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...

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Principais autores:	Hari Singh, Dola Sundeep, C. Chandrasekhara Sastry, Eswaramoorthy K Varadharaj
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Nature Portfolio 2025-07-01
coleção:	Scientific Reports
Assuntos:	IS 2062 steel Double-base propellant Material degradation Machine learning High-temperature combustion
Acesso em linha:	https://doi.org/10.1038/s41598-025-10033-x
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