VMAP IO Demo

This demo shows the stress gradient calculation module. A gradient is calculated by fitting a plane into a node and its neighbor nodes of an FEM mesh.

See documentation for details on the module.

import numpy as np
import pandas as pd
import pylife.vmap
import pylife.stress.equistress
import pyvista as pv

pv.set_plot_theme('document')
pv.set_jupyter_backend('ipygany')

Read in demo data and add the stress tensor dimensions for the third dimension.

vm_mesh = pylife.vmap.VMAPImport("plate_with_hole.vmap")

pyLife_mesh = (vm_mesh.make_mesh('1', 'STATE-2')
               .join_coordinates()
               .join_variable('STRESS_CAUCHY')
               .join_variable('DISPLACEMENT')
               .to_frame())
pyLife_mesh.sample(10)

		x	y	z	S11	S22	S33	S12	S13	S23	dx	dy	dz
element_id	node_id
3267	3621	8.121114	-4.490608	0.0	21.867970	-13.747931	0.0	7.758520	0.0	0.0	0.004623	7.864420e-04	0.0
3892	9034	-18.185001	0.000000	0.0	27.840216	15.018993	0.0	0.127443	0.0	0.0	-0.006497	1.918017e-37	0.0
4406	4412	-15.012715	-6.964381	0.0	39.262238	1.683851	0.0	-9.404963	0.0	0.0	-0.005405	4.239249e-05	0.0
4635	3833	-10.675753	-6.568871	0.0	48.634052	-0.761658	0.0	-13.739356	0.0	0.0	-0.004580	2.774546e-04	0.0
1872	2024	-14.391812	0.366991	0.0	15.852651	8.562475	0.0	1.622891	0.0	0.0	-0.006149	6.672515e-06	0.0
584	859	8.913480	2.461464	0.0	-2.514901	-25.786119	0.0	-3.572769	0.0	0.0	0.005472	-3.870771e-04	0.0
3245	3557	14.467859	-2.698292	0.0	21.078175	7.216562	0.0	9.874338	0.0	0.0	0.005719	-3.641288e-05	0.0
3156	3637	4.411795	-7.908645	0.0	76.299004	-0.893150	0.0	-8.012115	0.0	0.0	0.001600	3.362931e-03	0.0
4179	4206	-16.389534	-8.284608	0.0	37.194118	0.293217	0.0	-3.158941	0.0	0.0	-0.005526	8.016582e-05	0.0
1241	7567	14.355186	5.398512	0.0	34.705429	4.150722	0.0	-14.676251	0.0	0.0	0.005245	-8.010234e-07	0.0

pyLife_mesh['mises'] = pyLife_mesh.equistress.mises()

We will use Pyvista for plotting FEM in the future

still work in progress, sorry dudes

pyLife_nodes = pyLife_mesh[['x', 'y', 'z', 'mises']].groupby('node_id').mean()
mesh = pv.PolyData(pyLife_nodes[['x', 'y', 'z']].values)
mesh.point_arrays["mises"] = pyLife_nodes["mises"].values
mesh.plot(scalars="mises")

if you are using jupyter-lab you can use some lines, too:

for more information see here: https://pyvista-doc.readthedocs.io/en/latest/plotting/itk_plotting.html

pl = pv.PlotterITK()
pl.add_mesh(mesh, scalars="mises", smooth_shading=True)
pl.show(True)