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Record W2038375481 · doi:10.1115/1.2957599

Modeling Helicopter Blade Sailing: Dynamic Formulation and Validation

2008· article· en· W2038375481 on OpenAlexaff
Alanna Wall, Fred F. Afagh, Robert Langlois, S.J. Zan

Bibliographic record

VenueJournal of Applied Mechanics · 2008
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsNational Research Council CanadaCarleton University
Fundersnot available
KeywordsHelicopter rotorBlade element theoryAerodynamicsBlade (archaeology)Deflection (physics)Rotor (electric)Computer scienceAerospace engineeringEngineeringStructural engineeringMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

Rotor blade sailing, which is characterized by excessive deflection of rotor blades, can be experienced by shipboard helicopters during rotor start-up and shut-down. In an attempt to model the complete ship-helicopter-rotor system in a way that is geometrically representative and computationally efficient, the system was represented as a discrete-property rigid-body and flexible-element system capable of simulating many important dynamic effects that contribute to the motion of rotor blades. This paper describes the model in detail and discusses validation cases. While both dynamic effects and aerodynamic effects are believed to be important components of blade sailing, this paper focuses exclusively on the dynamics. The validation cases discussed herein suggest that the modeling approach presented offers excellent potential for efficiently modeling blade sailing and other blade motion phenomena.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.010
GPT teacher head0.198
Teacher spread0.188 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations10
Published2008
Admission routes1
Has abstractyes

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