MAP123-EP: a mechanistic-based data-driven approach for numerical elastoplastic analysis. 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.
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References in zbMATH (referenced in 5 articles , 1 standard article )
Showing results 1 to 5 of 5.
- Krokos, Vasilis; Xuan, Viet Bui; Bordas, Stéphane P. A.; Young, Philippe; Kerfriden, Pierre: A Bayesian multiscale CNN framework to predict local stress fields in structures with microscale features (2022)
- Qiu, Hai; Yang, Hang; Elkhodary, Khalil l.; Tang, Shan; Guo, Xu; Huang, Jinhao: A data-driven approach for modeling tension-compression asymmetric material behavior: numerical simulation and experiment (2022)
- Saha, Sourav; Gan, Zhengtao; Cheng, Lin; Gao, Jiaying; Kafka, Orion L.; Xie, Xiaoyu; Li, Hengyang; Tajdari, Mahsa; Kim, H. Alicia; Liu, Wing Kam: Hierarchical deep learning neural network (HiDeNN): an artificial intelligence (AI) framework for computational science and engineering (2021)
- Tang, Shan; Yang, Hang; Qiu, Hai; Fleming, Mark; Liu, Wing Kam; Guo, Xu: MAP123-EPF: a mechanistic-based data-driven approach for numerical elastoplastic modeling at finite strain (2021)
- Tang, Shan; Li, Ying; Qiu, Hai; Yang, Hang; Saha, Sourav; Mojumder, Satyajit; Liu, Wing Kam; Guo, Xu: MAP123-EP: a mechanistic-based data-driven approach for numerical elastoplastic analysis (2020)