Impact Attenuation Characteristics of Thin Walled Collapsible Air Chambers for Use in Protective Helmets
Bibliographic record
Abstract
Abstract For the past 40 years, helmets have primarily used expanded polystyrene, vinyl nitrile, and expanded polypropylene foams for impact attenuation. Even though the packaging industry has investigated a variety of structures for impact management, the helmet industry has been slow to adopt these types of innovations. More recently, engineered structures have been developed and introduced for use in the helmet industry. This study was intended to describe the impact characteristics of a thin walled collapsible air chambers designed to be used in sport helmets. This study investigated three structures: rigid walls, a chamber with rigid walls and a vent, and a chamber with rigid walls and no vent. Each structure was impacted with a 5 kg weight at three velocities: 1.9, 2.8, and 3.4 m/s. The three structures were also made using two materials of different stiffnesses. Analysis of the results revealed that the effect of the walls, vent, and material stiffness interacted to produce effective energy management. The results demonstrated that by changing the material stiffness, wall thickness, and vent diameter the performance of the chambers can be engineered to effectively manage different levels of energy.
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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 | 0.001 |
| 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) | 0.001 | 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".