Prediction of the flow behaviour of AISI 321 austenitic stainless steel during dynamic recovery using sine hyperbolic constitutive equation and artificial neural network-Reference-Cited by-同舟云学术

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Prediction of the flow behaviour of AISI 321 austenitic stainless steel during dynamic recovery using sine hyperbolic constitutive equation and artificial neural network

Published:2024-08-21 Issue: Volume: Page:1-16
ISSN:0008-4433
Container-title:Canadian Metallurgical Quarterly
language:en
Short-container-title:Canadian Metallurgical Quarterly

Author:

Ghazani Mehdi Shaban¹^ORCID,Vajd Akbar²,Hosseinnejad Keyhan³

Affiliation:

1. Department of Materials Science Engineering, University of Bonab, Bonab, Iran

2. Department of Materials Science Engineering, Technical and Vocational University (TVU), Tehran, Iran

3. Department of Materials Science Engineering, Sahand University of Technology, Tabriz, Iran

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/00084433.2024.2393026

Reference42 articles.

1. Development of hot rolled steel sheet with 600MPa UTS for automotive wheel application

2. Processing of ultra low carbon steels with mechanical properties adequate for automotive applications in the as-annealed condition

3. Application of neural-network for improving accuracy of roll-force model in hot-rolling mill

4. A study on on-line learning neural network for prediction for rolling force in hot-rolling mill

5. Constitutive analysis in hot working

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