S-Duct with Boundary Layer Ingestion: Geometry Optimization and Validation
Bibliographic record
Abstract
The National Research Council Canada Aerospace Research Centre is collaborating with the University of Toronto Institute for Aerospace Studies to develop an experimentally-validated numerical optimization tool that produces a propulsor intake geometry optimized to minimize circumferential flow distortion and pressure losses. The goal is to eventually apply this tool to the design of future low-emission aircraft concepts that incorporate S-ducts with boundary layer ingestion. The first phase of testing, which did not include a fan, was completed in the NRC’s Gas Turbine Lab Test Cell 1. After the empty test rig pressure calibrations and boundary layer generator calibrations, the main test program was completed by measuring the pressure distribution over the S-duct inlet and outlet areas, as well as various locations within the interior of the S-duct. The measurements were completed at inlet speeds of Mach 0.16 and Mach 0.19, and inlet boundary layer thicknesses varying from 20% to 69%. The experimental data shows good agreement with the CFD predictions, confirming the ability of the optimization algorithm to produce an optimized S-duct geometry with low circumferential flow distortion. The results include a discussion on the sensitivity of the S-duct performance to inlet boundary layer thickness and Mach number.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".