High Speed and Highly Efficient Rotor Blade Design
Bibliographic record
Abstract
Aerodynamic design of the high speed, highly efficient rotor (HSHER) blade is presented. The main objective was to design a medium-lift utility scale blade with improved high-speed performance and no penalty in hover, suitable for a single-main rotor operating at speeds between 180 and 200 knots. To accomplish this, a design concept was chosen consisting of an advanced passive blade shape along with an adjustable trailing-edge device. Initial studies using a blade-element solver combined with a genetic algorithm were used to quickly survey large portions of the design space. Next, a CFD-based process was established whereby CREATETM-AV HELIOS was used for high-speed forward-flight simulations while hover performance was addressed using a combination of Star-CCM+ for rapid iterations and HELIOS for more detailed evaluation. While fully-automated optimization was not performed, automation was introduced wherever possible to minimize manual effort and keep the engineering effort focused on high-level strategic decisions that are still somewhat difficult to automate. The final result was a new blade design which showed significant improvements in both high-speed performance (?L/D ~1) and hover efficiency (?FM ~0.03) with increased thrust capability.
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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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".