Aircraft Vertical Route Optimization by Beam Search and Initial Search Space Reduction
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
This paper describes an optimization algorithm that provides an economical vertical navigation profile by finding the combinations of climb, cruise, and descent speeds, as well as altitudes, for an aircraft to minimize flight costs. The computational algorithm takes advantage of a space search reduction methodology to reduce the initial number of available speed and altitude combinations. The optimal solution was found by implementing the beam search algorithm. A bounding function that correctly estimates the flight cost by considering step climbs was developed to reduce the number of calculations required by the beam search algorithm. The full-flight fuel burn cost was obtained using a performance database-based method. The algorithm uses a numerical performance model instead of equations of motion to compute fuel burn. The database was developed by using flight experimental data. To validate the algorithm, its results were compared to those of three other algorithms: an exhaustive search, beam search, and search space reduction. The solution provided by the algorithm was also compared to the solution provided by a flight management system. Following this comparison, the algorithm systematically found the optimal solutions, which were better in terms of flight cost than those provided by the flight management system.
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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 | 0.001 | 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 | 0.002 |
| 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