Direct detection of plasticity onset through total-strain profile evolution

07/08/2021
by   Stefanos Papanikolaou, et al.
0

Plastic yielding in solids strongly depends on various conditions, such as temperature and loading rate and indeed, sample-dependent knowledge of yield points in structural materials promotes reliability in mechanical behavior. Commonly, yielding is measured through controlled mechanical testing at small or large scales, in ways that either distinguish elastic (stress) from total deformation measurements, or by identifying plastic slip contributions. In this paper we argue that instead of separate elastic/plastic measurements, yielding can be unraveled through statistical analysis of total strain fluctuations during the evolution sequence of profiles measured in-situ, through digital image correlation. We demonstrate two distinct ways of precisely quantifying yield locations in widely applicable crystal plasticity models, that apply in polycrystalline solids, either by using principal component analysis or discrete wavelet transforms. We test and compare these approaches in synthetic data of polycrystal simulations and a variety of yielding responses, through changes of the applied loading rates and the strain-rate sensitivity exponents.

READ FULL TEXT

page 4

page 5

research
01/11/2020

Continuum modelling of stress diffusion interactions in an elastoplastic medium in the presence of geometric discontinuity

Chemo-mechanical coupled systems have been a subject of interest for man...
research
01/20/2022

Physics-informed neural networks for modeling rate- and temperature-dependent plasticity

This work presents a physics-informed neural network based framework to ...
research
11/28/2022

Cell Biomechanical Modeling Based on Membrane Theory with Considering Speed Effect of Microinjection

As an effective method to deliver external materials into biological cel...
research
08/10/2016

Dynamic Principal Component Analysis: Identifying the Relationship between Multiple Air Pollutants

The dynamic nature of air quality chemistry and transport makes it diffi...
research
09/24/2017

Learning crystal plasticity using digital image correlation: Examples from discrete dislocation dynamics

Digital image correlation (DIC) is a well-established, non-invasive tech...
research
06/16/2022

Automated analysis of continuum fields from atomistic simulations using statistical machine learning

Atomistic simulations of the molecular dynamics/statics kind are regular...

Please sign up or login with your details

Forgot password? Click here to reset