Predicting the multiaxial stress-strain behavior of polyethylene terephthalate (PET) at different strain rates and temperatures above Tg by using an Artificial Neural Network-Reference-Cited by-同舟云学术

Predicting the multiaxial stress-strain behavior of polyethylene terephthalate (PET) at different strain rates and temperatures above Tg by using an Artificial Neural Network

Published:2022-02 Issue: Volume:165 Page:104175
ISSN:0167-6636
Container-title:Mechanics of Materials
language:en
Short-container-title:Mechanics of Materials

Author:

Teng Fei,Menary Gary,Malinov Savko,Yan Shiyong,Stevens John Boyet^ORCID

Funder

Queen's University

China Scholarship Council

Publisher

Elsevier BV

Subject

Mechanics of Materials,General Materials Science,Instrumentation

Reference50 articles.

1. Biaxial hot drawing of poly(ethylene terephthalate): measurements and modelling of strain-stiffening;Adams;Polymer,2000

2. Fatigue life prediction of unidirectional glass fiber/epoxy composite laminae using neural networks;Al-Assaf;Compos. Struct.,2001

3. Prediction of nonlinear viscoelastic behavior of polymeric composites using an artificial neural network;Al-Haik;Int. J. Plast.,2006

4. Application of artificial neural networks in micromechanics for polycrystalline metals;Ali;Int. J. Plast.,2019

5. A theory for the low-temperature plastic deformation of glassy polymers;Argon;Philos. Mag. A,1973

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