Performance Analysis of a Smaller-Capacity Straight-Bladed VAWT with Prospective Airfoils
Bibliographic record
Abstract
Modern wind turbines are categorized as horizontal axis wind turbines (HAWTs) and vertical axis wind turbines (VAWTs), which are currently being utilized for diversified applications. The basic theoretical advantages of VAWTs are: (i) they accept the wind from any direction, and (ii) the generator, gearbox etc. can be placed on the ground. Selection of airfoil is one of the most critical factor in achieving optimum aerodynamic performance and in determining the optimum dimensions of a fixed-pitch straight-bladed vertical axis wind turbine (SB-VAWT). Airfoil related design changes also have the potential for increasing the cost effectiveness of VAWTs. Most of the earlier research works carried out by different research organizations mainly used NACA symmetric airfoils which were unable to self-start properly. In this paper, detail systematic investigative analyses have been performed with high-lift asymmetric airfoils appropriate for self-starting and better performance of smaller capacity SB-VAWT. In order to do the performance analysis, a computational scheme has been developed using the Cascade Model and XFOIL, a sub-sonic airfoil design and analysis tool developed in MIT. It has been found out that the results obtained from the computational scheme conform reasonably well with the experimental results. Subsequently, three prospective airfoils have been identified using this computational scheme. It has been found that their performance is better than conventionally used NACA 0015 at low tip speed ratio range where the problem of self-starting happens. Copyright © 2008 by Islam, Amin, Ting & Fartaj.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".