Application of the actuator surface concept to wind turbine rotor aerodynamics
Bibliographic record
Abstract
Abstract The structure of blade tip vortices is recognized as a key issue in wind turbine aerodynamic modelling by many researchers in the field. In the search for an intermediate model between full Navier–Stokes and blade‐element momentum simulations, this article presents a method using rotating actuator surfaces to model wind turbine aerodynamics. An actuator surface is a simple planar surface, porous to the flow, which is characterized by velocity and pressure discontinuities, whose action on the flow is achieved through an attached system of forces. These discontinuities and forces are determined from blade‐element analysis and the Kutta–Joukowski relation. After implementing this concept in a three‐dimensional CFD (Computational Fluid Dynamics) method, results are produced for the experimental rotors of NREL and TUDelft. The method is validated against both experimental measurements and the predictions of three other numerical models for wind turbine aerodynamic analysis. Qualitative and quantitative comparisons show that the actuator surface concept agrees well with the other numerical models. In addition to rotor aerodynamic analysis, the actuator surface concept can be used in the study of wake aerodynamics, or as the Eulerian flow solver in hybrid methods. Copyright © 2009 John Wiley & Sons, Ltd.
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 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 | 0.001 |
| Scholarly communication | 0.001 | 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 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".