Aerodynamic optimization of eVTOL rotor profiles
Bibliographic record
Abstract
Abstract: Electric Vertical Take-Off and Landing (eVTOL) aircraft are currently being developed to fill a gap in the air transportation sector and, simultaneously, provide zero-emissions alternatives to current generation carbon-intensive short-haul aircraft. However, unlike conventional fixed-wing or rotary aircraft, eVTOL rotors operate in both hover and forward flight configurations. This significantly increases the range of operating conditions experienced by the rotor, introducing multiple aerodynamic design challenges. Additionally, the efficiency of these rotors is particularly important, since it has a direct impact on power draw and aircraft range. In this presentation, a classical airfoil, the ClarkY, is used as a baseline configuration for an eVTOL rotor section. A gradient-based optimization framework using an adjoint solver in Discrete Adjoint with OpenFOAM (DAFoam) with the Reynolds Averaged Navier-Stokes (RANS) approach is then used. In this study, a control point-based free form deformation (FFD) method is used in the framework in order to change the aerodynamic shape. The objective function for this optimization is the lift-to-drag ratio, with additional target lift and geometric constraints. The baseline design is first validated against experimental data, and then the optimization is completed for several target lift coefficient values. Results demonstrate that the lift-to-drag ratio can be increased significantly while maintaining the desired target lift coefficient. Preliminary results for complete rotor optimization using RANS will then be presented, followed by preliminary airfoil optimization using Large Eddy Simulation (LES).
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.
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) | 0.001 | 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 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".