examples.phase.missOrientation package¶
Submodules¶
examples.phase.missOrientation.circle module¶
In this example, a phase equation is solved in one dimension with a misorientation between two solid domains. The phase equation is given by:
where
The initial conditions are:
and boundary conditions
for
and
.
Here the phase equation is solved with an explicit technique.
The solution is allowed to evolve for steps = 100
time steps.
>>> from builtins import range
>>> for step in range(steps):
... phaseEq.solve(phase, dt = timeStepDuration)
The solution is compared with test data. The test data was created
with a FORTRAN code written by Ryo Kobayashi for phase field
modeling. The following code opens the file circle.gz
extracts the
data and compares it with the phase
variable.
>>> import os
>>> from future.utils import text_to_native_str
>>> testData = numerix.loadtxt(os.path.splitext(__file__)[0] + text_to_native_str('.gz'))
>>> print(phase.allclose(testData))
1
examples.phase.missOrientation.mesh1D module¶
In this example a phase equation is solved in 1 dimension with a misorientation present. The phase equation is given by:
where
The initial conditions are:
and boundary conditions
for
and
.
Here the phase equation is solved with an explicit technique.
The solution is allowed to evolve for steps = 100
time steps.
>>> from builtins import range
>>> for step in range(steps):
... phaseEq.solve(phase, dt = timeStepDuration)
The solution is compared with test data. The test data was created
with a FORTRAN code written by Ryo Kobayashi for phase field
modeling. The following code opens the file mesh1D.gz
extracts the
data and compares it with the theta
variable.
>>> import os
>>> from future.utils import text_to_native_str
>>> testData = numerix.loadtxt(os.path.splitext(__file__)[0] + text_to_native_str('.gz'))
>>> print(phase.allclose(testData))
1
examples.phase.missOrientation.modCircle module¶
In this example a phase equation is solved in one dimension with a misorientation present. The phase equation is given by:
where
The initial conditions are:
and boundary conditions
for
and
.
Here the phase equation is solved with an explicit technique.
The solution is allowed to evolve for steps = 100
time steps.
>>> from builtins import range
>>> for step in range(steps):
... phaseEq.solve(phase, dt = timeStepDuration)
The solution is compared with test data. The test data was created
with a FORTRAN code written by Ryo Kobayashi for phase field
modeling. The following code opens the file modCircle.gz
extracts the
data and compares it with the phase
variable.
>>> import os
>>> from future.utils import text_to_native_str
>>> testData = numerix.loadtxt(os.path.splitext(__file__)[0] + text_to_native_str('.gz'))
>>> print(phase.allclose(testData))
1