Ice Particle Analysis of the Honeywell ALF502 Engine Booster
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">A flow and ice particle trajectory analysis was performed for the booster of the Honeywell ALF502 engine. The analysis focused on two closely related conditions one of which produced an icing event and another which did not during testing of the ALF502 engine in the Propulsion Systems Lab (PSL) at NASA Glenn Research Center. The flow analysis was generated using the NASA Glenn GlennHT flow solver and the particle analysis was generated using the NASA Glenn LEWICE3D v3.63 ice accretion software. The inflow conditions for the two conditions were similar with the main differences being that the condition that produced the icing event was 6.8 K colder than the non-icing event case and the inflow ice water content (IWC) for the non-icing event case was 50% less than for the icing event case. The particle analysis, which considered sublimation, evaporation and phase change, was generated for a 5 micron ice particle with a sticky impact model and for a 24 micron median volume diameter (MVD), 7 bin ice particle distribution with a supercooled large droplet (SLD) splash model used to simulate ice particle breakup. The particle analysis did not consider the effect of the runback and re-impingement of water resulting from the heated spinner and anti-icing system. The results from the analysis showed that the amount of impingement for the components were similar for the same particle size and impact model for the icing and non-icing event conditions. This was attributed to the similar aerodynamic conditions in the booster for the two cases. The particle temperature and melt fraction were higher at the same location and particle size for the non-icing event than for the icing event case due to the higher incoming inflow temperature for the non-event case. The 5 micron ice particle case produced higher impact temperatures and higher melt fractions on the components downstream of the fan than the 24 micron MVD case because the average particle size generated by the particle breakup was larger than 5 microns which yielded less warming and melting. The analysis also showed that the melt fraction and wet bulb temperature icing criterion developed during tests in the Research Altitude Test Facility (RATFac) at the National Research Council (NRC) of Canada were useful in predicting icing events in the ALF502 engine. The development of an ice particle impact model which includes the effects of particle breakup, phase change, and surface state is necessary to further improve the prediction of ice particle transport with phase change through turbomachinery.</div></div>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".