Aluminum Foam-Lined Suppressive Shields for Safe Transport of Explosives
Bibliographic record
Abstract
The manufacture, transportation, and storage of explosives in Canada and around the world pose serious challenges to explosives regulators and inspectors tasked with ensuring the safety of nearby populations. Explosives are routinely transported through, and manufacturing and storage facilities are often located close to, populated areas and traffic routes. This proximity increases the risk of severe casualties and infrastructure damage if there is an accidental or deliberate explosion. Even though an explosion is unlikely, the consequences can be severe. Several accidents that have involved explosives are discussed in the literature. These accidents highlight the devastation likely to result from an explosion and underscore the importance of finding cost-effective solutions to mitigate the effects on the population and infrastructure. This paper presents a research program designed to investigate the effectiveness of suppressive shield containers in reducing the blast pressure outside the container and eliminating fragment hazards from an explosion. Several types of suppressive shield panels, including panels lined with aluminum foam, were tested in a blast chamber. The results show reduced peak blast pressure outside the container by as much as 60% and in the incident impulse by about 58%. When the suppressive shield was lined with aluminum foam, a further reduction in peak incident pressure (up to 80%) was achieved.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.002 | 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".