Analysis and modelling of icing of air intake protection grids of aircraft engines
Bibliographic record
Abstract
Icing represents a major problem in the aviation industry. While icing of aerodynamic surfaces such as airfoils due to the impingement of supercooled liquid water droplets is widely studied, even if not yet fully understood, icing of supporting structures like protection grids of engine air intakes has been investigated to a lesser extent. An optimization of the design of the grids will help to reduce icing severity and delaying or avoiding loss of efficiency that could lead to hazardous situations. The present study investigates the icing behaviour of stainless steel protection grids in use on rotorcraft and turboprop engines. New experimental and analytical tools were developed to enable a quantitative study of grid icing under representative icing conditions in a lab-scale icing wind tunnel. The variation of the most relevant parameters like liquid water content of the cloud, airspeed, ambient temperature and mesh size of the grid allowed the identification of their influence on the icing behaviour. Further analysis of the experimental data led to the development and validation of a general physical model for ice accretion on grid structures.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".