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Record W1974254889 · doi:10.1115/imece2008-67103

Dynamic Stability Analysis of Aerial Refueling Hose/Drogue System by Finite Element Method

2008· article· en· W1974254889 on OpenAlexaff
Zheng Zhu, S. A. Meguid

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerospace Engineering and Control Systems
Canadian institutionsUniversity of TorontoYork University
Fundersnot available
KeywordsFinite element methodVortexWakeInstabilityAirflowPoint (geometry)Tension (geology)VibrationStability (learning theory)EngineeringStructural engineeringFlow (mathematics)Aerospace engineeringMechanicsMarine engineeringPhysicsAcousticsComputer scienceMechanical engineeringClassical mechanicsMathematics

Abstract

fetched live from OpenAlex

The present work investigates the effect of pertinent parameters such as the hose tension, tow point disturbance and vortex wake on the dynamic stability of the aerial refueling hose and drogue system by using the finite element method with an accurate and computationally efficient three-noded, curved beam element. The analysis results show that the conventional spectrum method is inappropriate for the dynamic stability analysis of the aerial refueling hose/drogue system. This is because the mechanism of instability due to the tow point disturbance is not the resonance of the refueling hose/drogue system but the wave propagation along the hose absorbing energy from the airflow as it travels downstream from the tow point, if the propagation speed is less than the airflow speed. The study also demonstrates that the vortex wake has a significant impact on the dynamics of the system. The short hose system will orbit with the vortex and the orbiting behavior will diminish as the hose length increases.

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)0.000
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.007
GPT teacher head0.211
Teacher spread0.204 · 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

Citations3
Published2008
Admission routes1
Has abstractyes

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