elasticipy - v4.0.0

Refactored project structure

In order to simplify the syntax and comply with PEP8 convention, the following changes have been made:

StiffnessTensor and ComplianceTensor are now at: Elasticipy.tensors.elasticity
StrainTensor and StressTensor are now at: Elasticipy.tensors.stress_strain
ThermalExpansion is now at: Elasticipy.tensors.thermal_expansion

For instance, the former import statements

````python

Old syntax

from Elasticipy.FourthOrderTensor import StiffnessTensor from Elasticipy.StressStressTensors import StressTensor, StrainTensor from Elasticipy.ThermalExpansion import ThermalExpansionTensor becomespython

New syntax

from Elasticipy.tensors.elasticity import StiffnessTensor from Elasticipy.tensors.stressstrain import StressTensor, StrainTensor from Elasticipy.tensors.thermalexpansion import ThermalExpansionTensor ````

Backward compatibility has been maintained, but a deprecation warning is raised if one uses the old syntax.

Multidimensional arrays of 4th-order tensors

It is now possible to define nd-arrays of 4th-order tensors (such as StiffnessTensor). This can easily be done with orix rotations. These arrays no longer store the orientations, but all the rotated components as a (...,6,6) matrix.

General-purpose 4th-order tensors

The release introduces the classes FourthOrderTensor and SymmetricFourthOrderTensor. This allows to perform tensor operation on between two 4th-order tensors.

New features

This release provides new features, such as:

invariants for SymmetricFourthOrderTensor
invariant-based tests for isotropic, cubic and tetragonal symmetries
invariant-based method to compute the Zener ratio

- Python
Published by DorianDepriester 11 months ago

elasticipy - v3.0.0

New syntax for basic operations between tensor arrays

Tensor product: broadcasting or cross-combinations?

In order to avoid confusion, tensor product with single contraction (e.g. matrix-like product) is now made with dot. By default, if the two tensors to be multiplied are multidimensional tensor arrays, the product is made on the last coincident axes, according to the numpy's broadcasting rules. E.g.:

python a = StressTensor.rand(4, 5) b = StrainTensor.rand(5) ab = a.dot(b) ab.shape (4, 5,)

Conversely, if one wants to compute all cross-combinations, he/she must use mode='cross' option, thus increasing the dimensionality of the returned tensor:

python ab_cross=a.dot(b, mode='cross') ab_cross.shape (4, 5, 5)

Rotation of tensors

The same considerations also apply with rotate (which takes the option mode='cross' to compute all cross-combinations between the single tensors and the considered rotations).

What about `*` operator then?

Standard multiplication (*) still works; it is just a shortcut for dot and rotate (depending on the type of object used for mutliplication). For instance:

np.all(a.dot(b) == a*b) True

And `matmul`?

For backward compatibilitymatmul still works, but throws a warning message mentioning its deprecation.

Other features

convertion of second-order tensors from/to vector(s), according to the Voigt or Kelvin(-Mandel) conventions,
convertion of StiffnessTensor and ComplianceTensor from/to (6,6) Kelvin matrix,
tensor analysis (e.g. eigenstiffnesses/eigencompliances),
supports for multidim arrays of FourthOrderTensor thanks to multidim rotations, as provided by Orix,
minor bug fixes.

- Python
Published by DorianDepriester 12 months ago

elasticipy - v2.9.0

The main new feature of this release is the implementation of the Johnson-Cook plasticity model, available for J2 and Tresca criteria. The following tutorial explains how this works: https://elasticipy.readthedocs.io/en/latest/

Full Changelog: https://github.com/DorianDepriester/Elasticipy/compare/v2.8.10...v2.9.0