Inverse Airfoil Design Method for Low-Speed Straight-Bladed Darrieus-Type VAWT Applications
Bibliographic record
Abstract
The paper demonstrates the application of inverse airfoil design method to improve performance of a low-speed straight-bladed Darrieus-type VAWT. The study shows that an appropriate tailoring of the airfoil surface using the inverse airfoil design technique can help improve performance by eliminating undesirable flow field characteristics at very low Re, such as early transition due to presence of separation bubbles. The increase aerodynamic efficiency then translates into an improved aerodynamic performance of VAWTs specifically at very low chord Reynolds numbers. The study employs an interactive inverse airfoil design method (PROFOIL) that allows specification of velocity and boundary-layer characteristics over different segments of the airfoil subject to constraints on the geometry (closure) and the flow field (far field boundary). Additional constraints to satisfy some desirable features, such as pitching moment coefficient, thickness, camber, etc., along with a merit of performance of the VAWT, such as the required power output for a given tip-speed ratio, are specified as part of the inverse problem. Performance analyses of the airfoil and the VAWT are carried out with the aid of state-of-the-art analyses codes, XFOIL and CARDAAV, respectively. XFOIL is a panel method with a coupled boundary-layer scheme and is used to obtain the aerodynamic characteristics of resulting airfoil shapes. The final airfoil geometry is obtained through a multi-dimensional Newton iteration. A design example is presented to demonstrate the merits of the technique in improving performance of small VAWTs at low speeds. The main findings of the study suggests that the strength of the method lies in the inverse design methodology whereas its weaknesses is in reliably predicting aerodynamic characteristics of airfoils at low Reynolds numbers and high angles of attack. This weakness can, however, be overcome by assessing relative performance of the VAWT with the assumption that the changes in airfoil characteristics be kept small. The results indicate that a 10–15% increase in the relative performance of the VAWT can be achieved with this method.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".