Assessment of Memory Cushions in Aircraft Seating for Injury Mitigation through Dynamic Impact Test
Bibliographic record
Abstract
Dynamic impact tests were conducted to assess the effectiveness of the Visco-Elastic Polyurethane (VEPU) memory foam seat cushions in mitigating impact to the occupant during an aircraft crash. A FAA specification Hybrid III crash dummy and seats with and without a stroke energy absorbing mechanism were used in the tests. Polyurethane foam (PU) cushions were also tested for comparison. The results with the rigid seat indicated that with 8.3 m/s impact, lumbar spine injury would occur. VEPU cushions reduced the lumbar force by up to 34%. With an impact speed of 6m/s, a VEPU cushion mitigated the impact to the tolerable level, whilst injury would still occur with the PU cushions. The results with the energy absorbing seats showed that with 8.3 m/s impact speed, the seat with over 125 mm (5 inch) stroke length is able to reduce the impact load below the injury threshold. A relatively softer VEPU cushion reduced the lumbar force by over 15% compared with the PU cushions. With a stoke length of 75 mm (3 inch), bottom-out occurred and occupant lumbar spine injury would occur. A relatively higher stiffness VEPU cushion reduced lumbar force by around 20%.
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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".