def test_pass(self):
# path to the test library
lib = os.environ['MGIS_TEST_BEHAVIOURS_LIBRARY']
# reference values
pref = [
0, 1.3523277308229e-11, 1.0955374667213e-07, 5.5890770166084e-06,
3.2392193670428e-05, 6.645865307584e-05, 9.9676622883138e-05,
0.00013302758358953, 0.00016635821069889, 0.00019969195920296,
0.00023302522883648, 0.00026635857194317, 0.000299691903777,
0.0003330252373404, 0.00036635857063843, 0.00039969190397718,
0.00043302523730968, 0.00046635857064314, 0.00049969190397646,
0.00053302523730979, 0.00056635857064313
]
# comparison criterion
eps = 1.e-12
b = mgis_bv.load(lib, 'Norton', mgis_bv.Hypothesis.Tridimensional)
d = mgis_bv.BehaviourData(b)
o = mgis_bv.getVariableOffset(b.isvs, 'EquivalentViscoplasticStrain',
b.hypothesis)
# strain increment per time step
de = 5.e-5
# time step
d.dt = 180
# setting the temperature
mgis_bv.setExternalStateVariable(d.s1, 'Temperature', 293.15)
# copy d.s1 in d.s0
mgis_bv.update(d)
d.s1.gradients[0] = de
# equivalent plastic strain
p = [d.s0.internal_state_variables[o]]
# integrate the behaviour
for i in range(0, 20):
mgis_bv.integrate(d, b)
mgis_bv.update(d)
d.s1.gradients[0] += de
p.append(d.s1.internal_state_variables[o])
# check-in results
for i in range(0, 20):
self.assertTrue(abs(p[i] - pref[i]) < eps)
pass
def test_pass(self):
# path to the test library
lib = os.environ['MGIS_TEST_MODELS_LIBRARY']
# modelling hypothesis
h = mgis_bv.Hypothesis.Tridimensional
# loading the behaviour
model = mgis.model.load(lib, 'ode_rk54', h)
# default value of parameter A
A = model.getParameterDefaultValue('A')
# material data manager
d = mgis_bv.BehaviourData(model)
# index of x in the array of state variable
o = mgis_bv.getVariableOffset(model.isvs, 'x', h)
# time step increment
d.dt = 0.1
# type of storage
mgis_bv.setExternalStateVariable(d.s1, 'Temperature', 293.15)
# Initial value of x
d.s1.internal_state_variables[o] = 1
# copy d.s1 in d.s0
mgis_bv.update(d)
# values of x
xvalues = [d.s0.internal_state_variables[o]]
# integration
for i in range(0, 10):
mgis_bv.integrate(d, model)
mgis_bv.update(d)
xvalues.append(d.s1.internal_state_variables[o])
# checks
# comparison criterion
eps = 1.e-10
t = 0
for i in range(0, 11):
x_ref = math.exp(-A * t)
self.assertTrue(abs(xvalues[i] - x_ref) < eps)
t = t + d.dt
pass
def test_pass(self):
print(dir(mgis))
# path to the test library
lib = os.environ['MGIS_TEST_BEHAVIOURS_LIBRARY']
# reference values
pref = [
0, 1.3523277308229e-11, 1.0955374667213e-07, 5.5890770166084e-06,
3.2392193670428e-05, 6.645865307584e-05, 9.9676622883138e-05,
0.00013302758358953, 0.00016635821069889, 0.00019969195920296,
0.00023302522883648, 0.00026635857194317, 0.000299691903777,
0.0003330252373404, 0.00036635857063843, 0.00039969190397718,
0.00043302523730968, 0.00046635857064314, 0.00049969190397646,
0.00053302523730979, 0.00056635857064313
]
# modelling hypothesis
h = mgis_bv.Hypothesis.Tridimensional
# loading the behaviour
b = mgis_bv.load(lib, 'Norton', h)
# number of integration points
nig = 100
# material data manager
m = mgis_bv.MaterialDataManager(b, nig)
# index of the equivalent viscplastic strain in the array of
# state variable
o = mgis_bv.getVariableOffset(b.isvs, 'EquivalentViscoplasticStrain',
h)
# strain increment per time step
de = 5.e-5
# time step increment
dt = 180
# setting the temperature
mgis_bv.setExternalStateVariable(m.s1, 'Temperature', 293.15)
# copy d.s1 in d.s0
mgis_bv.update(m)
# index of the first integration point
ni = 0
# index of the last integration point
ne = nig - 1
# values of the equivalent plastic strain
# for the first integration point
pi = [m.s0.internal_state_variables[ni][o]]
# values of the equivalent plastic strain
# for the last integration point
pe = [m.s0.internal_state_variables[ne][o]]
# setting the gradient at the end of the first time step
for i in range(0, nig):
m.s1.gradients[i][0] = de
# creating a thread pool for parallel integration
p = mgis.ThreadPool(2)
# integration
for i in range(0, 20):
it = mgis_bv.IntegrationType.IntegrationWithoutTangentOperator
mgis_bv.integrate(p, m, it, dt)
mgis_bv.update(m)
for j in range(0, nig):
m.s1.gradients[j][0] += de
pi.append(m.s0.internal_state_variables[ni][o])
pe.append(m.s0.internal_state_variables[ne][o])
# checks
# comparison criterion
eps = 1.e-12
for i in range(0, 21):
self.assertTrue(abs(pi[i] - pref[i]) < eps)
self.assertTrue(abs(pe[i] - pref[i]) < eps)
pass
