scadsfct > Strain reinforced rate neural networks, direct | PUMA

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1Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning
J. Gerritzen, A. Hornig, P. Winkler, and M. Gude. ECCM21 - Proceedings of the 21st European Conference on Composite Materials, 3, page 1252--1259. European Society for Composite Materials (ESCM), (Jul 2, 2024)21st European Conference on Composite Materials, ECCM 21 ; Conference date: 02-07-2024 Through 05-07-2024.
10 months ago by @scadsfct
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Convolutional
Direct
FIS_scads
Fiber
Strain
area_architectures
dependency,
identification,
networks,
neural
parameter
plastics
rate
reinforced
topic_engineering
yaff
machine
learning
ConvolutionalDirectFIS_scadsFiberStrainarea_architecturesdependency,identification,networks,neuralparameterplasticsratereinforcedtopic_engineeringyaffmachinelearning
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