Climb, Cruise and Descent 3D Trajectory Optimization Algorithm for a Flight Management System
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.
Bibliographic record
Abstract
Global warming is one of the major issues in the Earth today. Many studies are intended to reduce aircraft’s fuel consumption to minimize aviation’s footprint. This article presents the combination between two different trajectories’ optimization types: one optimizing the vertical navigation profile, and the other optimizing the lateral navigation profile. The aircraft model is obtained from a performance database, which offers an improved precision over aircraft modeled trough equations of motion, constantly used on the literature. The calculation of the optimal trajectory is obtained by implementing dynamic weather information. The VNAV algorithm calculates the optimal altitudes, speeds and step climbs to reduce fuel consumption, while the LNAV algorithm searches for alternative horizontal trajectories. The aircraft takes advantage of tail winds and avoids head winds. The results were compared with real flight information, and the fuel burn reduction obtained is encouraging.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it