Published December 2016 | Version v1
Journal article

On the determination of the anisotropic plasticity of metal materials by using instrumented indentation

  • 1. School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, 710072 (China)

Description

Highlights: • A new method is proposed to estimate the anisotropic plasticity of metal materials by using instrumented indentation. • The ill-posed nature of using only the indentation P-h curve in the inverse analysis process is investigated. • By introducing the pile-up effects, the well-posed solution is obtained. • Effectiveness of the new approach is verified by application on two engineering materials. In this paper, an inverse computation approach is proposed to estimate the anisotropic plastic properties of materials by using the instrumented indentation. For the anisotropic materials considered in the present study, the plastic properties (e.g. the stress strain curves) along orthogonal directions (e.g. longitudinal vs. transverse) are different. This approach is based on weighting the information collected from instrumented indentation and the conventional optimization algorithm. The ill-posed nature of using only the indentation load-displacement curve in the inverse analysis process is investigated. To obtain a unique solution, the pile-up values around indenter are considered as important additional information. Results show that, by introducing the pile-up values, the inverse analysis gives well-posed solution of the anisotropic plastic properties. The new approach is applied on two metal materials, and the anisotropic properties obtained from indentation and uniaxial tests show good agreement.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.matdes.2016.08.076

Additional details

Identifiers

DOI
10.1016/j.matdes.2016.08.076;
PII
S0264127516311388;

Publishing Information

Journal Title
Materials and Design
Journal Volume
111
Journal Page Range
p. 98-107
ISSN
0264-1275

Optional Information

Copyright
Copyright (c) 2016 Elsevier Ltd. All rights reserved.