Numerical simulation of the performance of an asymmetrical airfoil under extreme weather conditions
Bibliographic record
Abstract
This paper presents a numerical study of icing of a NACA2412 airfoil and the aerodynamic performance of the airfoil with ice accretion. The study analyzes the effects of liquid water content, accretion time and varying angles of attack (AoA) up to 200 on ice accretion and, consequently, on the aerodynamic coefficients of the airfoil. The free stream velocity and air temperature were kept constant in the simulations. Results revealed that the ratio of lift and drag coefficients was the highest after a short accretion time (i.e., about 20 minutes), but then it decreased significantly with accretion time. Ice accretion increased with time; its mass was the greatest at 100 of AoA. The results can be beneficial for designing blade shapes to optimize wind turbine performance during adverse weather conditions.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".