Neural Networks NARX for Durability Bonded Joint Prediction - Cnam - Conservatoire national des arts et métiers
Communication Dans Un Congrès Année : 2021

Neural Networks NARX for Durability Bonded Joint Prediction

Résumé

From the experimental data of the asymetric cleavage test at the bonded joint we studied the crack length propagation as a function of the fracture energy thanks an artificial neural networks. We used the Nonlinear Autoregressive Exogenous (NARX) neural network. The model predicts the crack length with a good agreement with the experimental findings. However, training of the stabilization crack on too long time can cause over-training.
Fichier principal
Vignette du fichier
IMECS2021_pp13-17 (1).pdf (1.57 Mo) Télécharger le fichier
Origine Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-04101626 , version 1 (10-07-2023)

Identifiants

  • HAL Id : hal-04101626 , version 1

Citer

Helene Canot, Philippe Durand, Emmanuel Frénod, Valérie Nassiet, Dariush Ghorbanzadeh. Neural Networks NARX for Durability Bonded Joint Prediction. International MultiConference of Engineers and Computer Scientists 2021, Oct 2021, Hong Kong, France. ⟨hal-04101626⟩
74 Consultations
42 Téléchargements

Partager

More