PLATE DENT TESTS AND SEDIMENTATION OF PARTICLES IN MELT-CAST EXPLOSIVES
Bibliographic record
Abstract
A short experimental study demonstrated that the plate dent test is very sensitive to the last few centimeters of explosives at the bottom of the cylinders. The tests were performed by simply detonating an explosive cylinder with a small thickness (12.7−25.4 mm) of a different explosive (faster, slower, inert) at the bottom. The study will present how those small thicknesses influence the dent depth and hence the reported performance. Cylinders of explosives were cast and then cut to determine the extent of sedimentation of the HMX particles. Densities were taken at various places and concentrations of HMX were extrapolated from those. It was found that there was a difference of 22% in the percentage of HMX from the bottom and the top of the cylinder (66% vs. 44%; theoretical average was 52.8%). The explosive at the bottom was then significantly different and more powerful than the one at the top. The study will also demonstrate how the situation can be worse in real artillery shells. Given the results of the plate dent experiments reported before, it will be demonstrated how in theory one could be misled on the plate dent test by letting particles settle. Simple precautions can be taken to eliminate this variable and to ensure that the results of the plate dent test are meaningful. It also serves as a reminder that the composite explosives that we test, especially the melt-cast explosives, have large variations in their composition from sample to sample.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".