Experimental and computational issues for automated extraction of plasticity parameters from spherical indentation
Published version
Peer-reviewed
Repository URI
Repository DOI
Change log
Authors
Abstract
Software packages are being developed for automated extraction of plasticity parameters from indentation data (primarily load-displacement plots, although residual indent dimension data are also likely to be useful). Their design must be closely integrated with the associated experimental measurements. The procedure involves iterative FE simulation of the penetration of a spherical indenter into a sample, with automated convergence on a best-fit set of parameter values characterizing the yielding and work hardening response of the material (in a constitutive law). This paper outlines the main issues involved in optimization of experimental conditions and model formulation. Illustrative experimental data are presented from extruded rods of 5 metallic materials. Experimental issues include the dimensional scales of the indenter radius, R, and the depth of penetration, δ, with δ/R (the “penetration ratio”) being of particular significance. A brief study is presented of the potentially conflicting requirements of deforming a volume large enough to represent the response of the bulk and having a value of δ/R that creates plastic strains in a range that will adequately capture the work hardening response. A key conclusion of this study is that a “mid-range” indentation facility is likely to be optimal, with a load capability of at least a few kN, able to create δ/R values up to ~40%, with R ~0.5-2 mm. Other experimental issues include displacement measurement techniques, calibration of machine compliance and the possibility of material anisotropy (due to crystallographic texture). Issues related to formulation of the FE model include specification of the domain and mesh, selection of the constitutive plasticity law and simulation of interfacial friction. The convergence algorithm used is also described.
Description
Keywords
Journal Title
Conference Name
Journal ISSN
1872-7743
Volume Title
Publisher
Publisher DOI
Sponsorship
Leverhulme Trust (IN-2016-004)
EPSRC (EP/K503757/1)
EPSRC (1504177)