Development of adaptive helicopter seat systems for aircrew vibration mitigation
Bibliographic record
Abstract
Helicopter aircrews are exposed to high levels of whole body vibration during flight. This paper presents the results of an investigation of adaptive seat mount approaches to reduce helicopter aircrew whole body vibration levels. A flight test was conducted on a four-blade helicopter and showed that the currently used passive seat systems were not able to provide satisfactory protection to the helicopter aircrew in both front-back and vertical directions. Long-term exposure to the measured whole body vibration environment may cause occupational health issues such as spine and neck strain injuries for aircrew. In order to address this issue, a novel adaptive seat mount concept was developed to mitigate the vibration levels transmitted to the aircrew body. For proof-of-concept demonstration, a miniature modal shaker was properly aligned between the cabin floor and the seat frame to provide adaptive actuation authority. Adaptive control laws were developed to reduce the vibration transmitted to the aircrew body, especially the helmet location in order to minimize neck and spine injuries. Closed-loop control test have been conducted on a full-scale helicopter seat with a mannequin configuration and a large mechanical shaker was used to provide representative helicopter vibration profiles to the seat frame. Significant vibration reductions to the vertical and front-back vibration modes have been achieved simultaneously, which verified the technical readiness of the adaptive mount approach for full-scale flight test on the vehicle.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".