First measurements on BEARCAT, the SAFRAN’s heavily instrumented turboshaft
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2023-1936.vid In this paper, we will present examples of first experimental results obtained on a brand new turboshaft test rig called BEARCAT. BEARCAT is based on a Makila engine, a turboshaft developed by Safran Helicopter Engines and powering the H215 and the H225 Helicopter of Airbus Helicopters. BEARCAT has been developed by SAFRAN-Tech, the Research and Technology Center of the SAFRAN Group. This test engine is devoted to the fine characterization of aero-thermal phenomena occurring within the combustion chamber and the High Pressure Turbine as well as their interactions. Therefore, BEARCAT differs from a standard test engine by the implementation of moving probes inside the combustion chamber and the 2-stage High Pressure Turbine, in order to perform both steady and non-steady flow measurements. These data will be used to validate CFD codes and models
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".