Design of a sub-scale fan for a boundary layer ingestion test with by-pass flow
Bibliographic record
Abstract
Abstract A design of a sub-scale Boundary Layer Ingestion (BLI) fan for a transonic test rig is presented. The fan is intended to be used in flow conditions with varying distortion patterns representative of a BLI application on an aircraft. The sub-scale fan design is based on a design study of a full-scale fan for a BLI demonstration project for a Fokker 100 aircraft. CFD results from the full-scale fan design and the ingested distortion pattern from CFD analyses of the whole aircraft are used as inputs for this study. The sub-scale fan is designed to have similar performance characteristics to the full-scale fan within the capabilities of the test facility. The available geometric rig envelope in the test facility necessitates a reduction in geometric scale and consideration of the operating conditions. Fan blades and vanes are re-designed for these conditions in order to mitigate the effects of the scaling. The effects of reduced size, increased relative tip clearance and thicknesses of the blades and vanes are evaluated as part of the step-by-step adaption of the design to the sub-scale conditions. Finally, the installation effects in the rig are simulated including important effects of the by-pass flow on the running characteristics and the need to control the effective fan nozzle area in order to cover the available fan operating range. The predicted operating behaviour of the fan as installed in the coming transonic test rig gives strong indication that the sub-scale fan tests will be successful.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".