Impact of DIC biases on the selection process of a unique test for anisotropic plasticity characterization

Jean-David Thoby,Bertrand Langrand,Thomas Fourest,Delphine Notta‐Cuvier ,Éric Markiewicz

doi:10.1051/epjconf/202125001001

Abstract

The exploitation of field measurements with inverse identification methods may reduce the number of required tests to characterize complex material constitutive models, provided that the generated stress field is sensitive enough to the targeted material parameters. For anisotropic elastoplastic material, the objective is to generate various stress states in the specimen through a single test. In this study, the effect of Digital Image Correlation measurement biases on the selection of the most suitable specimen geometry for characterisation of a complex anisotropic plasticity criterion using a unique uniaxial tensile test is investigated. To this aim, finite element (FE) based synthetic images are generated and DIC is used on these images. The biases in DIC measurement result in biased stress states that may cause errors in identification results.

Highlights

Commercial aviation industry is facing important challenges regarding the expectations about reduction of CO2 emissions
A first approach can be based on the exploitation of strain fields, following the indicator suggested by Souto et al (6) [12]
The objective was to quantify the influence of Digital Image Correlation (DIC) measurement biases on the selection procedure of a specimen geometry to identify material parameters of an anisotropic yield criterion

Summary

Introduction

Commercial aviation industry is facing important challenges regarding the expectations about reduction of CO2 emissions. In addition to studies on propulsion systems, engineers are focussing on reducing the weight of aircraft. This work involves manufacturing techniques, part design and selection of new lightweight materials. Each of these aspects relies on numerical predictions of aircraft structures behaviour. The quality of these simulations depends on the accuracy of constitutive laws for material behaviour modelling, which can be complex. Several laminated aluminium alloys (e.g. AA2198T351) show strong anisotropic behaviour that requires the definition and characterization of appropriate yield criteria [1]

Objectives

Results

Conclusion