def strain_energy():
C_al3Mg = np.array([[0.64, 0.24, 0.24, 0, 0, 0],
[0.24, 0.64, 0.24, 0, 0, 0],
[0.24, 0.24, 0.64, 0, 0, 0],
[0, 0, 0, 0.65, 0, 0],
[0, 0, 0, 0, 0.65, 0],
[0, 0, 0, 0, 0, 0.65]])
C_al = np.array([[0.63, 0.41, 0.41, 0, 0, 0],
[0.41, 0.63, 0.41, 0, 0, 0],
[0.41, 0.41, 0.63, 0, 0, 0],
[0, 0, 0, 0.43, 0, 0],
[0, 0, 0, 0, 0.43, 0],
[0, 0, 0, 0, 0, 0.43]])
C_al = np.array([[0.62639459, 0.41086487, 0.41086487, 0, 0, 0],
[0.41086487, 0.62639459, 0.41086487, 0, 0, 0],
[0.41086487, 0.41086487, 0.62639459, 0, 0, 0],
[0, 0, 0, 0.42750351, 0, 0],
[0, 0, 0, 0, 0.42750351, 0],
[0, 0, 0, 0, 0, 0.42750351]])
eigenstrain = [0.023, 0.023, 0.023, 0.0, 0.0, 0.0]
mu_al = 0.34876
mu_al3mg = 0.20835377082353254
poisson = 0.5*(mu_al + mu_al3mg)
poisson = mu_al
strain_energy = StrainEnergy(eigenstrain=eigenstrain, poisson=poisson)
print(strain_energy.is_isotropic(C_al))
energy = strain_energy.strain_energy(C_matrix=C_al, C_prec=C_al3Mg)
v_per_atom = 16.60753125
print(energy*1000.0*v_per_atom)
print(energy*1000.0)
def plot(self,
princ_misfit=[0.1, 0.1, 0.1],
theta=0.0,
phi=0.0,
show=True):
from matplotlib import pyplot as plt
from cemc.tools import rot_matrix_spherical_coordinates
from cemc.tools import rotate_tensor
scale_factors = np.logspace(-3, 3, 100)
# Sphere
aspects = {
"Sphere": [1.0, 1.0, 1.0],
"Needle": [10000.0, 1.0, 1.0],
"Plate": [10000.0, 10000.0, 1.0]
}
fig = plt.figure()
ax1 = fig.add_subplot(1, 1, 1)
colors = ["#5D5C61", "#7395AE", "#B1A296"]
color_count = 0
for k, v in aspects.items():
strain_tensor = np.diag(princ_misfit)
rot_matrix = rot_matrix_spherical_coordinates(phi, theta)
strain_tensor = rotate_tensor(strain_tensor, rot_matrix)
strain = StrainEnergy(aspect=v,
misfit=strain_tensor,
poisson=self.poisson)
energy = [
strain.strain_energy(C_matrix=self.tensor, scale_factor=f)
for f in scale_factors
]
ax1.plot(scale_factors,
energy,
label=k,
color=colors[color_count % 3])
color_count += 1
ax1.set_xscale("log")
ax1.set_yscale("log")
ax1.spines["right"].set_visible(False)
ax1.spines["top"].set_visible(False)
ax1.set_xlabel("Scale factor")
ax1.set_ylabel("Strain energy")
ax1.legend(frameon=False)
if show:
plt.show()
def __call__(self, system_changes):
self.cov_obs(system_changes)
inertia_tensor = np.trace(
self.cov_obs.cov_matrix) * np.eye(3) - self.cov_obs.cov_matrix
principal, rot_matrix = np.linalg.eigh(inertia_tensor)
# The rotation to be applied to the material properties
# and the misfit, is the transpose of the eigenvector
# matrix
C_mat = rotate_rank4_mandel(self.C_matrix, rot_matrix.T)
C_prec = rotate_rank4_mandel(self.C_prec, rot_matrix.T)
misfit = rotate_tensor(self.misfit, rot_matrix.T)
axes = self.ellipsoid_axes(principal)
str_eng = StrainEnergy(aspect=axes,
misfit=misfit,
poisson=self.poisson)
str_energy = str_eng.strain_energy(C_matrix=C_mat, C_prec=C_prec)
# Bias potential should not alter the observer
# The MC object will handle this
self.cov_obs.undo_last()
return str_energy * ellipsoid_volume(axes)
def optimal_orientation(self,
princ_misfit=[0.1, 0.1, 0.1],
aspect=[1.0, 1.0, 1.0],
scale=1.0,
show_map=True):
"""Find the optimial orientation of the ellipsoid."""
from itertools import product
from cemc.tools import rot_matrix_spherical_coordinates
from cemc.tools import rotate_tensor
from scipy.interpolate import griddata
from matplotlib import pyplot as plt
# Quick exploration of the space
theta = np.linspace(0.0, np.pi / 2.0, 100)
phi = np.linspace(0.0, np.pi / 2.0, 100)
energy = []
all_theta = []
all_phi = []
for ang in product(phi, theta):
strain_tensor = np.diag(princ_misfit)
rot_matrix = rot_matrix_spherical_coordinates(ang[0], ang[1])
strain_tensor = rotate_tensor(strain_tensor, rot_matrix)
strain = StrainEnergy(aspect=aspect,
misfit=strain_tensor,
poisson=self.poisson)
new_energy = strain.strain_energy(C_matrix=self.tensor,
scale_factor=scale)
energy.append(new_energy)
all_theta.append(ang[1])
all_phi.append(ang[0])
# Locate the minimal energy
min_indx = np.argmin(energy)
theta_min = all_theta[min_indx]
phi_min = all_phi[min_indx]
if theta_min > np.pi / 2.0:
theta_min = np.pi - theta_min
print("Min. energy: {}. Theta: {} Phi. {}"
"".format(energy[min_indx], int(theta_min * 180 / np.pi),
int(phi_min * 180 / np.pi)))
print("Poisson ratio: {}".format(self.poisson))
T, P = np.meshgrid(theta, phi)
data = griddata(np.vstack((all_theta, all_phi)).T, energy, (T, P))
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
im = ax.imshow(data.T,
origin="lower",
aspect="auto",
cmap="inferno",
extent=[0, 90, 0, 90])
cbar = fig.colorbar(im)
cbar.set_label("Strain energy")
ax.set_xlabel("Polar angle (deg)")
ax.set_ylabel("Azimuthal angle (deg)")
if show_map:
plt.show()