merge_elasto_plast…

plast_observer.py
View Options

			import numpy as np
			import matplotlib.pyplot as plt
			import sys
			sys.path.append("./build-clang-5.0-dbg/language_bindings/python/")
			from numpy.linalg import norm
			import muSpectre as µ



			def hyper_curve(tau_y0 = 200e6, h0 = 10e9, max_shear = 5e-2):
			bulk_m = 175e9;
			shear_m = 120e9;

			bulk_m = .833
			shear_m = .386
			Young = 9bulk_mshear_m/(3*bulk_m + shear_m)
			Poisson = Young/(2*shear_m) - 1
			print("E = {}, ν = {}".format(Young, Poisson))

			tolerance=1e-12
			dim=3
			resolution = [1,1, 1]
			lengths = [1, 1, 1]
			formulation = µ.Formulation.finite_strain

			cell = µ.Cell(resolution,
			lengths,
			formulation)
			dim = len(lengths)

			mat = µ.material.MaterialHyperElastoPlastic1_3d.make(
			cell, "hyper-elasto-plastic", Young, Poisson, tau_y0, h0)

			for pixel in cell:
			mat.add_pixel(pixel)

			cell.initialise()

			tau = list()
			sigma_xx=list()
			gammas=list()
			#tau_inc = list()
			#gamma_dot = list()
			shear_incr = 5e-3
			np_load = int(max_shear/shear_incr)
			F = np.eye(dim)

			for step in range(np_load):
			F[0,1] += shear_incr
			gammas.append(F[0,1])

			stress, tangent = cell.evaluate_stress_tangent(F.T.reshape(-1))
			mat.save_history_variables()
			tau.append(stress[dim])
			print("stress =\n", stress)
			sigma_xx.append(stress[0])
			gammas = np.array(gammas).reshape(-1)
			tau = np.array(tau)

			return gammas, tau, sigma_xx

			gammas, tau, sigma_xx = hyper_curve(tau_y0 = .006, h0 = .008*2, max_shear = 5e-2)
			plt.plot(gammas, tau, '+-', label=r"$\tau$ default")
			#plt.plot(gammas, sigma_xx, label=r"$\sigma_{{xx}}$ default")
			pass
			plt.legend(loc='best')
			plt.xlabel('ε₁₂')
			plt.ylabel('γ₁₂');

			plt.show()