FENSAP-ICE Applications to Complete Rotorcraft Configurations
Bibliographic record
Abstract
The FENSAP-ICE system was first conceived for fixed-wing aircraft and air induction system icing, but major developments are underway to augment its capabilities for icing simulation of rotorcraft and tiltrotor aircraft. A project is underway, under the auspices of the RITA (Rotorcraft Industry Technology Association) to reduce icing certification flight tests through use of second-generation three-dimensional (3D) Computational Fluid Dynamics (CFD) based technologies. The plan is to supplement traditional icing tunnel and flight-testing with modern 3D inflight icing simulation tools that facilitate the development and certification of all-weather operations rotorcraft and tilt-rotor aircraft. A viscous fully 3D ice accretion and runback modeling capability is being developed and initial correlation studies to both 2D and 3D icing test cases have produced very good results. An actuator disk model has also been developed to account for the effects of the main and tail rotors on the flow field and the subsequent changes to ice accretion patterns. The present paper will describe droplet impingement and ice accretion results in terms of increasing geometrical complexity from 2D trimmed airfoil sections, to full 3D tiltrotor aircraft in forward flight, with propellers modeled.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".