Investigation of counter-rotating shock wave and wave direction control of hollow rotating detonation engine with Laval nozzle
Bibliographic record
Abstract
The counter-rotating shock wave and wave direction control of the hollow rotating detonation combustor with Laval nozzle are studied. The in-house solver BYRFoam, developed on the OpenFOAM platform, is used. The phenomenon and spatial distribution of the counter-rotating shock wave in the combustor are revealed. The result suggests that the closer the location is to the outer wall, the stronger the counter-rotating shock wave is. A method of controlling the wave direction is proposed. It is shown that the intensity of the counter-rotating shock wave is controlled by reducing the total pressure of the inlet, and then the direction of the detonation wave is controlled. The process of detonation wave reversing is divided into four steps, namely, counter-rotating shock waves evolve into detonation waves, several detonation waves are extinguished, detonation waves form again, and detonation waves propagate stably. The mechanism of wave direction control is investigated. The result shows that the fluctuation of the total pressure of the inlet stimulates the positive feedback interaction between the counter-rotating shock wave and the fresh gas, which causes initial detonation waves to be extinguished and the intensity of counter-rotating shock waves to become stronger and stronger, and eventually counter-rotating shock waves evolve into reverse detonation waves.
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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 | 0.000 |
| 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 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".