Internal Aerodynamic Performance Evaluation of Double Entrance S-Duct Intake at Moderately High Subsonic Mach Number
Bibliographic record
Abstract
Abstract Inlets are an essential element of aircraft propulsion systems. Aircraft with fuselage-embedded engines require intake ducts with bends to direct oncoming air into the engine. Consequently they often experience flow separation, losses, total pressure distortion, and swirling flow near the engine faces, all of which are detrimental to engine stability and performance. In some aircraft, double-entrance ducts are used to meet geometric constraints and maintain the required airflow. The present paper investigated aerodynamic performance of a bifurcated Y-duct with S-bends in both horizontal and vertical planes. Intake performance was evaluated at inlet Ma = 0.63 by measuring the surface static pressure along the four stream-wise rows of pressure taps and total pressure and 3D velocities using 5-hole probe across the exit plane of the intake duct. The data were used to determine the static and total pressure recovery, together with associated radial and circumferential distortion coefficients and swirl intensity. This work provides a rare experimental data-set for a twin-entrance, moderately high-subsonic, double S-duct intake. It compared reasonably with the most similar work published, that of single-entrance ducts at higher Mach number. Pressure recovery was on par while swirl was noted to be reduced when compared with those geometries. Complementary computational fluid dynamics was useful in the qualitative comparisons as well.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".