A Wingspan Design Study of a Small Solar-Powered UAV
Bibliographic record
Abstract
A wingspan design study was performed to determine the influence of changing the wingspan and the weight of a small solar-powered UAV on the flight range. With an increasing wingspan, the area available for a solar array also grows and the optimum battery pack capacity will change. Both parameters affect the weight of the aircraft. This paper aims to determine the wingspan and battery configuration that maximizes the range of a fixed-wing solar-powered UAV that is flying from sunrise to sunset throughout the year in Southern Ontario, Canada. A design model was used to size the wing based on solar array size, as well as calculate the weight of the aircraft with a changing wingspan and battery pack configuration. A simple aerodynamic analysis was performed for each aircraft to determine the aerodynamic performance and optimum airspeed for maximum range considering the battery pack and solar energy available, while excluding the payload requirements. A range analysis was conducted to determine the maximum range capable for each configuration. Overall, an aircraft wingspan between 2-4 m with a high capacity battery pack has the longest range, with the optimum configuration depending on the flight location and date.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".