Automatic identification of macroscopic constitutive parameters for polycrystalline materials based on computational homogenisation
Abstract
Purpose
The purpose of this research is to establish a robust numerical framework for the calibration of macroscopic constitutive parameters, based on the analysis of polycrystalline RVEs with computational homogenisation.
Design/methodology/approach
This framework is composed of four building-blocks: (1) the multi-scale model, consisting of polycrystalline RVEs, where the grains are modelled with anisotropic crystal plasticity, and computational homogenisation to link the scales, (2) a set of loading cases to generate the reference responses, (3) the von Mises elasto-plastic model to be calibrated, and (4) the optimisation algorithms to solve the inverse identification problem. Several optimisation algorithms are assessed through a reference identification problem. Thereafter, different calibration strategies are tested. The accuracy of the calibrated models is evaluated by comparing their results against an FE2 model and experimental data.
Findings
In the initial tests, the LIPO optimiser performs the best. Good results accuracy is obtained with the calibrated constitutive models. The computing time needed by the FE2 simulations is 5 orders of magnitude larger, compared to the standard macroscopic simulations, demonstrating how this framework is suitable to obtain efficient micro-mechanics-informed constitutive models.
Originality/value
This contribution proposes a numerical framework, based on FE2 and macro-scale single element simulations, where the calibration of constitutive laws is informed by multi-scale analysis. The most efficient combination of optimisation algorithm and definition of the objective function is studied, and the robustness of the proposed approach is demonstrated by validation with both numerical and experimental data.
Keywords
Acknowledgements
Guilherme Fonseca Gonçalves acknowledges the financial support provided through the research fellowship RH BII LAETA UMEC 42/2022, which was funded within the scope of FCT’s (Fundação para a Ciência e Tecnologia) “Verão com Ciência” scholarship initiative. Rui P. Cardoso Coelho also gratefully acknowledges the financial support provided by FCT through the scholarship with reference 2020.07159.BD. Igor A. Rodrigues Lopes acknowledges Fundação para Ciência e a Tecnologia (FCT) for its financial support via the project UIDB/50022/2020 (LAETA Base Funding).
Citation
Fonseca Gonçalves, G., Cardoso Coelho, R.P. and Rodrigues Lopes, I.A. (2024), "Automatic identification of macroscopic constitutive parameters for polycrystalline materials based on computational homogenisation", Engineering Computations, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/EC-12-2023-0908
Publisher
:Emerald Publishing Limited
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