Reduced polynomial invariant integrity basis for in-plane magneto-mechanical loading

01/12/2022
by   Julien Taurines, et al.
0

The description of the behavior of a material subjected to multi-physics loadings requires the formulation of constitutive laws that usually derive from Gibbs free energies, using invariant quantities depending on the considered physics and material symmetries. On the other hand, most of crystalline materials can be described by their crystalline texture and the associated preferred directions of strong crystalline symmetry (the so-called fibers). Moreover, among the materials produced industrially, many are manufactured in the form of sheets or of thin layers. This article has for object the study of the magneto-mechanical coupling which is a function of the stress σ and the magnetization M. We consider a material with cubic symmetry whose texture can be described by one of three fibers denoted as θ, γ or α ' , and which is thin enough so that both the stress and the magnetization can be considered as in-plane quantities. We propose an algorithm able to derive linear relations between the 30 cubic invariants I k of a minimal integrity basis describing a magneto-elastic problem, when they are restricted to in-plane loading conditions and for different fiber orientations. The algorithm/program output is a reduced list of invariants of cardinal 7 for the 100-oriented θ fiber, of cardinal 15 for the 110-oriented α ' fiber and of cardinal 8 for the 111-oriented γ fiber. This reduction (compared to initial cardinal 30) can be of great help for the formulation of low-parameter macroscopic magneto-mechanical models.

READ FULL TEXT
research
06/10/2022

Finite electro-elasticity with physics-augmented neural networks

In the present work, a machine learning based constitutive model for ele...
research
02/05/2023

Neural networks meet hyperelasticity: A guide to enforcing physics

In the present work, a hyperelastic constitutive model based on neural n...
research
03/30/2023

A novel class of electro-mechanical metamaterials for stress reduction through electric fields

While most previous developed metamaterials only consider a single physi...
research
04/09/2021

Learning constitutive models from microstructural simulations via a non-intrusive reduced basis method

In order to optimally design materials, it is crucial to understand the ...
research
02/26/2021

A method for determining the parameters in a rheological model for viscoelastic materials by minimizing Tikhonov functionals

Mathematical models describing the behavior of viscoelastic materials ar...
research
03/09/2020

Discovering Symmetry Invariants and Conserved Quantities by Interpreting Siamese Neural Networks

In this paper, we introduce interpretable Siamese Neural Networks (SNN) ...

Please sign up or login with your details

Forgot password? Click here to reset