Tailored composites and digital optimization for efficient eVTOL propellers
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
Abstract Electrified urban air mobility (UAM) aircraft, including small drones and electric vertical takeoff and landing (eVTOL) vehicles, require highly efficient, lightweight propellers. These propellers must meet stringent mechanical performance requirements while being manufacturable at high volumes and low cost. This study explores a holistic optimization approach for eVTOL propellers using stitch-free, adhesive bonded T-NCFs and a semi-automated design tool “Proptimize”. The developed propeller design tool integrates mechanical performance, manufacturing quality, and economic considerations, enabling systematic optimization. Compared to a benchmark, the optimized propeller demonstrator achieved a weighted performance increase of approximately 45%. The key improvements include an over 80% increase in bending and torsional stiffness, a 30% reduction in manual labor and production time, slight gains in propeller thrust at minimal increase in overall weight. Additionally, lightweight performance—measured as longitudinal and torsional stiffness per kilogram—was enhanced by up to 94%.
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