Experimental study on boundary layer of internal flow visible supersonic nozzle
Bibliographic record
Abstract
The high-frequency pulsation noise generated by the turbulent boundary layer on the wall of a Laval nozzle can significantly affect the quality of the flow field at the nozzle outlet. In this study, a supersonic wind tunnel with visible internal flow is designed and fabricated to observe the development and evolution of the boundary layer on the contraction and expansion surfaces of a Laval nozzle, as well as to study the flow field inside the supersonic nozzle. The subsonic, transonic and supersonic profiles of the nozzle are designed by bicubic curve, Hall method and classical characteristic line method respectively. The results of numerical calculation and total pressure measurement show that the flow field at the nozzle outlet of the wind tunnel is uniform and stable, and the deviation of Mach-number-root mean square is better than the qualified level of China’s national military standard. Nanoparticle-tracer based planar laser scattering (NPLS) technology is used to carry out the flow display test of the internal flow visual supersonic nozzle, and the fine structure image of the whole flow field in the nozzle is obtained. The image clearly shows the development and evolution of the boundary layer in the nozzle. The interface between boundary layer and main stream and the wall curve of nozzle transition region are extracted by image processing technology. The fractal dimension of the extracted boundary layer contour is calculated, thereby establishing the corresponding relationship between the fractal dimension and the boundary layer state, and determining the transition position of the boundary layer. The results show that the transition position of the nozzle profile is closer to downstream than that of the nozzle straight wall. The fractal dimension can qualitatively judge the flow state of the boundary layer; however, it is necessary to distinguish between laminar boundary layers and hairpin vortices in the initial transition stage by considering the thickness of boundary layer.
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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 | 0.000 |
| 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".