Inverse identification of anisotropic plasticity model parameters using FEMU and a heterogeneous test
Mafalda Gonçalves, Sandrine Thuillier, António Andrade-Campos
Abstract. Accurate characterization of the anisotropic plastic behavior of sheet metals is critical for predicting their performance in forming operations. Traditional testing methods often struggle to capture complex material responses under varied loading conditions. This study focuses on combining a heterogeneous mechanical test with the Finite Element Model Updating (FEMU) technique to inversely identify the parameters from an anisotropic plasticity model. The experiments employed a specimen geometry designed through topology optimization – TopOpt, from which full-field data was extracted using Digital Image Correlation (DIC) from both surfaces. Numerical simulation was conducted using a finite element model reproducing the experimental boundary conditions, with material parameters calibrated through quasi-homogeneous tests assuming isotropic behavior. The FEMU procedure was then applied to calibrate the Swift-Voce hardening law and the Yld2004-18p yield criterion, using experimental data from both surfaces of the TopOpt specimen. This work allowed for the evaluation of the TopOpt specimen’s capability to provide sufficient data for parameter identification with the results highlighting the complexity of calibrating such an advanced material model with a single experiment.
Keywords
Heterogeneous Test, Anisotropic Plasticity, Inverse Identification
Published online 5/7/2025, 10 pages
Copyright © 2025 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: Mafalda Gonçalves, Sandrine Thuillier, António Andrade-Campos, Inverse identification of anisotropic plasticity model parameters using FEMU and a heterogeneous test, Materials Research Proceedings, Vol. 54, pp 1548-1557, 2025
DOI: https://doi.org/10.21741/9781644903599-167
The article was published as article 167 of the book Material Forming
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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