Investigation of an Asymmetrical Shock-Wave Boundary-Layer Interaction in a Supersonic Planar Nozzle
Bibliographic record
Abstract
When thrust nozzles are designed for high-altitude flight regimes, the propulsive jet is no longer adapted for operation at ground level and at low altitude. Thus, the nozzle operates in over-expanded regime. Unsteadiness due to the boundary layer/shock interactions in the divergent part of the nozzle can produce non-symmetric side loads that can damage the structure. The need for a complete understanding of this phenomenon and the validation of numerical methods and turbulence models able to predict this phenomenon has motivated a basic experiment aimed at producing an exhaustive set of experimental data. The test configuration made up of a rectangular nozzle and set up in a supersonic wind tunnel has allowed us to obtain a non-symmetric interaction whose unsteady aspects have been analyzed. This program was completed by numerical simulations of the flow in its mid-longitudinal symmetry plane. The goal was to test the capabilities of RANS (Reynolds Average Navier–Stokes) calculations in predicting the mean interacting flow through the use of three two-equation turbulence models. Two models, recently tested in the case of transonic and supersonic separations, compared with the Jones–Launder model, have given close results. Experimental and theoretical data have constituted the matter for a general discussion of the validation of turbulence models in channel flows where acoustic disturbances appear.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".