| Data-model-coupling method for fracture analysis of composite structures Ping Li1; Zengtao Kuang2; Jie Yang1; Qun Huang1; Wei Huang1; Heng Hu1; 1WUHAN UNIVERSITY, Wuhan, China; 2, Wuhan, China; PAPER: 467/Modelling/Keynote (Oral) SCHEDULED: 17:10/Mon. 28 Nov. 2022/Similan 1 ABSTRACT: Recently, a data-model-coupling method has been proposed based on a unified functional. This approach represents both the governing equations of data-driven computing and model-driven computing by using the same distance-based functional, thus enabling the two algorithms to be freely interconverted. The present study aims to further demonstrate the effectiveness of this coupling method in fracture analysis of composite structures. The data-driven algorithm is used in the area where the material modelling is complex, while the model-driven algorithm is applied in the rest areas to ensure high computational efficiency. The extended finite element method (XFEM) is employed to model the crack discontinuity and track the crack propagation path. We take a sandwich structure with an initial crack as an example to verify the effectiveness of the coupling method. The results demonstrate the capability of this coupling method to correctly predict the crack propagation path in composite structures. References: [1] T. Kirchdoerfer, M. Ortiz, Data-driven computational mechanics, Computer Methods in Applied Mechanics and Engineering 304 (2016) 81-101. [2] A. Platzer, A. Leygue, L. Stainier, M. Ortiz, Finite element solver for data-driven finite strain elasticity, Computer Methods in Applied Mechanics and Engineering 379 (2021) 113756. [3] L. T. K. Nguyen, M.-A. Keip, A data-driven approach to nonlinear elasticity, Computers & Structures 194 (2018) 97-115. [4] T. Kirchdoerfer, M. Ortiz, Data-driven computing in dynamics, International Journal for Numerical Methods in Engineering 113 (11) (2018) 1697-1710. [5] Y. Zhou, H. Zhan, W. Zhang, J. Zhu, J. Bai, Q. Wang, Y. Gu, A new data-driven topology optimization framework for structural optimization, Computers & Structures 239 (2020) 106310. [6] J. Yang, R. Xu, H. Hu, Q. Huang, W. Huang, Structural-genome-driven computing for thin composite structures, Composite Structures 215 (2019) 446-453. [7] R. Xu, J. Yang, W. Yan, Q. Huang, H. Hu, Data-driven multiscale finite element method: From concurrence to separation, Computer Methods in Applied Mechanics and Engineering 363 (2020) 112893. [8] X. Bai, J. Yang, W. Yan, Q. Huang, S. Belouettar, H. Hu, A data-driven approach for instability analysis of thin composite structures, Computers & Structures 273(2022) 106898. [9] W. Yan, W. Huang, Q. Huang, J. Yang, G. Giunta, S. Belouettar, H. Hu, Data-driven multiscale method for composite plates, Computational Mechanics 70 (5) (2022) 1025-1040. [10] J. Yang, X. Bai, W. Yan, W. Huang, Q. Huang, Q. Shao, H. Hu, An efficient hierarchical data searching scheme for data-driven computational mechanics, Chinese Journal of Solid Mechanics 42 (3) (2021) 241-248. [11] T. F. Korzeniowski, K. Weinberg, A multi-level method for data-driven finite element computations, Computer Methods in Applied Mechanics and Engineering 379 (2021)113740. [12] J. Yang, W. Huang, Q. Huang, H. Hu, An investigation on the coupling of data-driven computing and model-driven computing, Computer Methods in Applied Mechanics and Engineering 393 (2022) 114798. [13] S. Wattel, J.-F. Molinari, M. Ortiz, J. Garcia-Suarez, Mesh d-refinement: a databased computational framework to account for complex material response (2022). doi:10.48550/ARXIV.2212.08503. [14] J. Yang, P. Li, Y. Zhang, Y. Hui, L. Xu, N. Damil, H. Hu, Unified functional based data-model-coupling computing for composite materials and structures, [15] Q. Shao, Y. Liu, Joule heating effect on thermal stress for a bi-material interface crack, International Journal of Solids and Structures 226 (2021) 111069. |
