Numerical Simulation of Gaseous Hydrocarbon Fuel Injection in a Hypersonic Inlet
Bibliographic record
Abstract
The performance of gaseous hydrocarbon/air mixing in the inlet of a scramjet is investigated in this paper. The two-oblique-shock mixed-compression inlet configuration is selected, and cantilevered ramp injectors, designed to deliver rapid mixing in a high-enthalpy flow, are placed strategically near the leading edge of the inlet. Air inflow conditions correspond to a Mach 8 flight at a dynamic pressure of 67,032 Pa at a 28.6 km altitude. The objective of this study is to evaluate the impact of inlet geometrical parameters, fuel-injection properties, and injector dimensions on the mixing efficiency. Both light (CH 4 ) and heavy (C 12 H 24 ) hydrocarbon fuels are considered. The analysis ofthree-dimensional steady-state flowfields is undertaken numerically, using the WARP code. WARP solves the multispecies Favre-averaged Navier―Stokes equations, which are closed by the Wilcox t-ω turbulence model. The numerical results indicate that a mixing efficiency of up to 95.8% can be achieved with a low risk of premature ignition. Inlet compression ratio, fuel-tank stagnation temperature, and fuel/air equivalence ratio are all identified as having a significant influence on inlet fuel-injection performance. The applicability of the cantilevered ramp injector to the Mach 8 hydrocarbon inlet is validated and justified.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".