Modelling of Mach Reflections in Internal Axisymmetric Steady Supersonic Flow
Bibliographic record
Abstract
A new model to predict internal axisymmetric shocks with Mach reflections at their centreline is developed, and results are compared with an Eulerian flow solver, termed CFD herein. The model combines the method of characteristics with the equations for quasi-one-dimensional flow. Calculations are conducted for a range of axisymmetric wedge geometries, and the effects of wedge length and shock angle at the wedge leading edge are studied. These various wedge geometries are found to generate flowfields with similar flow features, with Mach discs that vary greatly in size. This observation forms the basis of a method that uses the results from a CFD mesh convergence study, conducted for a single wedge geometry, to determine the mesh resolution requirements and uncertainty due to finite mesh resolution for all other wedge geometries. When uncertainties due to the effects of finite mesh resolution are considered, it is shown that either the differences between model results and CFD results for Mach disc radius are small, or the results are almost indistinguishable from one another. The model indicates that these geometries generate a flowfield that can be treated as two separate parts: one supported by the wedge surface and another supported by the sharp corner at the wedge trailing edge. The influence of these separate flowfields on the incident shock, flow properties along the slip-line, and the size of the Mach disc is assessed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".