SHARCS Project: Modal Parameters Identification of Smart Spring/Helicopter Blade System
Bibliographic record
Abstract
It is expected that the next generation of helicopters will incorporate active control devices to suppress noise and vibration, One of the most advanced active control techniques to attenuate noise and vibration in helicopters is called individual blade control (IBC). Each blade is individually commanded independently of its azimuth angle. In the past, IBC was not fully developed, due to the lack of actuators able to withstand the loads that characterize the helicopter rotor environment. Among the new solutions to achieve efficient IBC, the ones that involve solid-state actuators or "smart" structures, are seen as the most promising. The Smart Hybrid Active Rotor Control System (SHARCS) project is expected to demonstrate the ability of smart structure systems, employing multiple active material actuators, sensors and closed-loop controllers, to reduce both vibration and noise in rotorcraft. To assess the capabilities of the smart spring actuator to attenuate vibrations, a prototype of the system is investigated. Before testing the SHARCS system in operative conditions, the characterization of the dynamic properties of the Smart Spring installed on a non rotating helicopter blade are analyzed. The effects of the Smart Spring actuator on the modal properties are studied through experimental investigations carried out at Carleton University. The capability of the Smart Spring to change the dynamic behavior of an actual helicopter blade is demonstrated by analyzing the shifts in the modal parameters. Finally, the modal properties of the blade predicted by a finite element model will be correlated with those experimentally estimated. Copyright © 2006 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.
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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 | 0.000 | 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) | 0.000 | 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".