Prediction of mechanical properties of superplastic Inconel*718 using artificial neural networks

Y Huang; Paul Blackwell

doi:10.1179/026708302225006016

Prediction of mechanical properties of superplastic Inconel*718 using artificial neural networks

Y Huang, Paul Blackwell

Research output: Contribution to journal › Article › peer-review

10 Citations (Scopus)

Abstract

This paper examines the application of artificial neural networks (ANNs) in materials science and explains the process of using an ANN to develop a constitutive relationship for the widely used nickel based superalloy Inconel 718 (IN718) in the temperature range 950-980°C with strain rates of 10-4 and 10-3 s-1. These parameters are relevant to the high temperature forming of IN718 sheet. The mathematical form of the constitutive relationship derived is given and practical applications of its use are discussed.

Original language	English
Pages (from-to)	1104-1108
Number of pages	5
Journal	Materials Science and Technology (United Kingdom)
Volume	18
Issue number	10
DOIs	https://doi.org/10.1179/026708302225006016
Publication status	Published - 30 Oct 2002

Keywords

mechanical properties
artificial neural networks
superplastic Inconel* 718

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abstract = "This paper examines the application of artificial neural networks (ANNs) in materials science and explains the process of using an ANN to develop a constitutive relationship for the widely used nickel based superalloy Inconel 718 (IN718) in the temperature range 950-980°C with strain rates of 10-4 and 10-3 s-1. These parameters are relevant to the high temperature forming of IN718 sheet. The mathematical form of the constitutive relationship derived is given and practical applications of its use are discussed.",

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AB - This paper examines the application of artificial neural networks (ANNs) in materials science and explains the process of using an ANN to develop a constitutive relationship for the widely used nickel based superalloy Inconel 718 (IN718) in the temperature range 950-980°C with strain rates of 10-4 and 10-3 s-1. These parameters are relevant to the high temperature forming of IN718 sheet. The mathematical form of the constitutive relationship derived is given and practical applications of its use are discussed.

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KW - artificial neural networks

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