""" Finite-strain continuum mechanics. All routines operate on numpy.ndarrays of shape (...,3,3). """ from typing import Sequence as _Sequence, Union as _Union #, Literal as _Literal import numpy as _np from . import tensor as _tensor from . import _rotation def deformation_Cauchy_Green_left(F: _np.ndarray) -> _np.ndarray: r""" Calculate left Cauchy-Green deformation tensor (Finger deformation tensor). Parameters ---------- F : numpy.ndarray, shape (...,3,3) Deformation gradient. Returns ------- B : numpy.ndarray, shape (...,3,3) Left Cauchy-Green deformation tensor. Notes ----- .. math:: \vb{B} = \vb{F} \vb{F}^\text{T} """ return _np.matmul(F,_tensor.transpose(F)) def deformation_Cauchy_Green_right(F: _np.ndarray) -> _np.ndarray: r""" Calculate right Cauchy-Green deformation tensor. Parameters ---------- F : numpy.ndarray, shape (...,3,3) Deformation gradient. Returns ------- C : numpy.ndarray, shape (...,3,3) Right Cauchy-Green deformation tensor. Notes ----- .. math:: \vb{C} = \vb{F}^\text{T} \vb{F} """ return _np.matmul(_tensor.transpose(F),F) def equivalent_strain_Mises(epsilon: _np.ndarray) -> _np.ndarray: r""" Calculate the Mises equivalent of a strain tensor. Parameters ---------- epsilon : numpy.ndarray, shape (...,3,3) Symmetric strain tensor of which the von Mises equivalent is computed. Returns ------- epsilon_vM : numpy.ndarray, shape (...) Von Mises equivalent strain of epsilon. Notes ----- The von Mises equivalent of a strain tensor is defined as: .. math:: \epsilon_\text{vM} = \sqrt{\frac{2}{3}\,\epsilon^\prime_{ij} \epsilon^\prime_{ij}} where :math:`\vb*{\epsilon}^\prime` is the deviatoric part of the strain tensor. """ return _equivalent_Mises(epsilon,2.0/3.0) def equivalent_stress_Mises(sigma: _np.ndarray) -> _np.ndarray: r""" Calculate the Mises equivalent of a stress tensor. Parameters ---------- sigma : numpy.ndarray, shape (...,3,3) Symmetric stress tensor of which the von Mises equivalent is computed. Returns ------- sigma_vM : numpy.ndarray, shape (...) Von Mises equivalent stress of sigma. Notes ----- The von Mises equivalent of a stress tensor is defined as: .. math:: \sigma_\text{vM} = \sqrt{\frac{3}{2}\,\sigma^\prime_{ij} \sigma^\prime_{ij}} where :math:`\vb*{\sigma}^\prime` is the deviatoric part of the stress tensor. """ return _equivalent_Mises(sigma,3.0/2.0) def maximum_shear(T_sym: _np.ndarray) -> _np.ndarray: """ Calculate the maximum shear component of a symmetric tensor. Parameters ---------- T_sym : numpy.ndarray, shape (...,3,3) Symmetric tensor of which the maximum shear is computed. Returns ------- gamma_max : numpy.ndarray, shape (...) Maximum shear of T_sym. """ w = _tensor.eigenvalues(T_sym) return (w[...,0] - w[...,2])*0.5 def rotation(T: _np.ndarray) -> _rotation.Rotation: r""" Calculate the rotational part of a tensor. Parameters ---------- T : numpy.ndarray, shape (...,3,3) Tensor of which the rotational part is computed. Returns ------- R : damask.Rotation, shape (...) Rotational part of the vector. Notes ----- The rotational part is calculated from the polar decomposition: .. math:: \vb{R} = \vb{T} \vb{U}^{-1} = \vb{V}^{-1} \vb{T} where :math:`\vb{V}` and :math:`\vb{U}` are the left and right stretch tensor, respectively. """ return _rotation.Rotation.from_matrix(_polar_decomposition(T,'R')[0]) def strain(F: _np.ndarray, #t: _Literal['V', 'U'], should work, but rejected by SC t: str, m: float) -> _np.ndarray: r""" Calculate strain tensor (Seth–Hill family). Parameters ---------- F : numpy.ndarray, shape (...,3,3) Deformation gradient. t : {'V', 'U'} Type of the polar decomposition, 'V' for left stretch tensor or 'U' for right stretch tensor. m : float Order of the strain. Returns ------- epsilon : numpy.ndarray, shape (...,3,3) Strain of F. Notes ----- The strain is defined as: .. math:: \vb*{\epsilon}_V^{(m)} = \frac{1}{2m} (\vb{V}^{2m} - \vb{I}) \\\\ \vb*{\epsilon}_U^{(m)} = \frac{1}{2m} (\vb{U}^{2m} - \vb{I}) References ---------- | https://en.wikipedia.org/wiki/Finite_strain_theory | https://de.wikipedia.org/wiki/Verzerrungstensor """ if t not in ['V', 'U']: raise ValueError('polar decomposition type not in {V, U}') w,n = _np.linalg.eigh(deformation_Cauchy_Green_left(F) if t=='V' else deformation_Cauchy_Green_right(F)) return 0.5 * _np.einsum('...j,...kj,...lj',_np.log(w),n,n) if m == 0.0 \ else 0.5/m * (_np.einsum('...j,...kj,...lj', w**m,n,n) - _np.eye(3)) def stress_Cauchy(P: _np.ndarray, F: _np.ndarray) -> _np.ndarray: """ Calculate the Cauchy stress (true stress). Resulting tensor is symmetrized as the Cauchy stress needs to be symmetric. Parameters ---------- P : numpy.ndarray, shape (...,3,3) First Piola-Kirchhoff stress. F : numpy.ndarray, shape (...,3,3) Deformation gradient. Returns ------- sigma : numpy.ndarray, shape (...,3,3) Cauchy stress. """ return _tensor.symmetric(_np.einsum('...,...ij,...kj',1.0/_np.linalg.det(F),P,F)) def stress_second_Piola_Kirchhoff(P: _np.ndarray, F: _np.ndarray) -> _np.ndarray: """ Calculate the second Piola-Kirchhoff stress. Resulting tensor is symmetrized as the second Piola-Kirchhoff stress needs to be symmetric. Parameters ---------- P : numpy.ndarray, shape (...,3,3) First Piola-Kirchhoff stress. F : numpy.ndarray, shape (...,3,3) Deformation gradient. Returns ------- S : numpy.ndarray, shape (...,3,3) Second Piola-Kirchhoff stress. """ return _tensor.symmetric(_np.einsum('...ij,...jk',_np.linalg.inv(F),P)) def stretch_left(T: _np.ndarray) -> _np.ndarray: r""" Calculate left stretch of a tensor. Parameters ---------- T : numpy.ndarray, shape (...,3,3) Tensor of which the left stretch is computed. Returns ------- V : numpy.ndarray, shape (...,3,3) Left stretch tensor from Polar decomposition of T. Notes ----- The left stretch tensor is calculated from the polar decomposition: .. math:: \vb{V} = \vb{T} \vb{R}^\text{T} where :math:`\vb{R}` is a rotation. """ return _polar_decomposition(T,'V')[0] def stretch_right(T: _np.ndarray) -> _np.ndarray: r""" Calculate right stretch of a tensor. Parameters ---------- T : numpy.ndarray, shape (...,3,3) Tensor of which the right stretch is computed. Returns ------- U : numpy.ndarray, shape (...,3,3) Left stretch tensor from Polar decomposition of T. Notes ----- The right stretch tensor is calculated from the polar decomposition: .. math:: \vb{U} = \vb{R}^\text{T} \vb{T} where :math:`\vb{R}` is a rotation. """ return _polar_decomposition(T,'U')[0] def _polar_decomposition(T: _np.ndarray, requested: _Union[str, _Sequence[str]]) -> tuple: """ Perform singular value decomposition. Parameters ---------- T : numpy.ndarray, shape (...,3,3) Tensor of which the singular values are computed. requested : sequence of {'R', 'U', 'V'} Requested outputs: 'R' for the rotation tensor, 'V' for left stretch tensor, and 'U' for right stretch tensor. Returns ------- VRU : tuple of numpy.ndarray, shape (...,3,3) Requested components of the singular value decomposition. """ if isinstance(requested, str): requested = [requested] u, _, vh = _np.linalg.svd(T) R = u @ vh output = [] if 'R' in requested: output+=[R] if 'V' in requested: output+=[_np.einsum('...ij,...kj',T,R)] if 'U' in requested: output+=[_np.einsum('...ji,...jk',R,T)] if len(output) == 0: raise ValueError('output not in {V, R, U}') return tuple(output) def _equivalent_Mises(T_sym: _np.ndarray, s: float) -> _np.ndarray: """ Base equation for Mises equivalent of a stress or strain tensor. Parameters ---------- T_sym : numpy.ndarray, shape (...,3,3) Symmetric tensor of which the von Mises equivalent is computed. s : float Scaling factor (2/3 for strain, 3/2 for stress). Returns ------- eq : numpy.ndarray, shape (...) Scaled second invariant of the deviatoric part of T_sym. """ d = _tensor.deviatoric(T_sym) return _np.sqrt(s*_np.sum(d**2.0,axis=(-1,-2)))