Effect of Geometrical Parameters on the Mixing Performance of Cantilevered Ramp Injectors
Bibliographic record
Abstract
A cantilevered ramp fuel-injection strategy is considered as a means to deliver rapid mixing for use in scramjets and shock-induced combustion ramjets (shcramjets). The primary objective is to perform parametric studies of the injector array spacing, injection angle, and sweeping angle at a convective Mach number of 1.5. Analysis of the three-dimensional steady-state hypersonic e owe elds is accomplished through the WARP code, using the Yee‐Roe e ux-limiting scheme and theWilcox k-! turbulencemodel, along with the Wilcox dilatational dissipation correction. A closer array spacing is shown to increase signie cantly the mixing efe ciency in the near e eld, and a direct relationship between initial fuel/air contact surface and mixing efe ciency growth is apparent. A change in the injector angle from 4 to 16 deg induces a 9% augmentation in the mixing efe ciency but more than a twofold increase in the thrust potential losses. A sweeping angle of i3.5 deg is observed to result into signie cantly better fuel penetration, translating into a 28% increase in the mixing efe ciency for a sweep angle decreased from 3.5 to i3.5 deg. It is observed that an air cushion between the wall and the hydrogen is sufe ciently thick to prevent fuel penetrating the boundary layer when 1 ) the fuel is injected at an angle of »10 deg or more, 2 ) an array spacing of at least the height of the injector is used, and 3 ) a swept ramp cone guration is avoided.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".