ArticleScientific reports2025
Experimental and machine learning-driven assessment of IS 2062 steel under double-base propellant combustion conditions.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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 combustion, providing insights into material resilience, oxidation, and erosion trends. A series of seven static firing tests were conducted with varying nozzle throat diameters, systematically analyzing chamber pressure, burn rates, and structural integrity. The optimal test, Test-06achieved stable combustion with an average chamber pressure of 313 ksc and a burn rate of 36-37 mm/s, demonstrating minimal material degradation. Conversely, Test-07 exceeded 355-372 ksc with burn rates surpassing 41 mm/s, exhibiting erosive burning and accelerated steel erosion.Material characterization techniques, including X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), Raman Spectroscopy, Field Emission Scanning Electron Microscopy (FESEM), and Energy Dispersive Spectroscopy (EDS), revealed significant oxidation, scale formation, and localized surface degradation, in high-temperature regions around 2500 Kelvinat the nozzle throat inducing structural changes. To enhance predictive accuracy, machine learning models Linear Regression, Random Forest Regression, Support Vector Machines (SVM), K-Means Clustering, and Artificial Neural Networks (ANN) were employed to analyze combustion-induced degradation trends, confirming Test-06 as the optimal balance of stability and high performance. Findings emphasize that while IS 2062 steel maintains integrity under transient high-temperature exposure, prolonged operation may lead to thermal fatigue and microstructural weakening, necessitating protective coatings or alternative alloy compositions for long-term durability. This study contributes to improving material selection, structural design, and predictive modeling for defence propulsion systems.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.