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Record W2533648150 · doi:10.1017/s0001924000010162

Horizontal flight trajectories optimisation for commercial aircraft through a flight management system

2014· article· en· W2533648150 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Aeronautical Journal · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced Aircraft Design and Technologies
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsCruiseReduction (mathematics)Fuel efficiencyEnvironmental scienceAtmosphere (unit)AeronauticsAutomotive engineeringTrajectoryFlight simulatorComputer scienceAerospace engineeringMeteorologySimulationEngineeringMathematics

Abstract

fetched live from OpenAlex

Abstract To reduce aircraft emissions to the atmosphere, the fuel burn from aircraft has to be reduced. For long flights, the cruise is the phase where the most significant reduction can be obtained. A new horizontal profile optimisation methodology to achieve lower emissions is described in this article. The impact of wind during a flight can reduce the flight time, either by taking advantage of tailwinds or by avoiding headwinds. A set of alternative trajectories are evaluated to determine the quickest flight time, and therefore, the lowest fuel burn. To determine the expected amount of fuel reduction, the performance databases used on actual FMS devices, were used. These databases represent the flight performance of commercial aircraft.

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.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.896
Threshold uncertainty score0.532

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.243
Teacher spread0.228 · 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