Design and fabrication of gradiently‐denitrated layer structure of seven‐hole gun propellant and its burning performance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Improving the progressive burning performance of gun propellant is an effective approach to increase the muzzle velocity of bullet. The seven‐hole gun propellant characterized by a perforated structure with progressive burning performance has a broad application in the field of medium and small caliber weapons. Therefore, researches aiming to improve its burning performance are indispensable. In this paper, a seven‐hole gun propellant with the gradiently‐denitrated layer structure (GDLS) that the energetic functional groups increased gradually from the surface to the inside was designed and fabricated. Theoretical calculation indicated that the nitrogen content of nitrocellulose in seven‐hole gun propellant has a positive relationship with the burning rate coefficient and impetus. The results of burning calculation showed that the progressive burning performance of seven‐hole gun propellant were improved with the thickness of GDLS increases or the burning rate coefficient of the surface decreases. Moreover, the seven‐hole gun propellant with GDLS was successfully prepared, named gradiently denitrated seven‐hole gun propellant (GDSGP), which was proved by the results of FT‐IR, Raman and SEM. The different denitration conditions enabled the GDSGP with a good progressive burning performance, as confirmed by closed bomb test. Furthermore, the progressive burning performance of GDSGP increased first and then decreased with extending the denitration time. On the basis of design and study of GDSGP, the control and optimization of the burning performance of GDSGP will be more accurate in practical applications.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it