Design and Development of the <i>Atlas</i> Human-Powered Helicopter
Bibliographic record
Abstract
AeroVelo initiated the Atlas Human-Powered Helicopter Project in August 2011 to win the AHS Sikorsky Prize, which despite prior attempts had remained unclaimed for over 30 years. The Sikorsky Prize required a human-powered helicopter to sustain flight for 60 s, momentarily reach a height of 3 m, and maintain position within a 10 m × 10 m area. A configuration study was undertaken using low-fidelity aerodynamic analysis and estimated mass figures. An aerostructural optimization framework was developed for rotor design, including a novel vortex-ring aerodynamic model with included ground effect prediction, finite-element analysis including integrated composite failure analysis, and a detailed weight estimation scheme. The airframe was composed of a wire-braced truss structure, and innovative designs were developed for many of the aircraft's lightweight-focused subsystems. After initial flight testing in August 2012, experimental optimization and performance improvement led to a second testing program beginning in January 2013. Testing in 2013 led to a reduction in required power, improved understanding of structural dynamics, and control strategy. The project culminated with the successful AHS Sikorsky Prize flight on June 13, 2013.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".