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Journal of Materials Engineering and Performance

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19.05.2022 | Technical Article

High-Temperature Deformation Constitutive Model of Zircaloy-4 Based on the Support Vector Regression Algorithm during Hot Rolling

verfasst von: Yuan Cao, Jianguo Cao, Leilei Wang, Chunning Song, Fang Li, Pengfei Zhang

Erschienen in: Journal of Materials Engineering and Performance | Ausgabe 12/2022

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Abstract

Due to the small range of plastic deformation temperatures during hot rolling of Zircaloy-4 plates, it is important to determine the appropriate flow behaviors for plate profile control of Zircaloy-4 plates. The developed microstructures and mechanical properties of Zircaloy-4 are evaluated by metallographic observations and Gleeble-3800 thermal simulation tester. To meet the need of data with small-sample properties, the support vector regression (SVR) algorithm is adopted to predict the constitutive model of Zircaloy-4, and the improved particle swarm optimization algorithm (IPSO) is used to optimize parameters of SVR algorithm. Meanwhile, results indicate that the correlation coefficient (R²) value of zirconium alloy constitutive model is 96.805%. Based on employed algorithm, comparing with modified Arrhenius model, the results show the superiority of IPSO-SVR algorithm. This provides an important theoretical basis for FE simulation of controlling the Zircaloy-4 plate shape during hot rolling process.

Vorheriger Artikel Effect of Cooling Rate and Coiling Temperature on Microstructure and Precipitation Behavior of a 700 MPa Weathering Steel

Nächster Artikel A New Dominance Distribution Method to Select Materials with Higher Fatigue Resistance under Property Scatter and Load Uncertainty

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Titel: High-Temperature Deformation Constitutive Model of Zircaloy-4 Based on the Support Vector Regression Algorithm during Hot Rolling
verfasst von: Yuan Cao
Jianguo Cao
Leilei Wang
Chunning Song
Fang Li
Pengfei Zhang
Publikationsdatum: 19.05.2022
Verlag: Springer US
Erschienen in: Journal of Materials Engineering and Performance / Ausgabe 12/2022
Print ISSN: 1059-9495
Elektronische ISSN: 1544-1024
DOI: https://doi.org/10.1007/s11665-022-06987-y

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