Large-eddy simulation of an ejector integrated in a rotating detonation engine cycle
Bibliographic record
Abstract
To facilitate the integration of a rotating detonation combustor (RDC) in a turbomachine, adding an ejector downstream of the combustor may be a viable option. The present work examines the performance of an ejector configuration under unsteady inflow conditions representative of an RDC exhaust, using a Large-Eddy Simulation. The RDC exhaust gas is generated at the nozzle exit of the ejector by an adequate choice of inlet axial fluctuation amplitude and frequency. The results along the jet centerline showed that the ejector flow remains in the low supersonic regime before passing through a secondary shock located at the constant-area mixing chamber exit. Mixing between the two flows begins immediately at the confluence and terminates slightly upstream of the secondary shock. The consideration of a theoretical thermodynamic cycle with the calculated ejector revealed that the ejector presence increases specific fuel consumption with respect to a reference cycle without an ejector installed. Entropy generation analysis showed that losses associated with thermal conduction have the most significant impact, followed by viscous dissipation losses. Both originate primarily in the shear layer between the RDC exhaust and the secondary flow. The flow characteristics at the ejector outlet and turbine inlet underline the potential of the ejector to couple the RDC with an axial turbine. Total pressure fluctuations are dampened by 65%, whereas the Mach number and the total temperature distortion are reduced to acceptable levels.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".