期刊
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
卷 364, 期 -, 页码 -出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.cma.2020.112955
关键词
Data-driven; Elastoplastic material; Constitutive law; Finite element analysis; Strain-driven
资金
- NSF of China [11872139, 11732004, 11821202]
- Program for Changjiang Scholars, and Innovative Research Team in University (PCSIRT)
- United States National Science Foundation (NSF) [MOMS/CMMI-1762035]
In this paper, a mechanistic-based data-driven approach, MAP123-EP, is proposed for numerical analysis of elastoplastic materials. In this method, stress-update is driven by a set of one-dimensional stress-strain data generated by numerical or physical experiments under uniaxial loading. Numerical results indicate that combined with the classical strain-driven scheme, the proposed method can predict the mechanical response of isotropic elastoplastic materials (characterized by J2 plasticity model with isotropic/kinematic hardening and associated Drucker-Prager model) accurately without resorting to the typical ingredients of classical model-based plasticity, such as decomposing the total strain into elastic and plastic parts, as well as identifying explicit functional expressions of yielding surface and hardening curve. This mechanistic-based data-driven approach has the potential of opening up a new avenue for numerical analysis of problems where complex material behaviors cannot be described in explicit function/functional forms. The applicability and limitation of the proposed approach are also discussed. (C) 2020 Elsevier B.V. All rights reserved.
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