MétaCan
Menu
Back to cohort
Record W7132069684

Development of a multi-axis active seat mount system for helicopter aircrew whole-body vibration reduction

2019· article· en· W7132069684 on OpenAlexvenueno aff
J. F. Chang, A. Fereidooni, V. Wickramasinghe, Y. B. Chen

Bibliographic record

VenueNPARC · 2019
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsnot available
Fundersnot available
KeywordsAircrewVibrationMountActuatorShakerFrame (networking)Car seat
DOInot available

Abstract

fetched live from OpenAlex

This paper presents the development and evaluation of a proof-of-concept multi-axis and actively controlled helicopter seat mount system for aircrew whole-body vibration reduction. The multi-axis seat mount is designed to be installed between the helicopter seat floor and the seat supporting structure to minimize the impact on crashworthiness requirements of the helicopter seat. The design involves multiple miniature force actuators to counteract the vibrations of the seat frame and occupant transmitted from the helicopter floor in three orthogonal directions. The actuators are controlled by an adaptive feedforward filtered-x least mean square algorithm to cancel the helicopter floor vibration input. The prototype active seat mount design was tested in various configurations with a shaker table providing representative Bell-412 helicopter vibration inputs. Test results demonstrated that the vibrations of the seat frame and mannequin occupant body were suppressed simultaneously, and the major N/rev harmonic peaks of the occupant's whole-body vibration were reduced by 95%. This demonstrated that the multi-axis active seat mount design can mitigate the whole-body vibration exposure of the helicopter aircrew to improve their ride quality and reduce adverse health effect.

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 score0.062
Threshold uncertainty score0.476

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)0.0000.000

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 head0.024
GPT teacher head0.313
Teacher spread0.289 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueNPARCSame topicEffects of Vibration on HealthFrench-language works237,207