Understanding Ice Crystal Accretion and Shedding Phenomenon in Jet Engines Using a Rig Test
Bibliographic record
Abstract
The aviation industry has now connected a number of engine power-loss events to the ingestion of atmospheric ice crystals. Ice crystals are believed to penetrate to and eventually accrete on surfaces in the engine core where local air temperatures are warmer than freezing. Research aimed at understanding the accretion and shedding of ice crystals within the engine is being conducted industrywide. Although this specific icing condition is readily produced inside an operating engine, rig testing is the preferred research tool because it has the advantage of good visibility of the ice accretion process and easy access for video documentation. This paper presents one of the first efforts to simulate the warm air/cold ice conditions occurring inside the engine core using a test rig. The test section contains geometry simulating the transition duct between the low and high compressors in a typical jet engine and an airfoil simulating the engine strut connecting the inner and outer surfaces. Test results showed ice formed on the airfoil and other surfaces in the test section at air temperatures warmer than freezing. However, when both the air and surface temperatures were held below freezing, the injected ice did not melt and no ice accretion was observed. Ice only formed on the airfoil when mixed-phase conditions (liquid and ice) were produced, by introducing the ice into a warm airflow. This test concludes that a rig-level ice crystal icing test is feasible and capable of producing ice accretion in a simulated engine environment. As it was the first test of its kind, reporting of these preliminary test results are expected to benefit future experimenters.
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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 | 0.001 | 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".