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

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 metal...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Journal of materials engineering and performance Ročník 31; číslo 12; s. 10237 - 10247
Hlavní autori: Cao, Yuan, Cao, Jianguo, Wang, Leilei, Song, Chunning, Li, Fang, Zhang, Pengfei
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.12.2022
Predmet:
ISSN:1059-9495, 1544-1024
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí: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 ( R 2 ) 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.
ISSN:1059-9495
1544-1024
DOI:10.1007/s11665-022-06987-y