Experimental and machine learning-driven assessment of IS 2062 steel under double-base propellant combustion conditions

Experimental and machine learning-driven assessment of IS 2062 steel under double-base propellant combustion conditions

Abstract The degradation behavior of IS 2062 structural steel under extreme combustion conditions induced by double-base propellant exposure is crucial for aerospace and defense applications.This study addresses in understanding steel performance under high-temperature, short-duration rocket motor c...

Full description

Saved in:
Bibliographic Details
Main Authors: Hari Singh, Dola Sundeep, C. Chandrasekhara Sastry, Eswaramoorthy K Varadharaj
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
IS 2062 steel
Double-base propellant
Material degradation
Machine learning
High-temperature combustion
Online Access:https://doi.org/10.1038/s41598-025-10033-x
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-10033-x

Similar Items