Evaluating roof-mounted VAWT performance with CFD for various building shapes, boundary layer flows, and location scenarios
Bibliographic record
Abstract
The performance of a vertical axis wind turbine (VAWT) is investigated when placed at different positions on the roof, considering the building’s interaction with wind under various terrain categories and changes in the building’s shape. Computational fluid dynamics simulations are used to model a two-blade Darrieus-type VAWT. The results indicate that placing the VAWT at different positions on the roof leads to variations in the power coefficient ( CP). The findings revealed that placing the VAWT in the middle of the roof edge led to 45.1% and 6.7% increase in the maximum CP compared to the isolated turbine in the uniform flow and positioning it at the front corner of the roof, respectively. By considering different velocity profiles associated with various terrain categories, it was found that terrain roughness plays a significant role in the power performance of roof-mounted VAWTs. The results show that maximum performance is achieved in low-roughness areas, such as coastal regions, while the maximum C P decreases in rougher terrains. Additionally, the results indicate that when the VAWT is placed on top of a dome, it generates 50.7% more power compared to when it is placed on top of a cubic building of the same height.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".