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Record W2316567628 · doi:10.2514/6.2014-2291

Construction of an aircraft's VNAV flight envelope for in-FMS flight trajectory computation and optimization

2014· article· en· W2316567628 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

Venue14th AIAA Aviation Technology, Integration, and Operations Conference · 2014
Typearticle
Languageen
FieldEngineering
TopicAir Traffic Management and Optimization
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsAerospace engineeringTrajectoryAeronauticsTrajectory optimizationEnvelope (radar)Flight management systemFlight simulatorFlight envelopeComputer scienceComputationEngineeringAerodynamicsPhysicsRadarAlgorithm

Abstract

fetched live from OpenAlex

This paper presents the results of a new method used for constructing an aircraft’s vertical navigation profile (VNAV) envelope, applied on an aircraft performance model described by linear interpolation tables. The method was developed for use in Flight Management System (FMS) trajectory computations and optimization. The main objective was to speed-up the trajectory generation/update and to reduce the volume of repetitive computations, especially those associated with a trajectory optimization. It considers a free-flight scenario with a vertical profile composed of unrestricted climb, constant-speed level flight, climb-in-cruise (no descentin-cruise) and continuous descent segments, at specified climb, cruise and descent speed schedules and a specified value of the air temperature deviation. It uses the same set of aircraft performance data (PDBs) as the FMS platforms.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.699
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.210
Teacher spread0.203 · 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