Optimizing crystal plasticity model parameters via machine learning-based optimization algorithms
JUAN Rongfei, BINH Nguyen Xuan, LIU Wenqi, LIAN Junhedownload PDF
Abstract. The field of materials science and engineering is constantly evolving, and new methods are being developed to improve our understanding of the relationship between microstructure and properties. One such method is crystal plasticity (CP) modeling, which is widely used for predicting the mechanical properties of crystals and phases. However, determining the constitutive parameters for CP models has been a significant challenge, with current methods relying on either direct chemical composition or inverse fitting, both of which can be time-consuming and lack accuracy. In this study, we propose an automated, advanced, and more efficient method for determining constitutive parameters by using a genetic algorithm (GA) optimization method coupled with machine learning. Our proposed method is applied to two widely used CP models, and the reference data for the calibration is the stress-strain curve from tensile tests. The results of the automated calibration process are then compared to numerical simulation results of CP models with known parameters, demonstrating the efficiency and accuracy of our proposed method.
Crystal Plasticity Model, Machine Learning, Parameter Calibration
Published online 4/19/2023, 10 pages
Copyright © 2023 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: JUAN Rongfei, BINH Nguyen Xuan, LIU Wenqi, LIAN Junhe, Optimizing crystal plasticity model parameters via machine learning-based optimization algorithms, Materials Research Proceedings, Vol. 28, pp 1417-1426, 2023
The article was published as article 153 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.
 F. Roters, M. Diehl, P. Shanthraj, P. Eisenlohr, C. Reuber, S.L. Wong, T. Maiti, A. Ebrahimi, T. Hochrainer, H.O. Fabritius, S. Nikolov, M. Friak, N. Fujita, N. Grilli, K.G.F. Janssens, N. Jia, P.J.J. Kok, D. Ma, F. Meier, E. Werner, M. Stricker, D. Weygand, D. Raabe, DAMASK – The Dusseldorf Advanced Material Simulation Kit for modeling multi-physics crystal plasticity, thermal, and damage phenomena from the single crystal up to the component scale, Computat. Mater. Sci. 158 (2019) 420-478. https://doi.org/10.1016/j.commatsci.2018.04.030
 E. Voce, The Relationship between Stress and Strain for Homogeneous Deformation, J. I. Met. 74 (1948) 537-562.
 S.L. Wong, M. Madivala, U. Prahl, F. Roters, D. Raabe, A crystal plasticity model for twinning- and transformation-induced plasticity, Acta Mater. 118 (2016) 140-151. https://doi.org/10.1016/j.actamat.2016.07.032
 F.J. Gallardo-Basile, Y. Naunheim, F. Roters, M. Diehl, Lath Martensite Microstructure Modeling: A High-Resolution Crystal Plasticity Simulation Study, Materials 14 (2021) 691. https://doi.org/10.3390/ma14030691
 R. Juan, W. Liu, X. Inza, X. Ureta, J. Mendiguren, J. Lian, Crystal Plasticity Modeling of Al Alloy under Linear and Non-Linear Loading, Key Eng. Mater. 926 (2022) 2099-2108. http://doi.org/10.4028/p-2jqp1v
 J. Lian, W. Liu, X. Gastañares, R. Juan, J. Mendiguren, Plasticity evolution of an aluminum-magnesium alloy under abrupt strain path changes, Int. J. Mater. Form. 15 (2022) 40. https://doi.org/10.1007/s12289-022-01692-6
 M. Bertin, C.W. Du, J.P.M. Hoefnagels, F. Hild, Crystal plasticity parameter identification with 3D measurements and Integrated Digital Image Correlation, Acta Mater. 116 (2016) 321-331. https://doi.org/10.1016/j.actamat.2016.06.039
 D. Raabe, M. Sachtleber, Z. Zhao, F. Roters, S. Zaefferer, Micromechanical and macromechanical effects in grain scale polycrystal plasticity experimentation and simulation, Acta Mater. 49 (2001) 3433-3441. https://doi.org/10.1016/S1359-6454(01)00242-7
 W. Liu, J. Lian, N. Aravas, S. Münstermann, A strategy for synthetic microstructure generation and crystal plasticity parameter calibration of fine-grain-structured dual-phase steel, Int. J. Plast. 126 (2020) 102614. https://doi.org/10.1016/j.ijplas.2019.10.002
 C.C. Tasan, J.P.M. Hoefnagels, M. Diehl, D. Yan, F. Roters, D. Raabe, Strain localization and damage in dual phase steels investigated by coupled in-situ deformation experiments and crystal plasticity simulations, Int. J. Plast. 63 (2014) 198-210. http://doi.org/10.1016/j.ijplas.2014.06.004
 H.J. Bong, H. Lim, M.-G. Lee, D.T. Fullwood, E.R. Homer, R.H. Wagoner, An RVE procedure for micromechanical prediction of mechanical behavior of dual-phase steel, Mater. Sci. Eng. A 695 (2017) 101-111. https://doi.org/10.1016/j.msea.2017.04.032
 K. Sedighiani, M. Diehl, K. Traka, F. Roters, J. Sietsma, D. Raabe, An efficient and robust approach to determine material parameters of crystal plasticity constitutive laws from macro-scale stress-strain curves, Int. J. Plast. 134 (2020) 102779. https://doi.org/10.1016/j.ijplas.2020.102779
 J. Kuhn, J. Spitz, P. Sonnweber-Ribic, M. Schneider, T. Bohlke, Identifying material parameters in crystal plasticity by Bayesian optimization, Optim. Eng. 23 (2022) 1489-1523. https://doi.org/10.1007/s11081-021-09663-7
 K. Zhang, B. Holmedal, S. Hopperstad, S. Dumoulin, J. Gawad, A. Van Bael, P. Van Houtte, Multi-level modelling of mechanical anisotropy of commercial pure aluminium plate: Crystal plasticity models, advanced yield functions and parameter identification, Int. J. Plast. 66 (2015) 3-30. https://doi.org/10.1016/j.ijplas.2014.02.003
 D.T. Do, D.H. Lam, T. Nguyen, T.T. Phuong Mai, L.T.M. Phan, H.T. Vuong, D.V. Nguyen, N.T.T. Linh, M.N. Hoang, T.P. Mai, H.H. Nguyen, Utilization of Response Surface Methodology in Optimization of Polysaccharides Extraction from Vietnamese Red Ganoderma lucidum by Ultrasound-Assisted Enzymatic Method and Examination of Bioactivities of the Extract, Scientific World Journal 2021 (2021) 7594092. https://doi.org/10.1155/2021/7594092
 P. Himani Panwar, Dharamveer Singh, Abha Singh, Genetic Algorithm for Solving Simple Mathematical Equality Problem, IRJET 07 (2020) 7622-7627.