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Artificial Neural Network: Artificial Neural Network Approach to Predict the Elastic Modulus from Dynamic Mechanical Analysis Results (Adv. Theory Simul. 4/2019)
Author(s) -
Xu Xianbo,
Gupta Nikhil
Publication year - 2019
Publication title -
advanced theory and simulations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.068
H-Index - 17
ISSN - 2513-0390
DOI - 10.1002/adts.201970011
Subject(s) - artificial neural network , viscoelasticity , elastic modulus , materials science , modulus , dynamic mechanical analysis , dynamic modulus , range (aeronautics) , ultimate tensile strength , composite material , structural engineering , computer science , artificial intelligence , engineering , polymer
In article number 1800131, Xianbo Xu and Nikhil Gupta report on combining an artificial neural network and viscoelastic theory to recover the elastic modulus of graphene‐reinforced composites from dynamic mechanical analysis results. Instead of conducting numerous tensile tests, the method can predict the elastic modulus over a range of strain rates and temperatures from a single specimen.