CPINet: parameter identification of path-dependent constitutive model with automatic denoising based on CNN-LSTM
DOI10.1016/j.euromechsol.2021.104327zbMath1478.74013OpenAlexW3172378095MaRDI QIDQ1982319
Hao Jiang, Zhenkun Lei, Zhenfei Guo, Da Liu, Jianchao Zou, Ruixiang Bai, Cheng Yan
Publication date: 8 September 2021
Published in: European Journal of Mechanics. A. Solids (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.euromechsol.2021.104327
denoisingelasto-plastic modelconstitutive parameter identificationconvolutional neural nerworkpath-dependent parameter
Neural networks for/in biological studies, artificial life and related topics (92B20) Small-strain, rate-independent theories of plasticity (including rigid-plastic and elasto-plastic materials) (74C05) Theory of constitutive functions in solid mechanics (74A20) Numerical and other methods in solid mechanics (74S99)
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