[hardening.ConstantGamma(0.0)], [0.0],
[1.0])
surface_m = surfaces.IsoKinJ2()
visco_flow_m = visco_flow.ChabocheFlowRule(surface_m, hmodel_rd, eta_m,
n_interp)
rd_flow = general_flow.TVPFlowRule(elastic_m, visco_flow_m)
rd_model = models.GeneralIntegrator(elastic_m, rd_flow)
ri_flow_m = ri_flow.RateIndependentNonAssociativeHardening(
surface_m, hmodel_ri)
ri_model = models.SmallStrainRateIndependentPlasticity(
elastic_m, ri_flow_m)
model = models.KMRegimeModel(elastic_m, [ri_model, rd_model], [g0], kboltz,
b, eps0)
smax = 400.0
Rs = [-1.0, -0.75, -0.5, -0.25, 0.0]
srate = 1.0e-3
ncycles = 50
for R in Rs:
res = drivers.stress_cyclic(model,
smax,
R,
srate,
ncycles,
T=550 + 273.15)
plt.plot(res['cycles'], res['max'])
#plt.plot(res['strain'], res['stress'])
#plt.show()
def setUp(self):
# Fully-defined perfectly plastic model
Epoly = [-78.2759, 236951.0]
nu = 0.3
A = -9.6187
B = -1.4819
C = -5.0486
g0 = 0.3708
b = 0.248 * 1.0e-6
kboltz = 1.38064e-23 * 1000.0
eps0 = 1.0e10
# Temperature range over which to consider (K)
Tmin = 550.0
Tmax = 950.0
Trange = np.linspace(Tmin, Tmax)
# Elastic
E_m = interpolate.PolynomialInterpolate(Epoly)
nu_m = interpolate.ConstantInterpolate(nu)
elastic_m = elasticity.IsotropicLinearElasticModel(
E_m, "youngs", nu_m, "poissons")
self.elastic = elastic_m
# Rate sensitivity interpolates values
mu_values = np.array([elastic_m.G(T) for T in Trange])
n_values = -mu_values * b**3.0 / (kboltz * Trange * A)
eta_values = np.exp(B) * eps0**(kboltz * Trange * A /
(mu_values * b**3.0)) * mu_values
# Rate independent interpolate values
flow_stress = mu_values * np.exp(C)
# Common objects
surface = surfaces.IsoKinJ2()
hmodulus = interpolate.PolynomialInterpolate([-10.0, 12000.0])
# Setup visco model
n_interp = interpolate.PiecewiseLinearInterpolate(
list(Trange), list(n_values))
eta_interp = interpolate.PiecewiseLinearInterpolate(
list(Trange), list(eta_values))
eta_m = visco_flow.ConstantFluidity(eta_interp)
iso_rd = hardening.LinearIsotropicHardeningRule(
interpolate.ConstantInterpolate(0.0), hmodulus)
hard_rd = hardening.Chaboche(
iso_rd, [interpolate.ConstantInterpolate(0.0)],
[hardening.ConstantGamma(interpolate.ConstantInterpolate(0.0))],
[interpolate.ConstantInterpolate(0.0)],
[interpolate.ConstantInterpolate(1.0)])
visco_rd = visco_flow.ChabocheFlowRule(surface, hard_rd, eta_m,
n_interp)
general_rd = general_flow.TVPFlowRule(elastic_m, visco_rd)
rate_dependent = models.GeneralIntegrator(elastic_m, general_rd)
# Setup rate independent
sy_interp = interpolate.PiecewiseLinearInterpolate(
list(Trange), list(flow_stress))
iso_ri = hardening.LinearIsotropicHardeningRule(sy_interp, hmodulus)
hard_ri = hardening.Chaboche(
iso_ri, [interpolate.ConstantInterpolate(0.0)],
[hardening.ConstantGamma(interpolate.ConstantInterpolate(0.0))],
[interpolate.ConstantInterpolate(0.0)],
[interpolate.ConstantInterpolate(1.0)])
flow_ri = ri_flow.RateIndependentNonAssociativeHardening(
surface, hard_ri)
rate_independent = models.SmallStrainRateIndependentPlasticity(
elastic_m, flow_ri)
# Combined model
self.model = models.KMRegimeModel(elastic_m,
[rate_independent, rate_dependent],
[g0], kboltz, b, eps0)
self.efinal = np.array([0.05, 0, 0, 0.02, 0, -0.01])
self.tfinal = 10.0
self.T = 700.0
self.nsteps = 100
sy_interp = interpolate.PiecewiseLinearInterpolate(list(Trange),
list(flow_stress))
iso_ri = hardening.LinearIsotropicHardeningRule(sy_interp, hmodulus)
hard_ri = hardening.Chaboche(
iso_ri, [interpolate.ConstantInterpolate(0.0)],
[hardening.ConstantGamma(interpolate.ConstantInterpolate(0.0))],
[interpolate.ConstantInterpolate(0.0)],
[interpolate.ConstantInterpolate(1.0)])
flow_ri = ri_flow.RateIndependentNonAssociativeHardening(surface, hard_ri)
rate_independent = models.SmallStrainRateIndependentPlasticity(
elastic_m, flow_ri)
# Combined model
combined = models.KMRegimeModel(elastic_m,
[rate_independent, rate_dependent], [g0],
kboltz, b, eps0)
# Do things
# Strain rate jump
Ts = np.linspace(Tmin, Tmax, 5)
erates = [
1.0e-6, 1.0e-5, 1.0e-4, 1.0e-3, 1.0e-2, 1.0e-1, 1.0e-2, 1.0e-3, 1.0e-4,
1.0e-5, 1.0e-6
]
es = [0.01] * len(erates)
for T in Ts:
strain, stress = rate_jump_test(combined, erates, es, T)
plt.plot(strain, stress)