Hotspot calculation demo

This notebook detects and classifies hotspots of the von Mises stress in a connected FEM mesh. Each element/node entry of the mesh receives a number of the hotspot it is member of. “0” means the element/node is not part of any hotspots. “1” means that the element/node is part of the hotspot with the highes peak, “2” the same for the second highest peak and so forth.

See module documentation further details.

import numpy as np
import pylife
import pandas as pd
import scipy.stats as stats
import pylife.stress.equistress
import pylife.strength.meanstress
import pylife.mesh.hotspot
import pylife.vmap

import pyvista as pv

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

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())

Equivalent stress calculation

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

Hot spot Calculation

threshold = .9 # factor of the maximum local value
pyLife_mesh['hotspot'] = pyLife_mesh.hotspot.calc("mises", threshold)
display(pyLife_mesh[['x', 'y', 'z', 'mises', 'hotspot']])

		x	y	z	mises	hotspot
element_id	node_id
1	1734	14.897208	5.269875	0.0	33.996987	0
	1582	14.555333	5.355806	0.0	33.399850	0
	1596	14.630658	4.908741	0.0	54.777007	0
	4923	14.726271	5.312840	0.0	33.446991	0
	4924	14.592996	5.132274	0.0	44.070962	0
...	...	...	...	...	...	...
4770	3812	-13.189782	-5.691876	0.0	43.577209	0
	12418	-13.560289	-5.278386	0.0	39.903508	0
	14446	-13.673285	-5.569107	0.0	40.478974	0
	14614	-13.389065	-5.709927	0.0	42.140169	0
	14534	-13.276068	-5.419206	0.0	41.143837	0

37884 rows × 5 columns

print("%d hotspots found over the threshold" % pyLife_mesh['hotspot'].max())

3 hotspots found over the threshold

# plotting using pyvista
pyLife_nodes = pyLife_mesh[['x', 'y', 'z', 'hotspot']].groupby('node_id').mean()
mesh = pv.PolyData(pyLife_nodes[['x', 'y', 'z']].values)
mesh.point_arrays["hotspot"] = pyLife_nodes["hotspot"].values
mesh.plot(scalars="hotspot",log_scale = False, off_screen=True)

First hotspot

display(pyLife_mesh[pyLife_mesh['hotspot'] == 1])

		x	y	z	S11	S22	S33	S12	S13	S23	dx	dy	dz	mises	hotspot
element_id	node_id
456	5	0.0	6.3	0.0	300.899658	30.574533	0.0	-7.081042	0.0	0.0	1.365477e-35	-0.005435	0.0	287.099222	1