ADVACT: A European Programme Investigating Adaptive Technologies for Future Aero Gas Turbine Engines
Bibliographic record
Abstract
*† ‡ § ** †† ‡‡ §§ , *** ††† , ‡‡‡ §§§ **** This paper will give an overview of flow-actuation systems contemplated in the ADVACT project, a European programme funded under the 6th Framework Programme. The project addresses the application of actuator technology in an aircraft engine environment, in particular flow-control of intake under strong cross-wind conditions, flow-control of low and high speed cascade blades and variable area nozzles by Shape Memory Alloys. The primary objective of ADVACT is to enable the achievements of improvements in operation, costs and reduction of environmental impact of gas turbines by the provision of extended in-flight actuation and control of engine parameters. Extended simulation work along with both material and devices characterization has enabled the ADVACT Consortium to design appropriate actuation systems that are aimed at engineconditions. Simulation and device characterization are the primary objects of this paper along with some insight on construction of rigs for testing under engine like conditions; this latter being the object of future work within ADVACT. Engine performance analysis with the adoption of some of these advanced actuation techniques is also investigated and data on 2 and 3-shaft engines are presented.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".