4.6 Article

Hot Deformation Behavior of Hastelloy C276 Alloy: Microstructural Variation and Constitutive Models

Journal

MATERIALS
Volume 16, Issue 18, Pages -

Publisher

MDPI
DOI: 10.3390/ma16186192

Keywords

Hastelloy C276 alloy; flow behavior; microstructural evolution; constitutive model

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Isothermal deformation experiments were conducted on Hastelloy C276 alloy to analyze its microstructural evolution mechanisms. The study revealed that the hot compression parameters had a significant impact on the alloy's microstructure variation features and flow behaviors. The strain rates influenced the strain hardening effects, while the compressed temperature affected the true stresses through the annihilation of substructures and dynamic recrystallization behaviors.
Isothermal deformation experiments of the Hastelloy C276 alloy were executed using the Gleeble-3500 hot simulator at a temperature range of 1000-1150 & DEG;C and a strain rate range of 0.01-10 s-1. Microstructural evolution mechanisms were analyzed via transmission electron microscope (TEM) and electron backscatter diffraction (EBSD). Results reveal that the influences of hot compression parameters on the microstructure variation features and flow behaviors of the Hastelloy C276 alloy were significant. The intense strain hardening (SH) effects caused by the accumulation of substructures were promoted when the strain rates were increased, and true stresses exhibited a notable increasing tendency. However, the apparent DRV effects caused by the annihilation of substructures and the increasingly dynamic recrystallization (DRX) behaviors occurred at high compressed temperature, inducing the reduction in true stresses. In addition, a physical-based (PB) constitutive model and a long short-term memory (LSTM) model optimized using the particle swarm optimization (PSO) algorithm were established to predict the flow behavior of Hastelloy C276 alloy. The smaller average absolute relative error and greater relation coefficient suggest that the LSTM model possesses a higher forecasting accuracy than the PB model.

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