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fragmentation.py
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Sat, Aug 17, 03:18
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text/x-python
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rAKA akantu
fragmentation.py
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#!/usr/bin/env python
# coding: utf-8
# import akantu
import
subprocess
import
akantu
as
aka
# import numpy for vector manipulation
import
numpy
as
np
import
matplotlib.pyplot
as
plt
# ### Setting up the *SolidMechanicsModelCohesive*
# We need to read again the material file and the mesh
# Create the Solid Mechanics Cohesive Model in Akantu
# reading material file
aka
.
parseInput
(
'material.dat'
)
# creating mesh
spatial_dimension
=
2
mesh
=
aka
.
Mesh
(
spatial_dimension
)
# geometry (as defined in geo file)
L
=
10
length
=
L
/
100
mesh
.
read
(
'fragmentation_mesh.msh'
)
# creates the model
model
=
aka
.
SolidMechanicsModelCohesive
(
mesh
)
model
.
initFull
(
_analysis_method
=
aka
.
_static
,
_is_extrinsic
=
True
)
# Initialize the solver
# configures the static solver
solver
=
model
.
getNonLinearSolver
(
'static'
)
solver
.
set
(
'max_iterations'
,
100
)
solver
.
set
(
'threshold'
,
1e-10
)
solver
.
set
(
"convergence_type"
,
aka
.
SolveConvergenceCriteria
.
residual
)
# Initilize a new solver (explicit Newmark with lumped mass)
model
.
initNewSolver
(
aka
.
_explicit_lumped_mass
)
# Dynamic insertion of cohesive elements
model
.
updateAutomaticInsertion
()
# Implement Boundary and initial conditions
# Dirichlet Boundary condition
# model.applyBC(aka.FixedValue(0., aka._x), 'left')
model
.
applyBC
(
aka
.
FixedValue
(
0.
,
aka
.
_y
),
'bottom'
)
model
.
getExternalForce
()[:]
=
0
# ### Generate paraview files
# Initialization for bulk vizualisation
model
.
setBaseName
(
'plate'
)
model
.
addDumpFieldVector
(
'displacement'
)
model
.
addDumpFieldVector
(
'velocity'
)
model
.
addDumpFieldVector
(
'external_force'
)
model
.
addDumpField
(
'strain'
)
model
.
addDumpField
(
'stress'
)
model
.
addDumpField
(
'blocked_dofs'
)
# Initialization of vizualisation for Cohesive model
model
.
setBaseNameToDumper
(
'cohesive elements'
,
'cohesive'
)
model
.
addDumpFieldVectorToDumper
(
'cohesive elements'
,
'displacement'
)
model
.
addDumpFieldToDumper
(
'cohesive elements'
,
'damage'
)
model
.
addDumpFieldVectorToDumper
(
'cohesive elements'
,
'tractions'
)
model
.
addDumpFieldVectorToDumper
(
'cohesive elements'
,
'opening'
)
# Custom Dirichlet Boundary Condition to impose constant velocity
# Boundary functor fixing the displacement as it is
class
FixedDisplacement
(
aka
.
DirichletFunctor
):
'''
Fix the displacement at its current value
'''
def
__init__
(
self
,
axis
,
vel
):
super
()
.
__init__
(
axis
)
self
.
axis
=
axis
self
.
time
=
0
self
.
vel
=
vel
def
set_time
(
self
,
t
):
self
.
time
=
t
def
__call__
(
self
,
node
,
flags
,
disp
,
coord
):
# sets the blocked dofs vector to true in the desired axis
flags
[
int
(
self
.
axis
)]
=
True
disp
[
int
(
self
.
axis
)]
=
self
.
vel
*
self
.
time
functor_r
=
FixedDisplacement
(
aka
.
_x
,
1e-1
)
model
.
applyBC
(
functor_r
,
'right'
)
functor_l
=
FixedDisplacement
(
aka
.
_x
,
-
1e-1
)
model
.
applyBC
(
functor_l
,
'left'
)
# Initial condition : velocity gradient:
# in x = 0 we have -v and in x = L we have +v
nodes
=
model
.
getMesh
()
.
getNodes
()
vel_field
=
np
.
zeros
(
nodes
.
shape
)
vel_field
[:,
0
]
=
(
2
*
nodes
[:,
0
]
-
L
)
/
L
*
1e-1
model
.
getVelocity
()[:]
=
vel_field
# ### Run the dynamical simulation
# Initialize data arrays
# Energies :
E_pot
=
[]
E_kin
=
[]
E_dis
=
[]
E_rev
=
[]
E_con
=
[]
# Stress :
Stress
=
[]
dt
=
model
.
getStableTimeStep
()
*
0.1
# choose the timestep
model
.
setTimeStep
(
dt
)
# set maximum number of iteration
maxsteps
=
5000
# solve
for
i
in
range
(
0
,
maxsteps
):
time
=
dt
*
i
functor_r
.
set_time
(
time
)
# fix displacements of the right boundary
model
.
applyBC
(
functor_r
,
'right'
)
functor_l
.
set_time
(
time
)
# fix displacements of the left boundary
model
.
applyBC
(
functor_l
,
'left'
)
if
i
%
10
==
0
:
model
.
dump
()
model
.
dump
(
'cohesive elements'
)
pass
if
i
%
50
==
0
:
print
(
'step {0}/{1}'
.
format
(
i
,
maxsteps
))
model
.
checkCohesiveStress
()
model
.
solveStep
(
'explicit_lumped'
)
Ep
=
model
.
getEnergy
(
"potential"
)
Ek
=
model
.
getEnergy
(
"kinetic"
)
Ed
=
model
.
getEnergy
(
"dissipated"
)
Er
=
model
.
getEnergy
(
"reversible"
)
Ec
=
model
.
getEnergy
(
"contact"
)
E_pot
.
append
(
Ep
)
E_kin
.
append
(
Ek
)
E_dis
.
append
(
Ed
)
E_rev
.
append
(
Er
)
E_con
.
append
(
Ec
)
Stress_field
=
model
.
getMaterial
(
0
)
.
getStress
(
aka
.
_triangle_3
)
Stress_mean
=
np
.
mean
(
Stress_field
)
Stress
.
append
(
Stress_mean
)
# Use the fragment Manager
fragment_manager
=
aka
.
FragmentManager
(
model
)
fragment_manager
.
computeAllData
()
Nb_elem_per_frag
=
fragment_manager
.
getNbElementsPerFragment
()
Nb_frag
=
fragment_manager
.
getNbFragment
()
print
(
'Nb_frag:'
,
Nb_frag
)
# Average number of elements per fragment
Nb_elem_mean
=
np
.
mean
(
Nb_elem_per_frag
)
print
(
'average Nb elem / fragment:'
,
Nb_elem_mean
)
# knowing the element size we can get the average fragment size
s_mean
=
Nb_elem_mean
*
length
print
(
'average fragment size:'
,
s_mean
)
# ## Plots
# Plot stress as a function of time
Time
=
[
i
*
dt
for
i
in
range
(
0
,
maxsteps
)]
Stress_MPa
=
[
x
/
10
**
6
for
x
in
Stress
]
plt
.
figure
()
plt
.
plot
(
Time
,
Stress
)
plt
.
xlabel
(
"Time [s]"
)
plt
.
ylabel
(
"Stress [Pa]"
)
plt
.
show
()
# Plot the energies as a function of time
plt
.
figure
()
plt
.
plot
(
Time
,
E_pot
,
label
=
'Potential Energy'
)
plt
.
plot
(
Time
,
E_kin
,
label
=
'Kinetic Energy'
)
plt
.
plot
(
Time
,
E_dis
,
label
=
'Dissipated Energy'
)
plt
.
plot
(
Time
,
E_rev
,
label
=
'Reversible Energy'
)
plt
.
plot
(
Time
,
E_con
,
label
=
'Contact Energy'
)
plt
.
legend
()
print
(
'uncomment if you want to see the graphs'
)
# plt.show()
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