Consider a line fracture $[-a_0, a_0] \times \{0\}$ ($a_0$ = 0.1) with no external loading and an internal fluid pressure of $p=1$ was applied to the fracture surfaces. The results are compared to the analytical solution (Sneddon et al., 1969) for the fracture half-opening: \begin{eqnarray} u(x,0) = \frac{2 p a_0}{ E’} \sqrt{1-(x/a_0)^2} , \label{eq:sneddon_2D_static} \end{eqnarray}
where $u$ is the displacement $E'$ is the plane strain Young’s modulus ($E' = E/(1-\nu^2)$) with $\nu$ is Poisson`s ratio, $p$ is the fluid pressure inside the fracture. To account for the infinite boundaries in the closed-form solution, we considered a large finite domain $ [-10a_o,10a_o] \times [-10a_o,10a_o]$. The effective element size, $h$, is $1\times10^{-2}$.
The material and geometrical properties are listed in the Table below. It’s worth noting that the properties are dimensionless and scaled.
Name | Value | Symbol |
---|---|---|
Young’s modulus | 1 | $E$ |
Poisson’s ratio | 0.15 | $\nu$ |
Fracture toughness | 1 | $G_{c}$ |
Regularization parameter | 2$h$ | $\ell_s$ |
Pressure | 1 | $p$ |
Length | 2 | $L$ |
Height | 2 | $H$ |
Initial crack length | 0.2 | $2a_0$ |
import math
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import math
import os
import time
from pathlib import Path
from subprocess import run
import gmsh
import matplotlib.pyplot as plt
import numpy as np
import ogstools as ot
import pyvista as pv
from ogstools.msh2vtu import msh2vtu
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pi = math.pi
plt.rcParams["text.usetex"] = True
E = 1.0
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E = 1.0
nu = 0.15
Gc = 1.0
P = 1.0
h = 0.01
Orientation = 0
a0 = 0.1 # half of the initial crack length
n_slices = (
2 * (round(3.0 * a0 / h)) + 1
) # number of slices for calcute width of fracture
phasefield_model = "AT1"
h_list = [0.01] # list of mesh sizes (h)
# h_list =[0.01, 0.005, 0.0025] # list of mesh sizes (h), for mesh sensitivity
# file's name
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# file's name
prj_name = "Kregime_Static.prj"
meshname = "mesh_full_pf"
out_dir = Path(os.environ.get("OGS_TESTRUNNER_OUT_DIR", "_out"))
if not out_dir.exists():
out_dir.mkdir(parents=True)
def mesh_generation(lc, lc_fine):
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def mesh_generation(lc, lc_fine):
"""
lc ... characteristic length for coarse meshing
lc_fine ... characteristic length for fine meshing
"""
L = 4.0 # Length
H = 4.0 # Height
b = 0.4 # Length/Height of subdomain with fine mesh
# Before using any functions in the Python API, Gmsh must be initialized
gmsh.initialize()
gmsh.option.setNumber("General.Terminal", 1)
gmsh.model.add("rectangle")
# Dimensions
dim1 = 1
dim2 = 2
# Points
gmsh.model.geo.addPoint(-L / 2, -H / 2, 0, lc, 1)
gmsh.model.geo.addPoint(L / 2, -H / 2, 0, lc, 2)
gmsh.model.geo.addPoint(L / 2, H / 2, 0, lc, 3)
gmsh.model.geo.addPoint(-L / 2, H / 2, 0, lc, 4)
gmsh.model.geo.addPoint(-b, -b - lc_fine / 2, 0, lc_fine, 5)
gmsh.model.geo.addPoint(b, -b - lc_fine / 2, 0, lc_fine, 6)
gmsh.model.geo.addPoint(b, b + lc_fine / 2, 0, lc_fine, 7)
gmsh.model.geo.addPoint(-b, b + lc_fine / 2, 0, lc_fine, 8)
# Lines
gmsh.model.geo.addLine(1, 2, 1)
gmsh.model.geo.addLine(2, 3, 2)
gmsh.model.geo.addLine(3, 4, 3)
gmsh.model.geo.addLine(4, 1, 4)
gmsh.model.geo.addLine(5, 6, 5)
gmsh.model.geo.addLine(6, 7, 6)
gmsh.model.geo.addLine(7, 8, 7)
gmsh.model.geo.addLine(8, 5, 8)
# Line loops
gmsh.model.geo.addCurveLoop([1, 2, 3, 4], 1)
gmsh.model.geo.addCurveLoop([5, 6, 7, 8], 2)
# Add plane surfaces defined by one or more curve loops.
gmsh.model.geo.addPlaneSurface([1, 2], 1)
gmsh.model.geo.addPlaneSurface([2], 2)
gmsh.model.geo.synchronize()
# Prepare structured grid
gmsh.model.geo.mesh.setTransfiniteCurve(
6, math.ceil(2 * b / lc_fine + 2), "Progression", 1
)
gmsh.model.geo.mesh.setTransfiniteCurve(
8, math.ceil(2 * b / lc_fine + 2), "Progression", 1
)
gmsh.model.geo.mesh.setTransfiniteSurface(2, "Alternate")
gmsh.model.geo.mesh.setRecombine(dim2, 1)
gmsh.model.geo.mesh.setRecombine(dim2, 2)
gmsh.model.geo.synchronize()
# Physical groups
Bottom = gmsh.model.addPhysicalGroup(dim1, [1])
gmsh.model.setPhysicalName(dim1, Bottom, "Bottom")
Right = gmsh.model.addPhysicalGroup(dim1, [2])
gmsh.model.setPhysicalName(dim1, Right, "Right")
Top = gmsh.model.addPhysicalGroup(dim1, [3])
gmsh.model.setPhysicalName(dim1, Top, "Top")
Left = gmsh.model.addPhysicalGroup(dim1, [4])
gmsh.model.setPhysicalName(dim1, Left, "Left")
Computational_domain = gmsh.model.addPhysicalGroup(dim2, [1, 2])
gmsh.model.setPhysicalName(dim2, Computational_domain, "Computational_domain")
gmsh.model.geo.synchronize()
output_file = f"{out_dir}/" + meshname + ".msh"
gmsh.model.mesh.generate(dim2)
gmsh.write(output_file)
gmsh.finalize()
def pre_processing(h, a0):
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def pre_processing(h, a0):
mesh = pv.read(f"{out_dir}/mesh_full_pf_domain.vtu")
phase_field = np.ones((len(mesh.points), 1))
pv.set_plot_theme("document")
for node_id, x in enumerate(mesh.points):
if (
(mesh.center[0] - x[0]) <= a0 + 0.001 * h
and (mesh.center[0] - x[0]) >= -a0 - 0.001 * h
and (mesh.center[1] - x[1]) < h / 2 + 0.001 * h
and (mesh.center[1] - x[1]) > -h / 2 - 0.001 * h
):
phase_field[node_id] = 0.0
mesh.point_data["phase-field"] = phase_field
mesh.save(f"{out_dir}/mesh_full_pf_OGS_pf_ic.vtu")
pv.set_plot_theme("document")
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pv.set_plot_theme("document")
pv.set_jupyter_backend("static")
def sneddon_numerical(h):
# mesh properties
ls = 2 * h
# generate prefix from properties
filename = f"results_h_{h:0.4f}"
mesh_generation(0.1, h)
# Convert GMSH (.msh) meshes to VTU meshes appropriate for OGS simulation.
input_file = f"{out_dir}/" + meshname + ".msh"
msh2vtu(filename=input_file, output_path=out_dir, keep_ids=True)
# As a preprocessing step, define the initial phase-field (crack).
pre_processing(h, a0)
# change properties in prj file #For more information visit: https://ogstools.opengeosys.org/stable/reference/ogstools.ogs6py.html
model = ot.Project(
input_file=prj_name,
output_file=f"{out_dir}/{prj_name}",
MKL=True,
args=f"-o {out_dir}",
)
gml_file = Path("./Kregime_Static.gml").resolve()
model.replace_parameter_value(name="ls", value=ls)
model.replace_text(gml_file, xpath="./geometry")
model.replace_text(filename, xpath="./time_loop/output/prefix")
model.write_input()
# run simulation with ogs
t0 = time.time()
print(">>> OGS started execution ... <<<")
run(
f"ogs {out_dir}/{prj_name} -o {out_dir} -m {out_dir} > {out_dir}/ogs-out.txt",
shell=True,
check=True,
)
tf = time.time()
print(">>> OGS terminated execution <<< Elapsed time: ", round(tf - t0, 2), " s.")
for h_j in h_list:
sneddon_numerical(h=h_j)
Info : Meshing 1D...
Info : [ 0%] Meshing curve 1 (Line)
Info : [ 20%] Meshing curve 2 (Line)
Info : [ 30%] Meshing curve 3 (Line)
Info : [ 40%] Meshing curve 4 (Line)
Info : [ 60%] Meshing curve 5 (Line)
Info : [ 70%] Meshing curve 6 (Line)
Info : [ 80%] Meshing curve 7 (Line)
Info : [ 90%] Meshing curve 8 (Line)
Info : Done meshing 1D (Wall 0.000526017s, CPU 0.000902s)
Info : Meshing 2D...
Info : [ 0%] Meshing surface 1 (Plane, Frontal-Delaunay)
Info : [ 0%] Blossom: 24032 internal 482 closed
INFO:root:Output: mesh_full_pf
INFO:root:Original mesh (read)
INFO:root:<meshio mesh object>
Number of points: 14439
Number of cells:
line: 40
line: 40
line: 40
line: 40
quad: 7878
quad: 6480
Cell sets: Bottom, Right, Top, Left, Computational_domain, gmsh:bounding_entities
Point data: gmsh:dim_tags
Cell data: gmsh:physical, gmsh:geometrical
Field data: Bottom, Right, Top, Left, Computational_domain
INFO:root:Detected mesh dimension: 2
INFO:root:##
INFO:root:Domain mesh (written)
INFO:root:14439 points in 3 dimensions
INFO:root:cells: 14358 quad
INFO:root:point_data=['gmsh:dim_tags']
INFO:root:cell_data=['gmsh:physical']
INFO:root:cell_sets=[]
INFO:root:##
INFO:root:Boundary mesh (written)
INFO:root:160 points in 3 dimensions
INFO:root:cells: 160 line
INFO:root:point_data=['gmsh:dim_tags']
INFO:root:cell_data=['gmsh:physical']
INFO:root:cell_sets=[]
INFO:root:##
INFO:root:Submesh Bottom (written)
INFO:root:41 points in 3 dimensions
INFO:root:cells: 40 line
INFO:root:point_data=['gmsh:dim_tags']
INFO:root:cell_data=['gmsh:physical']
INFO:root:cell_sets=[]
INFO:root:##
INFO:root:Submesh Right (written)
INFO:root:41 points in 3 dimensions
INFO:root:cells: 40 line
INFO:root:point_data=['gmsh:dim_tags']
INFO:root:cell_data=['gmsh:physical']
INFO:root:cell_sets=[]
INFO:root:##
INFO:root:Submesh Top (written)
INFO:root:41 points in 3 dimensions
INFO:root:cells: 40 line
INFO:root:point_data=['gmsh:dim_tags']
INFO:root:cell_data=['gmsh:physical']
INFO:root:cell_sets=[]
INFO:root:##
INFO:root:Submesh Left (written)
INFO:root:41 points in 3 dimensions
INFO:root:cells: 40 line
INFO:root:point_data=['gmsh:dim_tags']
INFO:root:cell_data=['gmsh:physical']
INFO:root:cell_sets=[]
INFO:root:##
Info : [ 0%] Blossom recombination completed (Wall 0.399129s, CPU 0.400634s): 7878 quads, 0 triangles, 0 invalid quads, 0 quads with Q < 0.1, avg Q = 0.793024, min Q = 0.371315
Info : [ 60%] Meshing surface 2 (Transfinite)
Info : Done meshing 2D (Wall 0.603961s, CPU 0.605542s)
Info : 14439 nodes 14848 elements
Info : Writing '/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/Tests/Data/PhaseField/kregime_jupyter_notebook/Kregime_Static_jupyter/mesh_full_pf.msh'...
Info : Done writing '/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/Tests/Data/PhaseField/kregime_jupyter_notebook/Kregime_Static_jupyter/mesh_full_pf.msh'
INFO:root:Submesh Computational_domain (written)
INFO:root:14439 points in 3 dimensions
INFO:root:cells: 14358 quad
INFO:root:point_data=['gmsh:dim_tags']
INFO:root:cell_data=['gmsh:physical']
INFO:root:cell_sets=[]
INFO:root:##
>>> OGS started execution ... <<<
>>> OGS terminated execution <<< Elapsed time: 6.13 s.
# As a post-process, we calculate the fracture opening.
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# As a post-process, we calculate the fracture opening.
def width_calculation(filename):
reader = pv.get_reader(f"{out_dir}/{filename}.pvd")
# --------------------------------------------------------------------------------
# Active the results of last time step
# --------------------------------------------------------------------------------
reader.set_active_time_value(reader.time_values[-1])
mesh = reader.read()[0]
# --------------------------------------------------------------------------------
# define grad d
# --------------------------------------------------------------------------------
mesh_d = mesh.compute_derivative(scalars="phasefield")
mesh_d["gradient"]
def gradients_to_dict(arr):
"""A helper method to label the gradients into a dictionary."""
keys = np.array(
["grad_dx", "grad_dy", "grad_dz", "grad_dx", "grad_dy", "grad_dz"]
)
keys = keys.reshape((2, 3))[:, : arr.shape[1]].ravel()
return dict(zip(keys, mesh_d["gradient"].T))
gradients_d = gradients_to_dict(mesh_d["gradient"])
mesh.point_data.update(gradients_d)
# --------------------------------------------------------------------------------
# define width at nodes
# --------------------------------------------------------------------------------
disp = mesh.point_data["displacement"]
grad_dx = mesh.point_data["grad_dx"]
grad_dy = mesh.point_data["grad_dy"]
num_points = disp.shape
Wnode = np.zeros(num_points[0])
for i, _x in enumerate(mesh.points):
u_x = disp[i][0]
u_y = disp[i][1]
gd_x = grad_dx[i]
gd_y = grad_dy[i]
Wnode[i] = 0.5 * (u_x * gd_x + u_y * gd_y)
mesh.point_data["Wnode"] = Wnode
# --------------------------------------------------------------------------------
# define width at nodes
# --------------------------------------------------------------------------------
# Normalize the vector
normal = [np.cos(Orientation), np.sin(Orientation), 0]
# Make points along that vector for the extent of your slices
point_a = mesh.center + np.array([1.5 * a0, 0, 0])
point_b = mesh.center + np.array([-1.5 * a0, 0, 0])
dist_a_b = ((point_b[0] - point_a[0]) ** 2 + (point_b[1] - point_a[1]) ** 2) ** 0.5
# Define the line/points for the slices
line = pv.Line(point_a, point_b, n_slices)
width_line = np.zeros(len(line.points))
r_i = np.zeros(len(line.points))
# Generate all of the slices
slices = pv.MultiBlock()
for i, point in enumerate(line.points):
slices.append(mesh.slice(normal=normal, origin=point))
slice_mesh = mesh.slice(normal=normal, origin=point)
y_slice = slice_mesh.points[:, 1]
Wnode_slice = slice_mesh.point_data["Wnode"]
width_i = np.trapz(Wnode_slice, x=y_slice) # noqa: NPY201
if width_i >= 0:
width_line[i] = width_i
r_i[i] = (
(point[0] - point_a[0]) ** 2 + (point[1] - point_a[1]) ** 2
) ** 0.5 - dist_a_b / 2
return r_i, width_line
def sneddon(h, ls, phasefield_model):
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def sneddon(h, ls, phasefield_model):
# Effective a for AT1/A2
if phasefield_model == "AT1":
a_eff = a0 * (1 + pi * ls / (4.0 * a0 * (3 * h / 8.0 / ls + 1.0)))
elif phasefield_model == "AT2":
a_eff = a0 * (1 + pi * ls / (4.0 * a0 * (h / (2.0 * ls) + 1.0)))
x = np.linspace(-1.0 * a_eff, a_eff, 40)
uy = []
for i in range(len(x)):
uy.append(
2 * a_eff * (1 - nu**2) * P / E * math.sqrt(1.0 - ((x[i]) / (a_eff)) ** 2)
)
return x, uy, a_eff
color = ["-.k", "ko", "-.r", "ro", "-.b", "bo", "-.g", "go"]
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color = ["-.k", "ko", "-.r", "ro", "-.b", "bo", "-.g", "go"]
Label = ["Closed form solution", "VPF-FEM"]
lineWIDTH = [1.5, 1.5, 1.5]
for j, h_j in enumerate(h_list):
r_i_num = []
width_line_num = []
filename = f"results_h_{h_j:0.4f}"
print(filename)
width_calculation(filename)
r_i_num = width_calculation(filename)[0]
width_line_num = width_calculation(filename)[1]
ls = 2 * h_j
x_Sneddon = sneddon(h_j, ls, phasefield_model)[0]
uy_Sneddon = sneddon(h_j, ls, phasefield_model)[1]
a_eff_Sneddon = sneddon(h_j, ls, phasefield_model)[2]
plt.plot(
np.array(x_Sneddon[:]),
np.array(uy_Sneddon[:]),
color[2 * j],
fillstyle="none",
markersize=0,
linewidth=lineWIDTH[0],
label=f"Closed form solution - $h= ${h_j:0.4f}",
)
plt.plot(
np.array(r_i_num[:]),
np.array(width_line_num[:]),
color[2 * j + 1],
fillstyle="none",
markersize=6,
linewidth=lineWIDTH[1],
label=f"VPF - $h =${h_j:0.4f}",
)
# ------------------------------------------------------------------------
plt.rcParams["figure.figsize"] = [40, 20]
plt.rcParams["figure.dpi"] = 1600
plt.ylabel("$w_n$ [m]", fontsize=14)
plt.xlabel("$r$ [m]", fontsize=14)
plt.grid(linestyle="dashed")
plt.title(f"{phasefield_model}")
legend = plt.legend(bbox_to_anchor=(1.04, 1), loc="upper left")
plt.show()
results_h_0.0100
DEBUG:matplotlib.pyplot:Loaded backend module://matplotlib_inline.backend_inline version unknown.
DEBUG:matplotlib.pyplot:Loaded backend module://matplotlib_inline.backend_inline version unknown.
DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0.
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/D050000L.otf', name='D050000L', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/C059-BdIta.otf', name='C059', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/adobe-source-code-pro/SourceCodePro-Semibold.otf', name='Source Code Pro', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/URWGothic-Demi.otf', name='URW Gothic', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/P052-Roman.otf', name='P052', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gnu-free/FreeMonoOblique.otf', name='FreeMono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/URWBookman-LightItalic.otf', name='URW Bookman', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/P052-Italic.otf', name='P052', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/C059-Italic.otf', name='C059', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/Z003-MediumItalic.otf', name='Z003', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gnu-free/FreeSerifBold.otf', name='FreeSerif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gnu-free/FreeSerif.otf', name='FreeSerif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gnu-free/FreeSans.otf', name='FreeSans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gnu-free/FreeSansBold.otf', name='FreeSans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gnu-free/FreeSansOblique.otf', name='FreeSans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/NimbusMonoPS-Regular.otf', name='Nimbus Mono PS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gnu-free/FreeSansBoldOblique.otf', name='FreeSans', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/URWBookman-Demi.otf', name='URW Bookman', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/NimbusSansNarrow-Oblique.otf', name='Nimbus Sans Narrow', style='oblique', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/URWBookman-Light.otf', name='URW Bookman', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/adobe-source-code-pro/SourceCodePro-MediumIt.otf', name='Source Code Pro', style='italic', variant='normal', weight=500, stretch='normal', size='scalable')) = 11.145
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/adobe-source-code-pro/SourceCodePro-ExtraLightIt.otf', name='Source Code Pro', style='italic', variant='normal', weight=200, stretch='normal', size='scalable')) = 11.24
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/P052-Bold.otf', name='P052', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/StandardSymbolsPS.otf', name='Standard Symbols PS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gnu-free/FreeMonoBoldOblique.otf', name='FreeMono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/adobe-source-code-pro/SourceCodePro-LightIt.otf', name='Source Code Pro', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/adobe-source-code-pro/SourceCodePro-Medium.otf', name='Source Code Pro', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gnu-free/FreeSerifItalic.otf', name='FreeSerif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/NimbusSans-BoldItalic.otf', name='Nimbus Sans', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/URWGothic-Book.otf', name='URW Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gnu-free/FreeSerifBoldItalic.otf', name='FreeSerif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/NimbusRoman-BoldItalic.otf', name='Nimbus Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/adobe-source-code-pro/SourceCodePro-SemiboldIt.otf', name='Source Code Pro', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/adobe-source-code-pro/SourceCodePro-Black.otf', name='Source Code Pro', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/adobe-source-code-pro/SourceCodePro-Regular.otf', name='Source Code Pro', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gnu-free/FreeMono.otf', name='FreeMono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/NimbusSans-Italic.otf', name='Nimbus Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/C059-Bold.otf', name='C059', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/adobe-source-code-pro/SourceCodePro-BoldIt.otf', name='Source Code Pro', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gnu-free/FreeMonoBold.otf', name='FreeMono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/NimbusRoman-Bold.otf', name='Nimbus Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/NimbusSansNarrow-Regular.otf', name='Nimbus Sans Narrow', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/NimbusRoman-Italic.otf', name='Nimbus Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/URWGothic-DemiOblique.otf', name='URW Gothic', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/adobe-source-code-pro/SourceCodePro-Bold.otf', name='Source Code Pro', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/NimbusSansNarrow-BoldOblique.otf', name='Nimbus Sans Narrow', style='oblique', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/URWGothic-BookOblique.otf', name='URW Gothic', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/NimbusSans-Bold.otf', name='Nimbus Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/NimbusRoman-Regular.otf', name='Nimbus Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/adobe-source-code-pro/SourceCodePro-It.otf', name='Source Code Pro', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/NimbusMonoPS-Bold.otf', name='Nimbus Mono PS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/P052-BoldItalic.otf', name='P052', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/C059-Roman.otf', name='C059', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/URWBookman-DemiItalic.otf', name='URW Bookman', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/adobe-source-code-pro/SourceCodePro-Light.otf', name='Source Code Pro', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/NimbusSans-Regular.otf', name='Nimbus Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/NimbusMonoPS-BoldItalic.otf', name='Nimbus Mono PS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/adobe-source-code-pro/SourceCodePro-ExtraLight.otf', name='Source Code Pro', style='normal', variant='normal', weight=200, stretch='normal', size='scalable')) = 10.24
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/NimbusMonoPS-Italic.otf', name='Nimbus Mono PS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/adobe-source-code-pro/SourceCodePro-BlackIt.otf', name='Source Code Pro', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525
DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='/usr/share/fonts/gsfonts/NimbusSansNarrow-Bold.otf', name='Nimbus Sans Narrow', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535
DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('/var/lib/gitlab-runner/builds/e3EQ9HiK/0/ogs/build/release-petsc/.venv/lib/python3.12/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf') with score of 0.050000.
DEBUG:matplotlib.texmanager:family: serif, package: \usepackage{type1ec}, font: Computer Modern Roman, skipped: DejaVu Serif, Bitstream Vera Serif
DEBUG:matplotlib.texmanager:family: sans-serif, package: \usepackage{type1ec}, font: Computer Modern Sans Serif, skipped: DejaVu Sans, Bitstream Vera Sans
DEBUG:matplotlib.texmanager:family: cursive, package: \usepackage{chancery}, font: Zapf Chancery, skipped: Apple Chancery, Textile
DEBUG:matplotlib.texmanager:family: monospace, package: \usepackage{type1ec}, font: Computer Modern Typewriter, skipped: DejaVu Sans Mono, Bitstream Vera Sans Mono
DEBUG:matplotlib.dviread:Dvi: /var/lib/gitlab-runner/.cache/matplotlib/tex.cache/84/4f/844f707e0917555faafa721cd5105dbd.dvi
DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: header=l3backend-dvips.pro
DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt
DEBUG:matplotlib.dviread:opening tfm file /usr/share/texmf-dist/fonts/tfm/public/cm/cmss10.tfm
DEBUG:matplotlib.dviread:lh=18, bc=0, ec=127, nw=52, nh=16, nd=11
DEBUG:matplotlib.texmanager:family: serif, package: \usepackage{type1ec}, font: Computer Modern Roman, skipped: DejaVu Serif, Bitstream Vera Serif
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DEBUG:matplotlib.dviread:lh=18, bc=0, ec=127, nw=97, nh=15, nd=9
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DEBUG:matplotlib.dviread:Dvi: /var/lib/gitlab-runner/.cache/matplotlib/tex.cache/85/17/8517ecfac9639c60aa1ba33f71a6ba0b.dvi
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DEBUG:matplotlib.dviread:lh=18, bc=0, ec=127, nw=44, nh=15, nd=16
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DEBUG:matplotlib.dviread:Dvi: /var/lib/gitlab-runner/.cache/matplotlib/tex.cache/af/14/af14988e6d5123cc71723954c0f475cb.dvi
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DEBUG:matplotlib.texmanager:family: serif, package: \usepackage{type1ec}, font: Computer Modern Roman, skipped: DejaVu Serif, Bitstream Vera Serif
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DEBUG:matplotlib.texmanager:family: cursive, package: \usepackage{chancery}, font: Zapf Chancery, skipped: Apple Chancery, Textile
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DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: header=l3backend-dvips.pro
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DEBUG:matplotlib.texmanager:family: cursive, package: \usepackage{chancery}, font: Zapf Chancery, skipped: Apple Chancery, Textile
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DEBUG:matplotlib.dviread:Dvi: /var/lib/gitlab-runner/.cache/matplotlib/tex.cache/84/4f/844f707e0917555faafa721cd5105dbd.dvi
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DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt
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DEBUG:matplotlib.texmanager:family: cursive, package: \usepackage{chancery}, font: Zapf Chancery, skipped: Apple Chancery, Textile
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DEBUG:matplotlib.dviread:Dvi: /var/lib/gitlab-runner/.cache/matplotlib/tex.cache/83/da/83dadff3e4191b3b60b3a0253eed0fe6.dvi
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DEBUG:matplotlib.texmanager:family: serif, package: \usepackage{type1ec}, font: Computer Modern Roman, skipped: DejaVu Serif, Bitstream Vera Serif
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DEBUG:matplotlib.texmanager:family: cursive, package: \usepackage{chancery}, font: Zapf Chancery, skipped: Apple Chancery, Textile
DEBUG:matplotlib.texmanager:family: monospace, package: \usepackage{type1ec}, font: Computer Modern Typewriter, skipped: DejaVu Sans Mono, Bitstream Vera Sans Mono
DEBUG:matplotlib.dviread:Dvi: /var/lib/gitlab-runner/.cache/matplotlib/tex.cache/84/4f/844f707e0917555faafa721cd5105dbd.dvi
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DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt
DEBUG:matplotlib.texmanager:family: serif, package: \usepackage{type1ec}, font: Computer Modern Roman, skipped: DejaVu Serif, Bitstream Vera Serif
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DEBUG:matplotlib.texmanager:family: cursive, package: \usepackage{chancery}, font: Zapf Chancery, skipped: Apple Chancery, Textile
DEBUG:matplotlib.texmanager:family: monospace, package: \usepackage{type1ec}, font: Computer Modern Typewriter, skipped: DejaVu Sans Mono, Bitstream Vera Sans Mono
DEBUG:matplotlib.dviread:Dvi: /var/lib/gitlab-runner/.cache/matplotlib/tex.cache/eb/e2/ebe27ee0b65d1cccb9d1d5910e5f72d9.dvi
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DEBUG:matplotlib.texmanager:family: serif, package: \usepackage{type1ec}, font: Computer Modern Roman, skipped: DejaVu Serif, Bitstream Vera Serif
DEBUG:matplotlib.texmanager:family: sans-serif, package: \usepackage{type1ec}, font: Computer Modern Sans Serif, skipped: DejaVu Sans, Bitstream Vera Sans
DEBUG:matplotlib.texmanager:family: cursive, package: \usepackage{chancery}, font: Zapf Chancery, skipped: Apple Chancery, Textile
DEBUG:matplotlib.texmanager:family: monospace, package: \usepackage{type1ec}, font: Computer Modern Typewriter, skipped: DejaVu Sans Mono, Bitstream Vera Sans Mono
DEBUG:matplotlib.dviread:Dvi: /var/lib/gitlab-runner/.cache/matplotlib/tex.cache/84/4f/844f707e0917555faafa721cd5105dbd.dvi
DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: header=l3backend-dvips.pro
DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt
DEBUG:matplotlib.texmanager:family: serif, package: \usepackage{type1ec}, font: Computer Modern Roman, skipped: DejaVu Serif, Bitstream Vera Serif
DEBUG:matplotlib.texmanager:family: sans-serif, package: \usepackage{type1ec}, font: Computer Modern Sans Serif, skipped: DejaVu Sans, Bitstream Vera Sans
DEBUG:matplotlib.texmanager:family: cursive, package: \usepackage{chancery}, font: Zapf Chancery, skipped: Apple Chancery, Textile
DEBUG:matplotlib.texmanager:family: monospace, package: \usepackage{type1ec}, font: Computer Modern Typewriter, skipped: DejaVu Sans Mono, Bitstream Vera Sans Mono
DEBUG:matplotlib.dviread:Dvi: /var/lib/gitlab-runner/.cache/matplotlib/tex.cache/84/4f/844f707e0917555faafa721cd5105dbd.dvi
DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: header=l3backend-dvips.pro
DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt
DEBUG:matplotlib.texmanager:family: serif, package: \usepackage{type1ec}, font: Computer Modern Roman, skipped: DejaVu Serif, Bitstream Vera Serif
DEBUG:matplotlib.texmanager:family: sans-serif, package: \usepackage{type1ec}, font: Computer Modern Sans Serif, skipped: DejaVu Sans, Bitstream Vera Sans
DEBUG:matplotlib.texmanager:family: cursive, package: \usepackage{chancery}, font: Zapf Chancery, skipped: Apple Chancery, Textile
DEBUG:matplotlib.texmanager:family: monospace, package: \usepackage{type1ec}, font: Computer Modern Typewriter, skipped: DejaVu Sans Mono, Bitstream Vera Sans Mono
DEBUG:matplotlib.dviread:Dvi: /var/lib/gitlab-runner/.cache/matplotlib/tex.cache/84/4f/844f707e0917555faafa721cd5105dbd.dvi
DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: header=l3backend-dvips.pro
DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt
DEBUG:matplotlib.texmanager:family: serif, package: \usepackage{type1ec}, font: Computer Modern Roman, skipped: DejaVu Serif, Bitstream Vera Serif
DEBUG:matplotlib.texmanager:family: sans-serif, package: \usepackage{type1ec}, font: Computer Modern Sans Serif, skipped: DejaVu Sans, Bitstream Vera Sans
DEBUG:matplotlib.texmanager:family: cursive, package: \usepackage{chancery}, font: Zapf Chancery, skipped: Apple Chancery, Textile
DEBUG:matplotlib.texmanager:family: monospace, package: \usepackage{type1ec}, font: Computer Modern Typewriter, skipped: DejaVu Sans Mono, Bitstream Vera Sans Mono
DEBUG:matplotlib.dviread:Dvi: /var/lib/gitlab-runner/.cache/matplotlib/tex.cache/84/4f/844f707e0917555faafa721cd5105dbd.dvi
DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: header=l3backend-dvips.pro
DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt
DEBUG:matplotlib.texmanager:family: serif, package: \usepackage{type1ec}, font: Computer Modern Roman, skipped: DejaVu Serif, Bitstream Vera Serif
DEBUG:matplotlib.texmanager:family: sans-serif, package: \usepackage{type1ec}, font: Computer Modern Sans Serif, skipped: DejaVu Sans, Bitstream Vera Sans
DEBUG:matplotlib.texmanager:family: cursive, package: \usepackage{chancery}, font: Zapf Chancery, skipped: Apple Chancery, Textile
DEBUG:matplotlib.texmanager:family: monospace, package: \usepackage{type1ec}, font: Computer Modern Typewriter, skipped: DejaVu Sans Mono, Bitstream Vera Sans Mono
DEBUG:matplotlib.dviread:Dvi: /var/lib/gitlab-runner/.cache/matplotlib/tex.cache/84/4f/844f707e0917555faafa721cd5105dbd.dvi
DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: header=l3backend-dvips.pro
DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt
DEBUG:matplotlib.texmanager:family: serif, package: \usepackage{type1ec}, font: Computer Modern Roman, skipped: DejaVu Serif, Bitstream Vera Serif
DEBUG:matplotlib.texmanager:family: sans-serif, package: \usepackage{type1ec}, font: Computer Modern Sans Serif, skipped: DejaVu Sans, Bitstream Vera Sans
DEBUG:matplotlib.texmanager:family: cursive, package: \usepackage{chancery}, font: Zapf Chancery, skipped: Apple Chancery, Textile
DEBUG:matplotlib.texmanager:family: monospace, package: \usepackage{type1ec}, font: Computer Modern Typewriter, skipped: DejaVu Sans Mono, Bitstream Vera Sans Mono
DEBUG:matplotlib.dviread:Dvi: /var/lib/gitlab-runner/.cache/matplotlib/tex.cache/84/4f/844f707e0917555faafa721cd5105dbd.dvi
DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: header=l3backend-dvips.pro
DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt
DEBUG:matplotlib.texmanager:family: serif, package: \usepackage{type1ec}, font: Computer Modern Roman, skipped: DejaVu Serif, Bitstream Vera Serif
DEBUG:matplotlib.texmanager:family: sans-serif, package: \usepackage{type1ec}, font: Computer Modern Sans Serif, skipped: DejaVu Sans, Bitstream Vera Sans
DEBUG:matplotlib.texmanager:family: cursive, package: \usepackage{chancery}, font: Zapf Chancery, skipped: Apple Chancery, Textile
DEBUG:matplotlib.texmanager:family: monospace, package: \usepackage{type1ec}, font: Computer Modern Typewriter, skipped: DejaVu Sans Mono, Bitstream Vera Sans Mono
DEBUG:matplotlib.dviread:Dvi: /var/lib/gitlab-runner/.cache/matplotlib/tex.cache/84/4f/844f707e0917555faafa721cd5105dbd.dvi
DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: header=l3backend-dvips.pro
DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt
DEBUG:matplotlib.texmanager:family: serif, package: \usepackage{type1ec}, font: Computer Modern Roman, skipped: DejaVu Serif, Bitstream Vera Serif
DEBUG:matplotlib.texmanager:family: sans-serif, package: \usepackage{type1ec}, font: Computer Modern Sans Serif, skipped: DejaVu Sans, Bitstream Vera Sans
DEBUG:matplotlib.texmanager:family: cursive, package: \usepackage{chancery}, font: Zapf Chancery, skipped: Apple Chancery, Textile
DEBUG:matplotlib.texmanager:family: monospace, package: \usepackage{type1ec}, font: Computer Modern Typewriter, skipped: DejaVu Sans Mono, Bitstream Vera Sans Mono
DEBUG:matplotlib.dviread:Dvi: /var/lib/gitlab-runner/.cache/matplotlib/tex.cache/84/4f/844f707e0917555faafa721cd5105dbd.dvi
DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: header=l3backend-dvips.pro
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To decrease computing time, we perform the simulation with an one coarse mesh; Mesh sensitivity can be investigated in order to assess the convergence of the opening profile for various mesh discretizations. Following are the mesh sensivity results for for Models $\texttt{AT}_1$ and $\texttt{AT}_2$ ($h=0.01,~0.005,~\text{and} ~0.0025$ m.)
Our mesh size sensitivity study shows even with coarse mesh. The results away from crack tips agree well with the Sneddon solution. Using finer mesh demonstrates that the opening along the whole crack length is accurate compared with the closed-form solution.
It’s worth noting that we estimate width as part of post-processing (using the line integral and a given crack normal vector). However, near crack tips the crack normal vector is different to the given normal vector, so the width values are inaccurate near crack tips. For the sake of simplicity, we neglect determining the normal crack vector here; for more information on the line integral approach, see Yoshioka et al., 2020.
[1] Yoshioka, Keita, Francesco Parisio, Dmitri Naumov, Renchao Lu, Olaf Kolditz, and Thomas Nagel. Comparative verification of discrete and smeared numerical approaches for the simulation of hydraulic fracturing. GEM-International Journal on Geomathematics 10, no. 1 (2019): 1-35.
[2] Yoshioka, Keita, Dmitri Naumov, and Olaf Kolditz. On crack opening computation in variational phase-field models for fracture. Computer Methods in Applied Mechanics and Engineering 369 (2020): 113210.
[3] Sneddon, Ian Naismith, and Morton Lowengrub. Crack problems in the classical theory of elasticity. 1969, 221 P (1969).
This article was written by Mostafa Mollaali, Keita Yoshioka. If you are missing something or you find an error please let us know.
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