Constitutive modelling and microstructural analysis of 92W-5Co-3Ni alloy subjected to high strain rate testing at elevated temperatures

The mechanical response of 92 W-5Co-3Ni alloy was analysed at dynamic strain rates ranging from 1800 s−1 to 4200 s−1 and temperatures from 323 K to 873 K. The marginal strain hardening, followed by significant strain softening, was seen in flow stress behaviour. The rise in the yield strength at roo...

Full description

Saved in:
Bibliographic Details
Main Authors: Suswanth Poluru, Aarjoo Jaimin, Nitin R. Kotkunde, Swadesh Kumar Singh, Amit Kumar, Ashutosh Panchal, Prabhu Gnanasambandam
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Materials & Design
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S0264127525004551
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The mechanical response of 92 W-5Co-3Ni alloy was analysed at dynamic strain rates ranging from 1800 s−1 to 4200 s−1 and temperatures from 323 K to 873 K. The marginal strain hardening, followed by significant strain softening, was seen in flow stress behaviour. The rise in the yield strength at room temperature and higher strain rates was mainly due to the increased fraction of low-angle grain boundaries and kernel average misorientation. The severe elongation of tungsten grains was noticed for all strain rates. The Adiabatic Shear Bands (ASBs) were noticed above strain rates of 2700 s−1 with an average shear band’s width of 45 µm. Moreover, the average size of the ASB shear band’s width was reduced to 30 µm for higher strain rates (4200 s−1), which exhibited the enhancement of the self-sharpening capacity of the kinetic energy penetrator. Subsequently, the Arrhenius constitutive model and machine-learning-based Random Forest model (RF) were developed to predict flow stress. The Arrhenius model accurately predicted the flow stress behaviour with a correlation coefficient (R) of 0.9766 and an average absolute error (AARE) of 2.033 %. However, the RF model demonstrated the best prediction of flow stress behaviour with an R of 0.9912 and an AARE of 1.145 %.
ISSN:0264-1275