OpenGeoSys

Surfing boundary

This page is based on a Jupyter notebook.

Problem description

Consider a plate, $\Omega=[0,2]\times [-0.5,0.5]$, with an explicit edge crack, $\Gamma=[0,0.5]\times \{0\}$; that is subjected to a time dependent crack opening displacement:

\begin{eqnarray} \label{eq:surfing_bc} \mathbf{u}(x,y,t)= \mathbf{U}(x-\text{v}t,y) \quad \text{on} \quad \partial\Omega_D, \end{eqnarray} where $\text{v}$ is an imposed loading velocity; and $\mathbf{U}$ is the asymptotic solution for the Mode-I crack opening displacement \begin{eqnarray} \label{eq:asymptotic} U_x= \dfrac{K_I}{2\mu} \sqrt{\dfrac{r}{2\pi}} (\kappa-\cos \varphi) \cos \frac{\varphi}{2}, \nonumber \ U_y= \dfrac{K_I}{2\mu} \sqrt{\dfrac{r}{2\pi}} (\kappa-\cos \varphi) \sin \frac{\varphi}{2}, \end{eqnarray}

where $K_I$ is the stress intensity factor, $\kappa=(3-\nu)/(1+\nu)$ and $\mu=E / 2 (1 + \nu) $; $(r,\varphi)$ are the polar coordinate system, where the origin is crack tip. Also, we used $G_\mathrm{c}=K_{Ic}^2(1-\nu^2)/E$ as the fracture surface energy under plane strain condition. Table 1 lists the material properties and geometry of the numerical model.

Schematic view of surfing boundary condition benchmark
Schematic view of surfing boundary condition benchmark.

Input Data

Name Value Unit Symbol
Young’s modulus 210x$10^3$ MPa $E$
Critical energy release rate 2.7 MPa$\cdot$mm $G_{c}$
Poisson’s ratio 0.3 $-$ $\nu$
Regularization parameter 2$h$ mm $\ell_s$
Imposed loading velocity 1.5 mm/s $\text{v}$
Length $2$ mm $L$
Height $1$ mm $H$
Initial crack length $0.5$ mm $a_0$
import os… (click to toggle) 
import os
import time
from pathlib import Path
from subprocess import run

import matplotlib.pyplot as plt
import numpy as np
import ogstools as ot
import pyvista as pv
from scipy.spatial import Delaunay
x_tip_Initial = 0.5… (click to toggle) 
x_tip_Initial = 0.5
y_tip_Initial = 0.5
Height = 1.0

Orientation = 0
h = 0.05
G_i = 2.7
ls = 2 * h
# We set ls=2h in our simulation
phasefield_model = "AT1"  # AT1 and AT2

Paths and project file name

# file's name… (click to toggle) 
# file's name
prj_name = "surfing.prj"

out_dir = Path(os.environ.get("OGS_TESTRUNNER_OUT_DIR", "_out"))
if not out_dir.exists():
    out_dir.mkdir(parents=True)

Mesh generation

# https://www.opengeosys.org/docs/tools/meshing/structured-mesh-generation/… (click to toggle) 
# https://www.opengeosys.org/docs/tools/meshing/structured-mesh-generation/
run(
    f"generateStructuredMesh -o {out_dir}/surfing_quad_1x2.vtu -e quad --lx 2 --nx {round(2/h)+1} --ly 1 --ny {round(1/h)+1}",
    shell=True,
    check=True,
)
run(
    f"NodeReordering -i {out_dir}/surfing_quad_1x2.vtu -o {out_dir}/surfing_quad_1x2_NR.vtu",
    shell=True,
    check=True,
)
[2024-12-20 13:05:29.819] [ogs] [info] Mesh created: 924 nodes, 861 elements.

[2024-12-20 13:05:31.278] [ogs] [info] Reordering nodes... 
[2024-12-20 13:05:31.278] [ogs] [info] Corrected 0 elements.
[2024-12-20 13:05:31.283] [ogs] [info] VTU file written.

CompletedProcess(args='NodeReordering -i /var/lib/gitlab-runner/builds/vZ6vnZiU/1/ogs/build/release-petsc/Tests/Data/PhaseField/surfing_jupyter_notebook/surfing_pyvista/surfing_quad_1x2.vtu -o /var/lib/gitlab-runner/builds/vZ6vnZiU/1/ogs/build/release-petsc/Tests/Data/PhaseField/surfing_jupyter_notebook/surfing_pyvista/surfing_quad_1x2_NR.vtu', returncode=0)

Pre-processing

At fracture, we set the initial phase field to zero.

pv.set_plot_theme("document")… (click to toggle) 
pv.set_plot_theme("document")
pv.set_jupyter_backend("static")

mesh = pv.read(f"{out_dir}/surfing_quad_1x2_NR.vtu")
phase_field = np.ones((len(mesh.points), 1))


for node_id, x in enumerate(mesh.points):
    if (
        x[0] < x_tip_Initial + h / 10
        and x[1] < Height / 2 + h
        and x[1] > Height / 2 - h
    ):
        phase_field[node_id] = 0.0

mesh.point_data["pf-ic"] = phase_field
mesh.save(f"{out_dir}/surfing_quad_1x2_NR_pf_ic.vtu")

pf_ic = mesh.point_data["pf-ic"]
sargs = {
    "title": "pf-ic",
    "title_font_size": 20,
    "label_font_size": 15,
    "n_labels": 5,
    "position_x": 0.24,
    "position_y": 0.0,
    "fmt": "%.1f",
    "width": 0.5,
}
clim = [0, 1.0]

p = pv.Plotter(shape=(1, 1), border=False)
p.add_mesh(
    mesh,
    scalars=pf_ic,
    show_edges=True,
    show_scalar_bar=True,
    colormap="coolwarm",
    clim=clim,
    scalar_bar_args=sargs,
)

p.view_xy()
p.camera.zoom(1.5)
p.window_size = [800, 400]
p.show()

png

Run the simulation

# Change the length scale and phasefield model in project file… (click to toggle) 
# Change the length scale and phasefield model in project file
model = ot.Project(
    input_file=prj_name,
    output_file=f"{out_dir}/{prj_name}",
    MKL=True,
    args=f"-o {out_dir}",
)

gml_file = Path("./surfing.gml").resolve()

model.replace_parameter_value(name="ls", value=2 * h)
model.replace_text(phasefield_model, xpath="./processes/process/phasefield_model")
model.replace_text(gml_file, xpath="./geometry")
model.replace_text(Path("./Surfing_python.py").resolve(), xpath="./python_script")
model.write_input()

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.")
>>> OGS started execution ... <<<

>>> OGS terminated execution  <<< Elapsed time:  19.84  s.

Results

We computed the energy release rate using $G_{\theta}$ method (Destuynder et al., 1983; Li et al., 2016) and plot the errors against the theoretical numerical toughness i.e. $(G_c^{\text{eff}})_{\texttt{num}}=G_c(1+\frac{h}{2\ell})$ for $\texttt{AT}_2$, and $(G_c^{\text{eff}})_{\texttt{num}}=G_c(1+\frac{3h}{8\ell})$ for $\texttt{AT}_1$ (Bourdin et al., 2008).

Alt text
Phase field and $\theta$ profile for the volumetric deviatoric $\texttt{AT}_2$ models. We use virtual perturbation of $\theta$ to compute energy release rate using $G_{\theta}$ Dubois et al., 1998. The $\theta$ value is 1 inside of $B_{r_{in}}(P)$, 0 outside, and a linear interpolation in between. We set $r_{in}=4\ell$ and $r_{out}=2.5r_{in}$ (see Li et al., 2016).

We computed the energy release rate using $G_{\theta}$ method (Destuynder et al., 1983; Li et al., 2016) and plot the errors against the theoretical numerical toughness i.e. $(G_c^{\text{eff}})_{\texttt{num}}=G_c(1+\frac{h}{2\ell})$ for $\texttt{AT}_2$, and $(G_c^{\text{eff}})_{\texttt{num}}=G_c(1+\frac{3h}{8\ell})$ for $\texttt{AT}_1$ (Bourdin et al., 2008).

Alt text
Phase field and $\theta$ profile for the volumetric deviatoric $\texttt{AT}_2$ models. We use virtual perturbation of $\theta$ to compute energy release rate using $G_{\theta}$ Dubois et al., 1998. The $\theta$ value is 1 inside of $B_{r_{in}}(P)$, 0 outside, and a linear interpolation in between. We set $r_{in}=4\ell$ and $r_{out}=2.5r_{in}$ (see Li et al., 2016).

R_inn = 4 * ls… (click to toggle) 
R_inn = 4 * ls
R_out = 2.5 * R_inn

if phasefield_model == "AT1":
    G_eff = G_i * (1 + 3 * h / (8 * ls))
elif phasefield_model == "AT2":
    G_eff = G_i * (1 + h / (2 * ls))

We run the simulation with a coarse mesh here to reduce computing time; however, a finer mesh would give a more accurate results. The energy release rate and its error for Models $\texttt{AT}_1$ and $\texttt{AT}_2$ with a mesh size of $h=0.005$ are shown below.

Alt text Alt text

Post-processing

reader = pv.get_reader(f"{out_dir}/surfing.pvd")… (click to toggle) 
reader = pv.get_reader(f"{out_dir}/surfing.pvd")
G_theta_time = np.zeros((len(reader.time_values), 2))


for t, time_value in enumerate(reader.time_values):
    reader.set_active_time_value(time_value)

    mesh = reader.read()[0]
    points = mesh.point_data["phasefield"].shape[0]
    xs = mesh.points[:, 0]
    ys = mesh.points[:, 1]
    pf = mesh.point_data["phasefield"]
    sigma = mesh.point_data["sigma"]
    disp = mesh.point_data["displacement"]

    num_points = disp.shape
    theta = np.zeros(num_points)

    # --------------------------------------------------------------------------------
    # find fracture tip
    # --------------------------------------------------------------------------------
    min_pf = min(pf[:])
    coord_pf_0p5 = mesh.points[pf < 0.5]
    if min_pf <= 0.5:
        coord_pf_0p5[np.argmax(coord_pf_0p5, axis=0)[0]][1]
        x0 = coord_pf_0p5[np.argmax(coord_pf_0p5, axis=0)[0]][0]
        y0 = coord_pf_0p5[np.argmax(coord_pf_0p5, axis=0)[0]][1]
    else:
        x0 = x_tip_Initial
        y0 = y_tip_Initial
    Crack_position = [x0, y0]
    # --------------------------------------------------------------------------------
    # define \theta
    # --------------------------------------------------------------------------------
    for i, x in enumerate(mesh.points):
        # distance from the crack tip
        R = np.sqrt((x[0] - Crack_position[0]) ** 2 + (x[1] - Crack_position[1]) ** 2)
        if R_inn > R:
            theta_funct = 1.0
        elif R_out < R:
            theta_funct = 0.0
        else:
            theta_funct = (R - R_out) / (R_inn - R_out)
        theta[i][0] = theta_funct * np.cos(Orientation)
        theta[i][1] = theta_funct * np.sin(Orientation)

    mesh.point_data["theta"] = theta

    # --------------------------------------------------------------------------------
    # define grad \theta
    # --------------------------------------------------------------------------------
    mesh_theta = mesh.compute_derivative(scalars="theta")
    mesh_theta["gradient"]

    keys = np.array(
        ["thetax_x", "thetax_y", "thetax_z", "thetay_x", "thetay_y", "thetay_z"]
    )
    keys = keys.reshape((2, 3))[:, : mesh_theta["gradient"].shape[1]].ravel()
    gradients_theta = dict(zip(keys, mesh_theta["gradient"].T))
    mesh.point_data.update(gradients_theta)
    # --------------------------------------------------------------------------------
    # define grad u
    # --------------------------------------------------------------------------------
    mesh_u = mesh.compute_derivative(scalars="displacement")
    mesh_u["gradient"]

    keys = np.array(["Ux_x", "Ux_y", "Ux_z", "Uy_x", "Uy_y", "Uy_z"])
    keys = keys.reshape((2, 3))[:, : mesh_u["gradient"].shape[1]].ravel()
    gradients_u = dict(zip(keys, mesh_u["gradient"].T))
    mesh.point_data.update(gradients_u)

    # --------------------------------------------------------------------------------
    # define G_theta
    # --------------------------------------------------------------------------------
    G_theta_i = np.zeros(num_points[0])
    sigma = mesh.point_data["sigma"]
    Ux_x = mesh.point_data["Ux_x"]
    Ux_y = mesh.point_data["Ux_y"]
    Uy_x = mesh.point_data["Uy_x"]
    Uy_y = mesh.point_data["Uy_y"]

    thetax_x = mesh.point_data["thetax_x"]
    thetax_y = mesh.point_data["thetax_y"]
    thetay_x = mesh.point_data["thetay_x"]
    thetay_y = mesh.point_data["thetay_y"]

    for i, _x in enumerate(mesh.points):
        # ---------------------------------------------------------------------------
        sigma_xx = sigma[i][0]
        sigma_yy = sigma[i][1]
        sigma_xy = sigma[i][3]

        Ux_x_i = Ux_x[i]
        Ux_y_i = Ux_y[i]
        Uy_x_i = Uy_x[i]
        Uy_y_i = Uy_y[i]

        thetax_x_i = thetax_x[i]
        thetax_y_i = thetax_y[i]
        thetay_x_i = thetay_x[i]
        thetay_y_i = thetay_y[i]
        # ---------------------------------------------------------------------------
        dUdTheta_11 = Ux_x_i * thetax_x_i + Ux_y_i * thetay_x_i
        dUdTheta_12 = Ux_x_i * thetax_y_i + Ux_y_i * thetay_y_i
        dUdTheta_21 = Uy_x_i * thetax_x_i + Uy_y_i * thetay_x_i
        dUdTheta_22 = Uy_x_i * thetax_y_i + Uy_y_i * thetay_y_i
        trace_sigma_grad_u_grad_theta = (
            sigma_xx * dUdTheta_11
            + sigma_xy * (dUdTheta_12 + dUdTheta_21)
            + sigma_yy * dUdTheta_22
        )
        trace_sigma_grad_u = (
            sigma_xx * Ux_x_i + sigma_xy * (Uy_x_i + Ux_y_i) + sigma_yy * Uy_y_i
        )
        div_theta_i = thetax_x_i + thetay_y_i
        G_theta_i[i] = (
            trace_sigma_grad_u_grad_theta - 0.5 * trace_sigma_grad_u * div_theta_i
        )
    mesh.point_data["G_theta_node"] = G_theta_i
    # --------------------------------------------------------------------------------
    # Integral G_theta
    # --------------------------------------------------------------------------------
    X = mesh.points[:, 0]
    Y = mesh.points[:, 1]
    G_theta_i = mesh.point_data["G_theta_node"]

    domain_points = np.array(list(zip(X, Y)))
    tri = Delaunay(domain_points)

    def area_from_3_points(x, y, z):
        return np.sqrt(np.sum(np.cross(x - y, x - z), axis=-1) ** 2) / 2

    G_theta = 0
    for vertices in tri.simplices:
        mean_value = (
            G_theta_i[vertices[0]] + G_theta_i[vertices[1]] + G_theta_i[vertices[2]]
        ) / 3
        area = area_from_3_points(
            domain_points[vertices[0]],
            domain_points[vertices[1]],
            domain_points[vertices[2]],
        )
        G_theta += mean_value * area
    G_theta_time[t][1] = G_theta
    G_theta_time[t][0] = time_value
mesh.save(f"{out_dir}/surfing_Post_Processing.vtu")

Plots

plt.xlabel("$t$", fontsize=14)… (click to toggle) 
plt.xlabel("$t$", fontsize=14)
plt.ylabel(
    r"$\frac{|{G}_\mathrm{\theta}-({G}_\mathrm{c}^{\mathrm{eff}})_\mathrm{num}|}{({G}_\mathrm{c}^{\mathrm{eff}})_\mathrm{num}}\times 100\%$",
    fontsize=14,
)
plt.plot(
    G_theta_time[:, 0],
    abs(G_theta_time[:, 1]) / G_eff,
    "-ob",
    fillstyle="none",
    linewidth=1.5,
    label=f"Phase-field {phasefield_model}",
)
plt.plot(
    G_theta_time[:, 0],
    np.append(0, np.ones(len(G_theta_time[:, 0]) - 1)),
    "-k",
    fillstyle="none",
    linewidth=1.5,
    label="Closed form",
)
plt.grid(linestyle="dashed")
plt.xlim(-0.05, 0.8)
legend = plt.legend(loc="lower right")
plt.show()

plt.xlabel("$t$", fontsize=14)
plt.ylabel(
    r"$\frac{|{G}_\mathrm{\theta}-({G}_\mathrm{c}^{\mathrm{eff}})_\mathrm{num}|}{({G}_\mathrm{c}^{\mathrm{eff}})_\mathrm{num}}\times 100\%$",
    fontsize=14,
)
plt.plot(
    G_theta_time[:, 0],
    abs(G_theta_time[:, 1] - G_eff) / G_eff * 100,
    "-ob",
    fillstyle="none",
    linewidth=1.5,
    label=f"Phase-field {phasefield_model}",
)
plt.grid(linestyle="dashed")
plt.xlim(-0.05, 0.8)
# plt.ylim(0,4)
legend = plt.legend(loc="upper right")
plt.show()

png

png

Hint: Accurate results can be obtained by using the mesh size below 0.02.

Phase field profile

Fracture propagation animation

plotter = pv.Plotter()… (click to toggle) 
plotter = pv.Plotter()

plotter.open_gif("figures/surfing.gif")
pv.set_plot_theme("document")
for time_value in reader.time_values:
    reader.set_active_time_value(time_value)
    mesh = reader.read()[0]  # This dataset only has 1 block

    sargs = {
        "title": "Phase field",
        "title_font_size": 20,
        "label_font_size": 15,
        "n_labels": 5,
        "position_x": 0.3,
        "position_y": 0.2,
        "fmt": "%.1f",
        "width": 0.5,
    }
    clim = [0, 1.0]
    points = mesh.point_data["phasefield"].shape[0]
    xs = mesh.points[:, 0]
    ys = mesh.points[:, 1]
    pf = mesh.point_data["phasefield"]
    plotter.clear()
    plotter.add_mesh(
        mesh,
        scalars=pf,
        show_scalar_bar=False,
        colormap="coolwarm",
        clim=clim,
        scalar_bar_args=sargs,
        lighting=False,
    )
    plotter.add_text(f"Time: {time_value:.0f}", color="black")

    plotter.view_xy()
    plotter.write_frame()

plotter.close()

Phase field profile at last time step

mesh = reader.read()[0]… (click to toggle) 
mesh = reader.read()[0]

pv.set_jupyter_backend("static")
p = pv.Plotter(shape=(1, 1), border=False)
p.add_mesh(
    mesh,
    scalars=pf,
    show_edges=False,
    show_scalar_bar=True,
    colormap="coolwarm",
    clim=clim,
    scalar_bar_args=sargs,
)

p.view_xy()
p.camera.zoom(1.5)
p.window_size = [800, 400]
p.show()

png

References

[1] B. Bourdin, G.A. Francfort, and J.-J. Marigo, The variational approach to fracture, Journal of Elasticity 91 (2008), no. 1-3, 5–148.

[2] Li, Tianyi, Jean-Jacques Marigo, Daniel Guilbaud, and Serguei Potapov. Numerical investigation of dynamic brittle fracture via gradient damage models. Advanced Modeling and Simulation in Engineering Sciences 3, no. 1 (2016): 1-24.

[3] Dubois, Frédéric and Chazal, Claude and Petit, Christophe, A Finite Element Analysis of Creep-Crack Growth in Viscoelastic Media, Mechanics Time-Dependent Materials 2 (1998), no. 3, 269–286

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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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