Computational Method for Calculation of Blast Pressure outside Vented Suppressive Shield Containers
Bibliographic record
Abstract
Vented suppressive shield (VSS) containers have traditionally been used to store hazardous materials, especially explosives, and to attenuate the blast pressure and impulse outside the shield. VSS containers also eliminate the primary fragment hazard associated with accidental explosions. Most VSS containers are designed from experience and observations of container test programs. This design process, however, limits the designer's ability to economize on materials or use suppressive shield configurations other than those used in the test programs. The aim of this study is to investigate the interaction between the blast waves and the structural steel elements used in VSSs. This paper investigates the effect of different VSS sections (configurations) in the attenuation of blast pressure outside the container and develops semiempirical equations that can be used to predict blast pressure and impulse outside VSS containers. AUTODYN, a commercial software package, was used to model the explosive detonation process and the evolution of the blast wave and its interaction with the VSS. Different VSS configurations, which ranged in complexity and included single- and multilayer shields, were studied. The single- and multilayer VSSs were compared and used to develop semiempirical equations to predict the pressure and impulse outside the VSS container. The proposed equations were compared with the results obtained from a previous experimental test program and showed a very good correlation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".