Icing Qualification Wind Tunnel Test of Helicopter Engine with Inlet Barrier Filter Air Intake
Bibliographic record
Abstract
Icing wind tunnel testing was performed as part of the Republic of Korea certification of the Light Civil Helicopter (LCH) for inadvertent flight in icing conditions. The test was aimed at the compliance demonstration of the engine and air intake with dry-media Inlet Barrier Filter (IBF) and was performed with an Arriel 2C2 engine in turbojet configuration. Testing took place at the sea level ambient pressure Large Climatic Wind Tunnel (CWT) at Rail Tec Arsenal (RTA) in Vienna, Austria, by an integrated test team comprising engineers from the Royal Netherlands Aerospace Centre (NLR), Korea Aerospace Industries (KAI), and Safran Helicopter Engines. The test matrix covered the AC29-2C Appendix C 10,000 ft icing envelope, as well as simulated ground icing conditions, considering both a clean and artificially contaminated IBF. Beyond the aforementioned certification conditions, exploratory testing was performed in conditions with Supercooled Large Droplets (SLD) and rain. The test set-up consisted of the front section of the full-scale production cowling with internal modifications to accommodate the test engine and interface with the RTA exhaust gas handling system. Prior to tunnel entry, initial check-out and integration tests were performed with the same set-up at Safran, as well as in the Small CWT at RTA. Data gathering included the delta-pressure across the IBF, static pressures at the Aerodynamic Interface Plane (AIP), engine parameters, high-speed camera imagery, and 3-D scans of the critical ice shapes. The latter was used to support dry air flight testing with simulated ice shapes and blockage to demonstrate altitude effects and measure inlet distortion.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".