Development and Testing of Advanced Cork Composite Sandwiches for Energy-Absorbing Structures
Bibliographic record
Abstract
Cork is a sustainable material with remarkable properties. In addition to its main application as wine stoppers, it has also been employed as a sound and thermal insulator in facades, building roofs, aeronautical applications, and, more recently, in impact energy absorption systems. In its natural form, cork is mainly used in wine stopper manufacturing, but for other applications, cork compounds are usually employed, which makes it possible to manufacture complex geometries with nearly isotropic behavior. In this work, an attempt was made to merge the desirable properties of two different cork materials (agglomerated and expanded black) into cork composite sandwich structures. These structures were tested according to impact conditions typically experienced by energy-absorbing liners used in personal safety devices. Additionally, the performance dependency on the working temperature was analyzed. The sole black, expanded cork (EC159) and agglomerated cork (AC199A and AC216) were tested in 500 J impacts. It was found that black cork was characterized by superior thermal stability, while expanded cork allowed absorbing high energies. In the second stage, the composites consisting of both tested materials were tested in 100 J impact scenarios. The combination of two materials of different properties enabled reduction of the peak force exerted on a helmet user's head during the impact by about 10% compared to agglomerated specimens. Additionally, it was proved that there was no influence of the glue used to join different cork types.
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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) | 0.001 | 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".