Comparison of a Compact Isokinetic Total Water Content Probe to Standard & T-Shaped Multi-Element Probes for Characterizing Glaciated, Liquid and Mixed Phase Environments
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2021-2656.vid Characterizing mixed phase environments is an ongoing challenge in icing research. The Gas Turbine Laboratory at the National Research Council of Canada uses three different instruments to differentiate liquid and ice water content. The instruments are the NRC compact isokinetic total water content probe, the SEA multi-element probe and the SEA T-shaped multi-element probe. Each has its advantages and are in active use. To properly compare tests using different probes they have been assessed under a variety of conditions in an altitude wind tunnel. Initially the probes were compared under fully glaciated and liquid environments. A mixed phase environment was generated by combining super cooled liquid spray and injected ice crystals. The response to the conditions encountered within a warm engine environment was also examined starting with fully glaciated conditions and increasing levels of melt to increase the liquid water content. This paper describes the test conditions and presents the results.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".