Experimental and machine learning-driven assessment of IS 2062 steel under double-base propellant combustion conditions
- DOI
- 10.1038/s41598-025-10033-x
- Published
- 2025-07-03
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-025-10033-x,
title = {Experimental and machine learning-driven assessment of IS 2062 steel under double-base propellant combustion conditions},
author = {Hari Singh and Dola Sundeep and C. Chandrasekhara Sastry and Eswaramoorthy K Varadharaj},
year = {2025},
journal = {Scientific Reports},
doi = {10.1038/s41598-025-10033-x},
url = {https://doi.org/10.1038/s41598-025-10033-x}
}RIS
TY - JOUR TI - Experimental and machine learning-driven assessment of IS 2062 steel under double-base propellant combustion conditions AU - Hari Singh AU - Dola Sundeep AU - C. Chandrasekhara Sastry AU - Eswaramoorthy K Varadharaj PY - 2025 JO - Scientific Reports DO - 10.1038/s41598-025-10033-x UR - https://doi.org/10.1038/s41598-025-10033-x ER -
APA
Singh, H., Sundeep, D., Sastry, C. C., & Varadharaj, E. K. (2025). Experimental and machine learning-driven assessment of IS 2062 steel under double-base propellant combustion conditions. Scientific Reports. https://doi.org/10.1038/s41598-025-10033-x
Source records
- crossref · retrieved 2026-09-26T07:10:49.154Z