Design, Challenges, and Innovations of the CREATeV Solar-Powered UAV
Bibliographic record
Abstract
The Clean Renewable Energy Aerial Test Vehicle (CREATeV) project has been the focus of the Applied Aerodynamics Laboratory of Flight (AALF) at Toronto Metropolitan University since 2017. This initiative aims to develop a solar-powered uncrewed aerial vehicle (UAV) capable of breaking the world record for the longest autonomous flight. Featuring a 6-meter wingspan, lightweight composite structure, and 96-cell solar array, CREATeV serves not only as a technological innovation in ultra-long endurance flight but also as a foundation for generating new and diverse research avenues. Over the past eight years, the project has accumulated over 70 hours of logged flight time and generated numerous publications on topics such as flight path optimization, wind tunnel testing, design optimizations, and flight testing methodologies. Current research efforts focus on further extending the aircraft’s endurance, including dynamic soaring techniques making use of temperature inversions, gust energy harvesting through aeroelastic tailoring, and optimized daytime flight strategies to maximize solar charge. This paper provides an overview of the ongoing activities in the lab, showcasing the progress of the CREATeV project, recent test flights and experiments, and the future research opportunities it continues to present. It also discusses the challenges faced during development along with the solutions implemented to address them.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".