import pytest import numpy as np from damask import tensor from damask import mechanics def Cauchy(P,F): sigma = 1.0/np.linalg.det(F) * np.dot(P,F.T) return symmetric(sigma) def deviatoric_part(T): return T - np.eye(3)*spherical_part(T) def eigenvalues(T_sym): return np.linalg.eigvalsh(symmetric(T_sym)) def left_stretch(T): return polar_decomposition(T,'V')[0] def maximum_shear(T_sym): w = eigenvalues(T_sym) return (w[0] - w[2])*0.5 def Mises_strain(epsilon): return Mises(epsilon,2.0/3.0) def Mises_stress(sigma): return Mises(sigma,3.0/2.0) def PK2(P,F): S = np.dot(np.linalg.inv(F),P) return symmetric(S) def right_stretch(T): return polar_decomposition(T,'U')[0] def rotational_part(T): return polar_decomposition(T,'R')[0] def spherical_part(T,tensor=False): sph = np.trace(T)/3.0 return sph if not tensor else np.eye(3)*sph def strain_tensor(F,t,m): if t == 'V': B = np.matmul(F,F.T) w,n = np.linalg.eigh(B) elif t == 'U': C = np.matmul(F.T,F) w,n = np.linalg.eigh(C) if m > 0.0: eps = 1.0/(2.0*abs(m)) * (+ np.matmul(n,np.einsum('j,kj->jk',w**m,n)) - np.eye(3)) elif m < 0.0: eps = 1.0/(2.0*abs(m)) * (- np.matmul(n,np.einsum('j,kj->jk',w**m,n)) + np.eye(3)) else: eps = np.matmul(n,np.einsum('j,kj->jk',0.5*np.log(w),n)) return eps def symmetric(T): return (T+T.T)*0.5 def polar_decomposition(T,requested): u, s, vh = np.linalg.svd(T) R = np.dot(u,vh) output = [] if 'R' in requested: output.append(R) if 'V' in requested: output.append(np.dot(T,R.T)) if 'U' in requested: output.append(np.dot(R.T,T)) return tuple(output) def Mises(T_sym,s): d = deviatoric_part(T_sym) return np.sqrt(s*(np.sum(d**2.0))) class TestMechanics: n = 1000 c = np.random.randint(n) @pytest.mark.parametrize('vectorized,single',[(mechanics.deviatoric_part, deviatoric_part), (mechanics.spherical_part, spherical_part) ]) def test_vectorize_1_arg_(self,vectorized,single): print("done") test_data_flat = np.random.rand(self.n,3,3) test_data = np.reshape(test_data_flat,(self.n//10,10,3,3)) for i,v in enumerate(np.reshape(vectorized(test_data),vectorized(test_data_flat).shape)): assert np.allclose(single(test_data_flat[i]),v) @pytest.mark.parametrize('vectorized,single',[(mechanics.deviatoric_part, deviatoric_part), (mechanics.left_stretch , left_stretch ), (mechanics.maximum_shear , maximum_shear ), (mechanics.Mises_strain , Mises_strain ), (mechanics.Mises_stress , Mises_stress ), (mechanics.right_stretch , right_stretch ), (mechanics.rotational_part, rotational_part), (mechanics.spherical_part , spherical_part ), ]) def test_vectorize_1_arg(self,vectorized,single): epsilon = np.random.rand(self.n,3,3) epsilon_vec = np.reshape(epsilon,(self.n//10,10,3,3)) for i,v in enumerate(np.reshape(vectorized(epsilon_vec),vectorized(epsilon).shape)): assert np.allclose(single(epsilon[i]),v) @pytest.mark.parametrize('vectorized,single',[ (mechanics.Cauchy,Cauchy), (mechanics.PK2 ,PK2 ) ]) def test_vectorize_2_arg(self,vectorized,single): P = np.random.rand(self.n,3,3) F = np.random.rand(self.n,3,3) P_vec = np.reshape(P,(self.n//10,10,3,3)) F_vec = np.reshape(F,(self.n//10,10,3,3)) for i,v in enumerate(np.reshape(vectorized(P_vec,F_vec),vectorized(P,F).shape)): assert np.allclose(single(P[i],F[i]),v) @pytest.mark.parametrize('vectorized,single',[(mechanics.strain_tensor,strain_tensor)]) def test_vectorize_strain_tensor(self,vectorized,single): F = np.random.rand(self.n,3,3) F_vec = np.reshape(F,(self.n//10,10,3,3)) t = ['V','U'][np.random.randint(0,2)] m = np.random.random()*10.0 -5.0 for i,v in enumerate(np.reshape(vectorized(F_vec,t,m),vectorized(F,t,m).shape)): assert np.allclose(single(F[i],t,m),v) @pytest.mark.parametrize('function',[mechanics.Cauchy, mechanics.PK2, ]) def test_stress_measures(self,function): """Ensure that all stress measures are equivalent for no deformation.""" P = np.random.rand(self.n,3,3) assert np.allclose(function(P,np.broadcast_to(np.eye(3),(self.n,3,3))),tensor.symmetric(P)) def test_deviatoric_part(self): I_n = np.broadcast_to(np.eye(3),(self.n,3,3)) r = np.logical_not(I_n)*np.random.rand(self.n,3,3) assert np.allclose(mechanics.deviatoric_part(I_n+r),r) def test_polar_decomposition(self): """F = RU = VR.""" F = np.broadcast_to(np.eye(3),[self.n,3,3])*np.random.rand(self.n,3,3) R = mechanics.rotational_part(F) V = mechanics.left_stretch(F) U = mechanics.right_stretch(F) assert np.allclose(np.matmul(R,U), np.matmul(V,R)) @pytest.mark.parametrize('m',[0.0,np.random.random()*10.,np.random.random()*-10.]) def test_strain_tensor_no_rotation(self,m): """Ensure that left and right stretch give same results for no rotation.""" F = np.broadcast_to(np.eye(3),[self.n,3,3])*np.random.rand(self.n,3,3) assert np.allclose(mechanics.strain_tensor(F,'U',m), mechanics.strain_tensor(F,'V',m)) @pytest.mark.parametrize('m',[0.0,np.random.random()*2.5,np.random.random()*-2.5]) def test_strain_tensor_rotation_equivalence(self,m): """Ensure that left and right strain differ only by a rotation.""" F = np.broadcast_to(np.eye(3),[self.n,3,3]) + (np.random.rand(self.n,3,3)*0.5 - 0.25) assert np.allclose(np.linalg.det(mechanics.strain_tensor(F,'U',m)), np.linalg.det(mechanics.strain_tensor(F,'V',m))) @pytest.mark.parametrize('m',[0.0,np.random.random(),np.random.random()*-1.]) @pytest.mark.parametrize('t',['V','U']) def test_strain_tensor_rotation(self,m,t): """Ensure that pure rotation results in no strain.""" F = mechanics.rotational_part(np.random.rand(self.n,3,3)) assert np.allclose(mechanics.strain_tensor(F,t,m), 0.0) def test_rotation_determinant(self): """ Ensure that the determinant of the rotational part is +- 1. Should be +1, but random F might contain a reflection. """ x = np.random.rand(self.n,3,3) assert np.allclose(np.abs(np.linalg.det(mechanics.rotational_part(x))), 1.0) def test_spherical_deviatoric_part(self): """Ensure that full tensor is sum of spherical and deviatoric part.""" x = np.random.rand(self.n,3,3) sph = mechanics.spherical_part(x,True) assert np.allclose(sph + mechanics.deviatoric_part(x), x) def test_deviatoric_Mises(self): """Ensure that Mises equivalent stress depends only on deviatoric part.""" x = np.random.rand(self.n,3,3) full = mechanics.Mises_stress(x) dev = mechanics.Mises_stress(mechanics.deviatoric_part(x)) assert np.allclose(full, dev) def test_spherical_mapping(self): """Ensure that mapping to tensor is correct.""" x = np.random.rand(self.n,3,3) tnsr = mechanics.spherical_part(x,True) scalar = mechanics.spherical_part(x) assert np.allclose(np.linalg.det(tnsr), scalar**3.0) def test_spherical_Mises(self): """Ensure that Mises equivalent strrain of spherical strain is 0.""" x = np.random.rand(self.n,3,3) sph = mechanics.spherical_part(x,True) assert np.allclose(mechanics.Mises_strain(sph), 0.0) def test_Mises(self): """Ensure that equivalent stress is 3/2 of equivalent strain.""" x = np.random.rand(self.n,3,3) assert np.allclose(mechanics.Mises_stress(x)/mechanics.Mises_strain(x), 1.5) def test_spherical_no_shear(self): """Ensure that sherical stress has max shear of 0.0.""" A = mechanics.spherical_part(tensor.symmetric(np.random.rand(self.n,3,3)),True) assert np.allclose(mechanics.maximum_shear(A),0.0)