A Preliminary Study of Inter-Facility LWC Differences in Appendix C and Supercooled Large Droplet Conditions due to Calibration Instruments
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2021-2652.vid The simulation of clouds containing Supercooled Large Droplets has received increasing attention due to the introduction of Appendix O and future associated requirements for means of compliance. Supercooled Large Droplet conditions can cover four orders of magnitude in drop sizes, imposing a larger instrument measurement challenge than for Appendix C conditions. Wind tunnel facilities have adopted different instrumentation for liquid water content measurement, with fundamentally different principles of operation. In order to explore the comparability of the different instruments used for Appendix C and SLD measurement, and its impact on confidence in measurements used for means of compliance, a project was established to conduct a series of dedicated tests at three wind tunnel facilities. To date, liquid water content measurements have been completed using a Multi-Element sensor as the common instrument at two of the facilities. The data have provided preliminary information suggesting that substantial inter-facility differences likely exist in liquid water content estimates in Supercooled Large Droplet conditions that appear to be largely attributable to the choice of calibration instruments. These results are dependent on the assumption that the Multi-Element probe would produce equivalent measurements at the two facilities if the liquid water content were the same, regardless of other environmental differences that may exist between the two facilities. Planned further testing with other liquid water content measurement techniques may provide further information to confirm or refute the results of this study.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".