Development and Flight Demonstration of An Active Seat Mount System for Aircrew Whole-Body Vibration Mitigation on NRC Bell-412 Helicopter
Bibliographic record
Abstract
Helicopter aircrew are exposed to high levels of whole-body vibration (WBV) in fight operations, which may degrade their ride comfort and performance in the short-term, and contribute to some health issues in the long-term. This paper presents the latest development and flight test demonstration results of an active seat mount system that is designed to reduce helicopter aircrew WBV levels through active cancellation of the N/rev vibration peaks related to the helicopter main rotor speed. A prototype airworthy hardware of the active seat mount system has been developed based on previous bench-top-test designs to meet airframe integrity requirements for installation and flight testing on the Bell-412 helicopter. Extensive experimental results on human occupants using a shaker table facility and flight demonstrations on the NRC Bell-412 helicopter in representative flight conditions are presented and discussed. The active seat mount system has achieved significant reduction to the occupant WBV levels at the bottom seat cushion interface per ISO2631/MIL-STD-1472G metrics, and also showed effective mitigation to the occupant head vibrations. These investigations demonstrate that the active seat mount technology is a feasible solution for helicopter aircrew WBV mitigation.
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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 | 0.000 |
| 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) | 0.002 | 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".