
A full-field optimization approach for iterative definition of yielding for non-quadratic and free shape yield models in plane strain
Author(s) -
Holger Hippke,
Bekim Berisha,
Pavel Hora
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/967/1/012084
Subject(s) - plane stress , quadratic equation , field (mathematics) , plasticity , plane (geometry) , structural engineering , mathematics , materials science , finite element method , geometry , engineering , composite material , pure mathematics
An advanced strategy for iterative definition of initial yielding based on planar strain distribution is presented. It is shown that full-field DIC measurement of NTR5 samples provides information on initial yielding for plane strain. The interdependency of strain increment and yield locus under assumption of associated flow allows for definition of yield parameters using a non-linear optimization scheme with LS-OPT. Pivotal for research in direction of additional support points for definition of initial yielding was the discovery that definition of yielding based only on tensile and biaxial experiments is not sufficient for aluminum alloy. Special focus was placed on the area of generalized plane strain, which is the most critical stress state. Previous publications illustrated experimental options using cruciform tension and crystal plasticity as support points in generalized plane strain. This publication introduces an additional strategy to determine data for multiaxial stress states without need of additional experiments. The iterative strategy shows promising results for definition of yielding in generalized plane strain. Additionally, it is illustrated that common yield models such as non-quadratic YLD2000-2D and free-shape Vegter are sufficiently capable to describe yielding of aluminum alloy, if their full potential is exploited. The strategy is evaluated on the basis of Nakajima strain distributions and a conclusion is drawn on applicability and predictive capabilities.