Characterization of PAX‐21 Insensitive Munition Detonation Residues
Bibliographic record
Abstract
Abstract Insensitive high explosives are being used in military munitions to counteract unintended detonations during storage and transportation. These formulations contain compounds such as 2,4‐dinitroanisole (DNAN) and 3‐nitro‐1,2,4‐triazol‐5‐one (NTO), which are less sensitive to shock and heat than conventional explosives. We conducted a series of four tests on snow‐covered ice utilizing 60‐mm mortar cartridges filled with 358 g of PAX‐21, a mixture of RDX, DNAN, and ammonium perchlorate. Rounds were detonated high‐ and low‐order using a fuze simulator to initiate detonation. Blow‐in‐place (BIP) operations were conducted on fuzed rounds using an external donor charge or a shaped‐charge initiator. Results indicate that 0.001 % of the original mass of RDX and DNAN were deposited during high‐order detonations, but up to 28 % of the perchlorate remained. For the donor block BIPs, 1 % of the RDX and DNAN remained. Residues masses for these operations were significantly higher than for conventional munitions. Low‐order detonations deposited 10–15 % of their original explosive filler in friable chunks up to 5.2 g in mass. Shaped‐charge BIPs scattered 15 % of the filler and produced chunks up to 15 g. Ammonium perchlorate residue masses were extremely high because of the presence of large AP crystals, up to 400 μm in the recovered particles.
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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 | 0.000 | 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) | 0.001 | 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".