Investigation of Horizontal and Vertical Wind Shear Effects Using a Wind Turbine Emulator
Bibliographic record
Abstract
This paper presents modeling and analysis of horizontal and vertical wind shear effects using a wind turbine emulator (WTE) with a comprehensive model. These periodic effects generate power fluctuations and mechanical stress on the wind turbine (WT) components during its operation. The frequency of these fluctuations associates with the rotation speed and the number of blades, whereas the amplitude increases in larger turbines. Although the vertical wind shear effect was modeled in literature using WTEs, the simplified aerodynamic and mechanical models were considered for WTs. In this paper, in addition to the vertical wind shear, the horizontal wind shear is modeled in simulation and experiment using a WTE, which may have more severe effects. The utilized WTE employs a comprehensive model for the WT, which considers aerodynamic, mechanical, and electrical aspects. The interaction of different aspects and mechanical dynamics is included in the WTE, which utilizes AeroDyn and FAST software tools to model the aerodynamic and the mechanical aspects of the WT. A coupled induction motor-induction generator set was employed to develop the WTE, which is used to model the wind shear effects for a fixed-speed WT.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".