kong-applicationofconstitutiveand-1999.pdf (1.15 MB)
The application of constitutive and artificial neural network models to predict the hot strength of steels
journal contribution
posted on 1999-10-01, 00:00 authored by Lingxue KongLingxue Kong, Peter HodgsonPeter HodgsonMany constitutive models have been successfully used to interpolatively and extrapolatively predict the hot strength of metal materials and artificial neural network (ANN) models have recently appeared to be an alternative for constitutive modelling due to the strong capability of the ANN in predicting and correlating nonlinear relationship between inputs and outputs. In this work, the constitutive and ANN models will initially be used to predict the complex stress strain behaviours of an austenitic steel with carbon content ranging from 0.0037 to 0.79 wt%. Due to the limitations of the models and the complexity of the material properties, both the constitutive and ANN models cannot accurately predict the effect of chemical composition. As both models have their advantages, the integration of constitutive and ANN models significantly improves the prediction accuracy and the complex influence of the chemical composition is more accurately predicted.
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Journal
ISIJ InternationalVolume
39Issue
10Pagination
991 - 998Publisher
Iron and Steel Institute of Japan (ISIJ), Nippon Tekko KyokaiLocation
Tokyo, Japan.Publisher DOI
ISSN
0915-1559Language
engPublication classification
C1.1 Refereed article in a scholarly journalCopyright notice
1999, Iron and Steel Institute of JapanUsage metrics
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