Ice Crystal Environment - Modular Axial Compressor Rig: Comparisons of Ice Accretion for 1 and 2 Stages of Compression
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">In 2021 the Federal Aviation Administration in collaboration with the National Research Council of Canada performed research on altitude ice crystal icing of aircraft engines using the modular compressor rig, ICE-MACR, in an altitude wind tunnel. The aim of the research campaign was to address research needs related to ice crystal icing of aircraft engines outlined in FAA publication Engine Ice Crystal Icing Technology Plan with Research Needs. This paper reports the findings on ice accretion from a configuration of ICE-MACR with two compression stages. Inherent in two-stage operation is not just additional fracturing and heating by the second stage but also higher axial velocity and potentially greater centrifuging of particles. These factors influence the accretion behavior in the test article compared to single stage accretion.</div><div class="htmlview paragraph">The melt ratio (liquid/total water content) has been shown to be an important parameter in ice crystal icing, with a relatively narrow band of melt ratios associated with optimum icing. Comparisons of appearance and the development of ice accretions were made at constant melt ratio for 1 and 2 stages, and important differences were found. The ice appeared different for two cases with equal melt ratio, and optimum icing occurred at much higher melt ratios for the 2-stage than the 1-stage configuration. The extent to which fracturing, centrifuging, heating and velocity affects the resulting ice accretions is evaluated using video, thermocouple, heat flux gauge and shadowgraph measurements. Heat flux gauge analysis provides insight into the importance of the dry-side temperature in the accretion process.</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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".