 0.]
16 0.000000 [ 0. 0. 0.] [ 0. 0. 0. 0. 0. 0.]
19 0.017749 [ -0.23 6.021 -35.642] [ 24.961 26.944 6.461 -0.078 0.151 -3.954]
20 0.163082 [ 6.808e-16 0.000e+00 -1.855e+01] [ 6.510e+01 9.086e+01 2.576e+01 0.000e+00 -1.776e-15 0.000e+00]
21 0.003625 [ -1.196e-16 -1.077e-15 -2.000e+01] [ 2.178e+00 2.178e+00 1.410e+00 0.000e+00 0.000e+00 -2.776e-17]
22 0.000000 [ 0. 0. 0.] [ 0. 0. 0. 0. 0. 0.]
23 0.000000 [ 0. 0. 0.] [ 0. 0. 0. 0. 0. 0.]
33 0.001346 [ -3.612e-14 -2.175e+00 3.691e-01] [ 8.358e-02 8.533e-02 1.683e-01 1.802e-16 -3.670e-17 -1.832e-03]
34 0.003561 [ -5.899e-17 -1.903e-18 1.483e+01] [ 1.054e+00 1.054e+00 6.701e-02 -5.828e-19 -4.120e-18 -8.674e-19]
35 0.000000 [ 0. 0. 0.] [ 0. 0. 0. 0. 0. 0.]
36 0.007197 [ 3.676e-15 0.000e+00 -1.478e+01] [ 2.408e+00 5.178e+00 3.020e+00 6.939e-18 8.153e-17 -1.041e-17]
37 0.094566 [ -4.439e-15 0.000e+00 -1.950e+01] [ 4.493e+01 8.867e+01 4.649e+01 5.454e-14 -2.776e-16 0.000e+00]
38 0.007602 [ 6.830e-06 -9.329e+00 2.731e+01] [ 7.013e+00 6.884e+00 1.223e+00 -2.922e-07 1.641e-06 -1.867e+00]
39 0.002433 [ 1.348e-13 -8.954e+00 4.040e+00] [ 2.568e-01 8.454e-02 2.187e-01 -2.920e-15 1.207e-15 -9.123e-02]
41 0.000735 [ -9.583e-16 -1.843e-17 2.193e+00] [ 1.226e-02 6.032e-02 6.220e-02 5.127e-16 8.674e-19 -5.421e-20]
42 0.008854 [ -1.554 20.121 -19.007] [ 7.95 4.679 3.9 -0.277 0.318 -3.386]
43 0.012241 [ 6.191e-15 2.214e-18 -1.950e+01] [ 6.882e+00 1.224e+01 6.320e+00 7.003e-15 -4.749e-17 1.762e-18]
46 0.003671 [ 3.544e-15 7.383e-18 1.528e+01] [ 1.035e+00 1.205e+00 3.350e-01 1.239e-07 8.544e-17 4.120e-18]
60 0.000000 [ 0. 0. 0.] [ 0. 0. 0. 0. 0. 0.]
61 0.000000 [ 0. 0. 0.] [ 0. 0. 0. 0. 0. 0.]