def complete(self):
self.E = 92000.0
self.nu = 0.3
self.s0 = 180.0
self.Kp = 1000.0
self.H = 1000.0
self.elastic = elasticity.IsotropicLinearElasticModel(self.E, "youngs",
self.nu, "poissons")
surface = surfaces.IsoKinJ2()
iso = hardening.LinearIsotropicHardeningRule(self.s0, self.Kp)
kin = hardening.LinearKinematicHardeningRule(self.H)
hrule = hardening.CombinedHardeningRule(iso, kin)
flow = ri_flow.RateIndependentAssociativeFlow(surface, hrule)
self.bmodel = models.SmallStrainRateIndependentPlasticity(self.elastic,
flow)
self.xi = 0.478
self.phi = 1.914
self.A = 10000000.0
self.model = damage.ModularCreepDamageModel_sd(
self.elastic,
self.A, self.xi, self.phi,
self.effective_model(),
self.bmodel)
self.stress = np.array([100,-50.0,300.0,-99,50.0,125.0])
self.T = 100.0
self.s_np1 = self.stress
self.s_n = np.array([-25,150,250,-25,-100,25])
self.d_np1 = 0.5
self.d_n = 0.4
self.e_np1 = np.array([0.1,-0.01,0.15,-0.05,-0.1,0.15])
self.e_n = np.array([-0.05,0.025,-0.1,0.2,0.11,0.13])
self.T_np1 = self.T
self.T_n = 90.0
self.t_np1 = 1.0
self.t_n = 0.0
self.u_n = 0.0
self.p_n = 0.0
# This is a rather boring baseline history state to probe, but I can't
# think of a better way to get a "generic" history from a generic model
self.hist_n = np.array([self.d_n] + list(self.bmodel.init_store()))
self.x_trial = np.array([50,-25,150,-150,190,100.0] + [0.41])
self.nsteps = 10
self.etarget = np.array([0.1,-0.025,0.02,0.015,-0.02,-0.05])
self.ttarget = 10.0
def setUp(self):
self.E = 92000.0
self.nu = 0.3
self.s0 = 180.0
self.Kp = 1000.0
self.H = 1000.0
self.elastic = elasticity.IsotropicLinearElasticModel(self.E, "youngs",
self.nu, "poissons")
surface = surfaces.IsoKinJ2()
iso = hardening.LinearIsotropicHardeningRule(self.s0, self.Kp)
kin = hardening.LinearKinematicHardeningRule(self.H)
hrule = hardening.CombinedHardeningRule(iso, kin)
flow = ri_flow.RateIndependentAssociativeFlow(surface, hrule)
self.bmodel = models.SmallStrainRateIndependentPlasticity(self.elastic,
flow)
self.fn = interpolate.PolynomialInterpolate([-6.653e-9,2.952e-4,-6.197e-1])
self.C = 32.06
self.lmr = larsonmiller.LarsonMillerRelation(self.fn, self.C)
self.effective = damage.VonMisesEffectiveStress()
self.model = damage.LarsonMillerCreepDamageModel_sd(
self.elastic, self.lmr, self.effective, self.bmodel)
self.stress = np.array([100,-50.0,300.0,-99,50.0,125.0])
self.T = 100.0
self.s_np1 = self.stress
self.s_n = np.array([-25,150,250,-25,-100,25])
self.d_np1 = 0.5
self.d_n = 0.4
self.e_np1 = np.array([0.1,-0.01,0.15,-0.05,-0.1,0.15])
self.e_n = np.array([-0.05,0.025,-0.1,0.2,0.11,0.13])
self.T_np1 = self.T
self.T_n = 90.0
self.t_np1 = 1.0
self.t_n = 0.0
self.dt = self.t_np1 - self.t_n
self.u_n = 0.0
self.p_n = 0.0
# This is a rather boring baseline history state to probe, but I can't
# think of a better way to get a "generic" history from a generic model
self.hist_n = np.array([self.d_n] + list(self.bmodel.init_store()))
self.x_trial = np.array([50,-25,150,-150,190,100.0] + [0.41])
self.nsteps = 10
self.etarget = np.array([0.1,-0.025,0.02,0.015,-0.02,-0.05])
self.ttarget = 10.0
def setUp(self):
self.model1 = parse.parse_xml("test/examples.xml", "test_perzyna")
mu = 40000.0
K = 84000.0
elastic = elasticity.IsotropicLinearElasticModel(
mu, "shear", K, "bulk")
sy = 100.0
r = 100.0
d = 1000.0
KK = 1000.0
n = 5.0
eta = 500.0
surface = surfaces.IsoKinJ2()
iso = hardening.VoceIsotropicHardeningRule(sy, r, d)
kin = hardening.LinearKinematicHardeningRule(KK)
hmodel = hardening.CombinedHardeningRule(iso, kin)
gmodel = visco_flow.GPowerLaw(n, eta)
vmodel = visco_flow.PerzynaFlowRule(surface, hmodel, gmodel)
flow = general_flow.TVPFlowRule(elastic, vmodel)
self.model2 = models.GeneralIntegrator(elastic, flow)
self.T = 550.0 + 273.15
self.tmax = 10.0
self.nsteps = 100.0
self.emax = np.array([0.1, 0, 0, 0, 0, 0])
def setUp(self):
self.hist0 = np.zeros((13, ))
self.E = 92000.0
self.nu = 0.3
self.mu = self.E / (2 * (1 + self.nu))
self.K = self.E / (3 * (1 - 2 * self.nu))
self.s0 = 180.0
self.Kp = 1000.0
self.H = 1000.0
self.elastic = elasticity.IsotropicLinearElasticModel(
self.mu, "shear", self.K, "bulk")
surface = surfaces.IsoKinJ2()
iso = hardening.LinearIsotropicHardeningRule(self.s0, self.Kp)
kin = hardening.LinearKinematicHardeningRule(self.H)
hrule = hardening.CombinedHardeningRule(iso, kin)
flow = ri_flow.RateIndependentAssociativeFlow(surface, hrule)
self.model = models.SmallStrainRateIndependentPlasticity(
self.elastic, flow, check_kt=False)
self.efinal = np.array([0.1, -0.05, 0.02, -0.03, 0.1, -0.15])
self.tfinal = 10.0
self.T = 300.0
self.nsteps = 10
def setUp(self):
self.model1 = parse.parse_xml("test/examples.xml", "test_j2comb")
mu = 40000.0
K = 84000.0
ys = 100.0
r = 100.0
d = 1000.0
KH = 1000.0
elastic = elasticity.IsotropicLinearElasticModel(
mu, "shear", K, "bulk")
surface = surfaces.IsoKinJ2()
iso = hardening.VoceIsotropicHardeningRule(ys, r, d)
kin = hardening.LinearKinematicHardeningRule(KH)
hrule = hardening.CombinedHardeningRule(iso, kin)
flow = ri_flow.RateIndependentAssociativeFlow(surface, hrule)
self.model2 = models.SmallStrainRateIndependentPlasticity(
elastic, flow)
self.T = 300.0
self.tmax = 10.0
self.nsteps = 100.0
self.emax = np.array([0.1, 0, 0, 0, 0, 0])
def simple_ex():
E = 92000.0
nu = 0.3
s0 = 180.0
Kp = 1000.0
H = 1000.0
elastic = elasticity.IsotropicLinearElasticModel(E, "youngs", nu,
"poissons")
surface = surfaces.IsoKinJ2()
iso = hardening.LinearIsotropicHardeningRule(s0, Kp)
kin = hardening.LinearKinematicHardeningRule(H)
hrule = hardening.CombinedHardeningRule(iso, kin)
flow = ri_flow.RateIndependentAssociativeFlow(surface, hrule)
bmodel = models.SmallStrainRateIndependentPlasticity(elastic, flow)
A = 0.0e-6
a = 2.2
model_off = damage.NEMLPowerLawDamagedModel_sd(elastic, A, a, bmodel)
A = 2e-5
model_on = damage.NEMLPowerLawDamagedModel_sd(elastic, A, a, bmodel)
res_off = drivers.uniaxial_test(model_off, 1.0e-2, emax=0.13)
res_on = drivers.uniaxial_test(model_on, 1.0e-2, emax=0.13)
plt.plot(res_off['strain'], res_off['stress'], 'k-')
plt.plot(res_on['strain'], res_on['stress'], 'r-')
plt.show()
def setUp(self):
self.H = 1000.0
self.hist0 = np.zeros((6,))
self.hist_trial = np.array([50.0,25.0,75.0,10.0,15.0,50.0])
self.hist_trial = self.hist_trial - np.array([1,1,1,0,0,0]) * sum(self.hist_trial[:3]) / 3.0
self.T = 300.0
self.model = hardening.LinearKinematicHardeningRule(self.H)
def unload_ex():
E = 92000.0
nu = 0.3
s0 = 180.0
Kp = 1000.0
H = 1000.0
elastic = elasticity.IsotropicLinearElasticModel(E, "youngs", nu,
"poissons")
surface = surfaces.IsoKinJ2()
iso = hardening.LinearIsotropicHardeningRule(s0, Kp)
kin = hardening.LinearKinematicHardeningRule(H)
hrule = hardening.CombinedHardeningRule(iso, kin)
flow = ri_flow.RateIndependentAssociativeFlow(surface, hrule)
bmodel = models.SmallStrainRateIndependentPlasticity(elastic, flow)
A = 2e-5
a = 2.2
model = damage.NEMLPowerLawDamagedModel_sd(elastic, A, a, bmodel)
driver = drivers.Driver_sd(model)
nsteps = 25
sdir = np.array([1, 0, 0, 0, 0, 0])
erate = 1.0e-5
e_inc = 0.1 / nsteps
for i in range(nsteps):
einc, ainc = driver.erate_einc_step(sdir, erate, e_inc, 0.0)
estrain = model.elastic_strains(driver.stress_int[-1], driver.T_int[-1],
driver.stored[-1])
print("Calculated elastic strain: %f" % estrain[0])
nsteps = 20
dt = 0.1
rstress = driver.stress_int[-1]
rstrain = driver.strain_int[-1][0]
for m in np.linspace(0, 1.0, nsteps, endpoint=False)[::-1]:
driver.stress_step(rstress * m, driver.t_int[-1] + dt,
driver.T_int[-1])
fstrain = driver.strain_int[-1][0]
print("Actual elastic strain: %f" % (rstrain - fstrain))
print("Calculated final elastic strain: %f" % model.elastic_strains(
driver.stress_int[-1], driver.T_int[-1], driver.stored[-1])[0])
plt.plot(driver.strain[:, 0], driver.stress[:, 0])
plt.show()
def test_ri_plasticity(self):
surface = surfaces.IsoJ2()
sy = 100.0
K = 1000.0
H = 500.0
hrule = hardening.CombinedHardeningRule(
hardening.LinearIsotropicHardeningRule(sy, K),
hardening.LinearKinematicHardeningRule(H))
flow = ri_flow.RateIndependentAssociativeFlow(surface, hrule)
model = models.SmallStrainRateIndependentPlasticity(
self.elastic1, flow)
self.are_equal(self.elastic1, model.elastic)
model.set_elastic_model(self.elastic2)
self.are_equal(self.elastic2, model.elastic)
def setUp(self):
self.s0 = 200.0
self.K = 1000.0
self.H = 1000.0
self.hist0 = np.zeros((7, ))
self.hist_trial = np.array([50.0, 75.0, 100.0, 25.0, 10.0, 15.0, 60.0])
self.hist_trial[1:] = make_dev(self.hist_trial[1:])
self.T = 300.0
self.iso = hardening.LinearIsotropicHardeningRule(self.s0, self.K)
self.kin = hardening.LinearKinematicHardeningRule(self.H)
self.model = hardening.CombinedHardeningRule(self.iso, self.kin)
def creep_ex():
E = 92000.0
nu = 0.3
s0 = 120.0
A = 1.0e-10
n = 3.0
Kp = E / 500
H = E / 500
smodel = creep.PowerLawCreep(A, n)
cmodel = creep.J2CreepModel(smodel)
elastic = elasticity.IsotropicLinearElasticModel(E, "youngs", nu,
"poissons")
surface = surfaces.IsoKinJ2()
iso = hardening.LinearIsotropicHardeningRule(s0, Kp)
kin = hardening.LinearKinematicHardeningRule(H)
hrule = hardening.CombinedHardeningRule(iso, kin)
flow = ri_flow.RateIndependentAssociativeFlow(surface, hrule)
pmodel = models.SmallStrainRateIndependentPlasticity(elastic, flow)
bmodel = models.SmallStrainCreepPlasticity(elastic, pmodel, cmodel)
A_damg = 1.0e-2
a_damg = 1.0
model = damage.NEMLPowerLawDamagedModel_sd(elastic,
A_damg,
a_damg,
bmodel,
verbose=False)
#res = drivers.uniaxial_test(model, 1.0e-2, emax = 0.25)
#plt.plot(res['strain'], res['stress'])
#plt.show()
res = drivers.creep(model, 120.0, 1.0, 393.0, verbose=False)
plt.plot(res['rtime'], res['rstrain'])
plt.show()
plt.loglog(res['rtime'], res['rrate'])
plt.show()
def test_damage(self):
s0 = 180.0
Kp = 1000.0
H = 1000.0
surface = surfaces.IsoKinJ2()
iso = hardening.LinearIsotropicHardeningRule(s0, Kp)
kin = hardening.LinearKinematicHardeningRule(H)
hrule = hardening.CombinedHardeningRule(iso, kin)
flow = ri_flow.RateIndependentAssociativeFlow(surface, hrule)
bmodel = models.SmallStrainRateIndependentPlasticity(
self.elastic1, flow)
W0 = 10.0
k0 = 0.0001
a0 = 2.0
model1 = damage.NEMLExponentialWorkDamagedModel_sd(
self.elastic1, W0, k0, a0, bmodel)
W02 = 10.0
k02 = 0.001
a02 = 1.5
model2 = damage.NEMLExponentialWorkDamagedModel_sd(
self.elastic1, W02, k02, a02, bmodel)
model = damage.CombinedDamageModel_sd(self.elastic1, [model1, model2],
bmodel)
self.very_close(model, self.emodel1)
model.set_elastic_model(self.elastic2)
self.very_close(model, self.emodel2)
def setUp(self):
self.E = 92000.0
self.nu = 0.3
self.s0 = 180.0
self.Kp = 1000.0
self.H = 1000.0
self.elastic = elasticity.IsotropicLinearElasticModel(self.E, "youngs",
self.nu, "poissons")
surface = surfaces.IsoKinJ2()
iso = hardening.LinearIsotropicHardeningRule(self.s0, self.Kp)
kin = hardening.LinearKinematicHardeningRule(self.H)
hrule = hardening.CombinedHardeningRule(iso, kin)
flow = ri_flow.RateIndependentAssociativeFlow(surface, hrule)
self.bmodel = models.SmallStrainRateIndependentPlasticity(self.elastic,
flow)
self.fn = interpolate.PolynomialInterpolate([0.1,5.0, 1e-8])
self.n = 2.1
self.model = damage.NEMLWorkDamagedModel_sd(
self.elastic, self.fn, self.n, self.bmodel, verbose = False)
self.stress = np.array([100,-50.0,300.0,-99,50.0,125.0]) * 0.75
self.T = 100.0
self.s_np1 = self.stress
self.s_n = np.array([-25,150,250,-25,-100,25]) * 0.0
self.d_np1 = 0.2
self.d_n = 0.1
self.e_np1 = np.array([0.1,-0.01,0.15,-0.05,-0.1,0.15]) * 0.75
self.e_n = np.array([-0.05,0.025,-0.1,0.2,0.11,0.13]) * 0.0
self.T_np1 = self.T
self.T_n = 90.0
self.t_np1 = 5000.0
self.t_n = 0.9
self.u_n = 0.0
self.p_n = 0.0
# This is a rather boring baseline history state to probe, but I can't
# think of a better way to get a "generic" history from a generic model
self.hist_n = np.array([self.d_n] + list(self.bmodel.init_store()))
self.x_trial = np.array([50,-25,150,-150,190,100.0] + [0.41])
self.nsteps = 10
self.etarget = np.array([0.1,-0.025,0.02,0.015,-0.02,-0.05])
self.ttarget = 2.0
self.ee = np.dot(self.elastic.S(self.T_np1), self.s_np1*(1.0-self.d_np1) - self.s_n*(1.0-self.d_n))
self.de = self.e_np1 - self.e_n
self.dp = self.de - self.ee
self.dt = self.t_np1 - self.t_n
self.Wdot = np.dot(self.s_np1*(1.0-self.d_np1), self.dp) / self.dt
