MétaCan
Menu
Back to cohort
Record W2733805579 · doi:10.4050/f-0071-2015-10151

Development of a Magneto-Rheological Fluid-Based Trim Actuator with Active Tactile Cueing Capabilities

2015· article· en· W2733805579 on OpenAlexaff
Guifré Julió, Geoffrey Latham, Jean‐Sébastien Plante

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsBell Helicopter Textron (Canada)
Fundersnot available
KeywordsActuatorTrimMagnetorheological fluidMagnetoRheologyComputer scienceMechanical engineeringMaterials scienceControl engineeringEngineeringArtificial intelligenceMagnetComposite material

Abstract

fetched live from OpenAlex

A magneto-rheological (MR) fluid-based trim actuator is being developed for rotorcraft applications. The device can provide active tactile cues to the pilot in the form of infinitely variable force gradients, stick shaking, and soft stops. Tactile cueing has proved to be an effective method of increasing situational awareness, especially during emergency situations and can reduce pilot workload for increased operational safety. The MR actuator uses magneto-rheological fluid to permit variable slippage between rotating clutch surfaces. With an MR fluid, the torque transfer between the clutch surfaces is dependent upon a user controlled magnetic field that is used to modulate output forces applied to control linkages. This paper discusses the design of the MR trim actuator and the control logic used to implement active tactile cueing. The latest experimental results on a single axis test bench are presented and discussed. The prototype work shows that MR technology can provide broad tactile cueing functionality with size and weight similar to conventional trim actuators found on light aircraft that lack tactile cueing functions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.195
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.021
GPT teacher head0.212
Teacher spread0.191 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2015
Admission routes1
Has abstractyes

Explore more

Same topicVibration Control and Rheological FluidsFrench-language works237,207