Book-keeping Investigations for BLI Aircraft
Bibliographic record
Abstract
Due to the high coupling between airframe and engine aerodynamics, new metrics are required to analyse and design aircraft configurations with Boundary Layer Ingestion (BLI). The objective of this work is to evaluate different methods of analysing and quantifying the benefits of BLI and to investigate their applicability in a preliminary design phase. In this context, CFD calculations have been carried out for different propulsor operating points on a simple fuselage with an actuator disk on its trailing edge to model the propulsor. A comparison between different book-keeping methods was performed and focused on the physical analysis of the aerodynamic coupling between the propulsor and fuselage. The power balance approach allows an understanding of the phenomena related to boundary layer ingestion and can be used even at a preliminary design stage. Furthermore, it gives better insights and allows the quantification of the interaction effects between the propulsor and the airframe. The comparison between the isentropic expansion method and the rigorous power balance shows that the isentropic expansion approach gives reasonable results when the interaction effects are limited. The accuracy degrades if inappropriate averaging is applied.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".