Effect of Superhydrophobic Coating on the Anti-Icing and Deicing of an Airfoil
Bibliographic record
Abstract
Ice accumulation on aircraft wings can cause a loss in lift and increased drag. The present research investigates the effect of using a superhydrophobic coating, applied on an aluminum small-scale two-dimensional NACA 0012 airfoil, on ice accretion. The coating used is a commercial product that provides a contact angle of 160 deg, whereas the contact angle hysteresis is 6 deg. Experiments are conducted in a small-scale closed-loop icing wind tunnel at flow velocities ranging from 10 to , air temperatures from 0 to , a liquid water content between 1.0 and , and a mean volume diameter from 25 to . The experiments show that, compared to the aluminum airfoil, the superhydrophobic airfoil counteracts the formation of ice at air temperatures as low as . The results indicate a 50% power reduction to keep the superhydrophobic airfoil ice free in the simulated icing conditions and a time reduction of 75% to deice the airfoil when compared to the aluminum airfoil. It is deduced that no ice accretes on the airfoil when only its direct droplet impact area is covered with the superhydrophobic coating in anti-icing mode.
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".