# Copyright (c) 2012-2024, OpenGeoSys Community (http://www.opengeosys.org)
# Distributed under a Modified BSD License.
# See accompanying file LICENSE.txt or
# http://www.opengeosys.org/project/license
#
"""Common tensor transformation operations.
They can be used as they are, but are also part of
:py:obj:`ogstools.variables.matrix.Matrix` variables.
All input arrays are expected to be in vector notation of symmetric tensors in
the form of:
[xx, yy, zz, xy] for 2D and
[xx, yy, zz, xy, yz, xz] for 3D.
This notation style is the default output of OGS:
<https://www.opengeosys.org/docs/userguide/basics/conventions/#a-namesymmetric-tensorsa--symmetric-tensors-and-kelvin-mapping>
A better overview for the theoretical background of the equations can be found
here, for example:
<https://en.wikipedia.org/wiki/Cauchy_stress_tensor#Cauchy's_stress_theorem%E2%80%94stress_tensor>
"""
from typing import TypeAlias, TypeVar
import numpy as np
from numpy import linalg as LA
from pint.facets.plain import PlainQuantity, PlainUnit
from .unit_registry import u_reg
ValType: TypeAlias = PlainQuantity | np.ndarray
T = TypeVar("T")
def _split_quantity(values: ValType) -> tuple[np.ndarray, PlainUnit | None]:
if isinstance(values, PlainQuantity):
return values.magnitude, values.units
return values, None
def _to_quantity(
values: np.ndarray, unit: PlainUnit | None
) -> np.ndarray | PlainQuantity:
return values if unit is None else u_reg.Quantity(values, unit)
[docs]
def identity(vals: T) -> T:
":returns: The input values."
return vals
[docs]
def sym_tensor_to_mat(values: ValType) -> ValType:
"Convert an symmetric tensor to a 3x3 matrix."
vals, unit = _split_quantity(values)
assert np.shape(vals)[-1] in [4, 6]
shape = list(np.shape(vals))[:-1] + [3, 3]
mat = np.zeros(shape)
mat[..., 0, 0] = vals[..., 0]
mat[..., 1, 1] = vals[..., 1]
mat[..., 2, 2] = vals[..., 2]
mat[..., 0, 1] = vals[..., 3]
mat[..., 1, 0] = vals[..., 3]
if np.shape(vals)[-1] == 6:
mat[..., 0, 2] = vals[..., 4]
mat[..., 2, 0] = vals[..., 4]
mat[..., 1, 2] = vals[..., 5]
mat[..., 2, 1] = vals[..., 5]
return _to_quantity(mat, unit)
[docs]
def trace(values: ValType) -> ValType:
"""Return the trace of the given symmetric tensor.
:math:`tr(\\mathbf{\\sigma}) = \\sum\\limits_{i=1}^3 \\sigma_{ii}`
"""
vals, unit = _split_quantity(values)
return _to_quantity(np.sum(vals[..., :3], axis=-1), unit)
[docs]
def matrix_trace(values: ValType) -> ValType:
"""Return the trace of the given matrix.
:math:`tr(\\mathbf{\\sigma}) = \\sum\\limits_{i=1}^3 \\sigma_{ii}`
"""
vals, unit = _split_quantity(values)
return _to_quantity(np.trace(vals, axis1=-2, axis2=-1), unit)
[docs]
def eigenvalues(values: ValType) -> ValType:
"Return the eigenvalues."
mat_vals, unit = _split_quantity(sym_tensor_to_mat(values))
eigvals: np.ndarray = LA.eigvals(mat_vals)
eigvals.sort(axis=-1)
assert np.all(eigvals[..., 0] <= eigvals[..., 1])
assert np.all(eigvals[..., 1] <= eigvals[..., 2])
return _to_quantity(eigvals, unit)
[docs]
def eigenvectors(values: ValType) -> ValType:
"Return the eigenvectors."
mat_vals, unit = _split_quantity(sym_tensor_to_mat(values))
eigvals, eigvecs = LA.eig(mat_vals)
ids = eigvals.argsort(axis=-1)
eigvals = np.take_along_axis(eigvals, ids, axis=-1)
eigvecs = np.take_along_axis(eigvecs, ids[:, np.newaxis], axis=-1)
assert np.all(eigvals[..., 0] <= eigvals[..., 1])
assert np.all(eigvals[..., 1] <= eigvals[..., 2])
return _to_quantity(eigvecs, unit)
[docs]
def det(values: ValType) -> ValType:
"Return the determinants."
mat_vals, unit = _split_quantity(sym_tensor_to_mat(values))
if unit is not None:
unit *= unit
return _to_quantity(np.linalg.det(mat_vals), unit)
[docs]
def frobenius_norm(values: ValType) -> ValType:
"""Return the Frobenius norm.
:math:`||\\mathbf{\\sigma}||_F = \\sqrt{ \\sum\\limits_{i=1}^m \\sum\\limits_{j=1}^n |\\sigma_{ij}|^2 }`
"""
mat_vals, unit = _split_quantity(sym_tensor_to_mat(values))
return _to_quantity(np.linalg.norm(mat_vals, axis=(-2, -1)), unit)
[docs]
def invariant_1(values: ValType) -> ValType:
"""Return the first invariant.
:math:`I1 = tr(\\mathbf{\\sigma})`
"""
return trace(values)
[docs]
def invariant_2(values: ValType) -> ValType:
"""Return the second invariant.
:math:`I2 = \\frac{1}{2} \\left[(tr(\\mathbf{\\sigma}))^2 - tr(\\mathbf{\\sigma}^2) \\right]`
"""
mat_vals = sym_tensor_to_mat(values)
return 0.5 * (trace(values) ** 2 - matrix_trace(mat_vals @ mat_vals))
[docs]
def invariant_3(values: ValType) -> ValType:
"""Return the third invariant.
:math:`I3 = det(\\mathbf{\\sigma})`
"""
return det(values)
[docs]
def mean(values: ValType) -> ValType:
"""Return the mean value.
Also called hydrostatic component or octahedral normal component.
:math:`\\pi = \\frac{1}{3} I1`
"""
return (1.0 / 3.0) * invariant_1(values)
[docs]
def effective_pressure(values: ValType) -> ValType:
"""Return the effective pressure.
:math:`\\pi = -\\frac{1}{3} I1`
"""
return -mean(values)
[docs]
def hydrostatic_component(values: ValType) -> ValType:
"""Return the hydrostatic component.
:math:`p_{ij} = \\pi \\delta_{ij}`
"""
vals, unit = _split_quantity(values)
result = vals * 0.0
result[..., :3] = _split_quantity(mean(vals))[0][..., np.newaxis]
return _to_quantity(result, unit)
[docs]
def deviator(values: ValType) -> ValType:
"""Return the deviator.
:math:`s_{ij} = \\sigma_{ij} - \\pi \\delta_{ij}`
"""
return values - hydrostatic_component(values)
[docs]
def deviator_invariant_1(values: ValType) -> ValType:
"""Return the first invariant of the deviator.
:math:`J1 = 0`
"""
return trace(deviator(values))
[docs]
def deviator_invariant_2(values: ValType) -> ValType:
"""Return the second invariant of the deviator.
:math:`J2 = \\frac{1}{2} tr(\\mathbf{s}^2)`
"""
mat_dev = sym_tensor_to_mat(deviator(values))
return 0.5 * matrix_trace(mat_dev @ mat_dev)
[docs]
def deviator_invariant_3(values: ValType) -> ValType:
"""Return the third invariant of the deviator.
:math:`J3 = \\frac{1}{3} tr(\\mathbf{s}^3)`
"""
mat_dev = sym_tensor_to_mat(deviator(values))
return (1.0 / 3.0) * matrix_trace(mat_dev @ mat_dev @ mat_dev)
[docs]
def octahedral_shear(values: ValType) -> ValType:
"""Return the octahedral shear value.
:math:`\\tau_{oct} = \\sqrt{\\frac{2}{3} J2}`
"""
return np.sqrt((2.0 / 3.0) * deviator_invariant_2(values))
[docs]
def von_mises(values: ValType) -> ValType:
"""Return the von Mises stress.
:math:`\\sigma_{Mises} = \\sqrt{3 J2}`
"""
return np.sqrt(3.0 * deviator_invariant_2(values))
[docs]
def qp_ratio(values: ValType) -> ValType:
"""Return the qp ratio (von Mises stress / effective pressure).
:math:`qp = \\sigma_{Mises} / \\pi`
"""
return von_mises(values) / effective_pressure(values)
