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Record W4399843003 · doi:10.4050/f-0080-2024-0035

Impact of the Wind on the Hovering Performance of Stabilized Payload Lifting with a Single Tethered Fixed-Wing Aircraft

2024· article· en· W4399843003 on OpenAlexaff
Maxime Doguet, David Rancourt

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPayload (computing)Aerospace engineeringAirplaneFixed wingEngineeringMarine engineeringComputer scienceWing

Abstract

fetched live from OpenAlex

Over the last 90 years, many concepts of lifting payload with a single tethered fixed-wing aircraft have been proposed. In this concept, an airplane flies along a quasi-circular flight path and the payload should remain at the center of this circle. The main challenge encountered has been payload stability in hover (i.e., when the payload is fixed in space and the aircraft flies along a quasi-circular path above). In calm conditions, lengthening the tether to reach two or three kilometers (1.5 mile) has been proven to stabilize the payload in an orbit with a radius of the order of 1 meter (3 ft). However, the presence of wind has shown a drastic reduction in payload stability. At the end of the 1990s, a patent proposed to add a thruster-based stabilization device onto the payload but no further studies explored such a concept. This study proposes a new concept inspired by the former. The main difference lies in the addition of a reel-in mechanism to control and stabilize the payload in the vertical direction. This work analyzes the impact of the wind on this new concept in hover. The results have shown a maximum power requirement of 37 kW (60 hp) for the aircraft and 15 kW (20 hp) for the stabilization device to lift a 300 kg (660 lbm) payload fixed in the inertial frame with a 400 m (1,300 ft) long tether. This work has highlighted the high impact of the tether force on the towing airplane and therefore a means to reduce this impact is required.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.267

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 head0.008
GPT teacher head0.196
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 teacher head, 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

Citations0
Published2024
Admission routes1
Has abstractyes

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