Analytical Approach to Wake Vortex and Jet Wake Flow Interaction in Cruising Flight
Bibliographic record
Abstract
An analytical approach has been taken, to the crossplane nature of wake vortex and jet wake flows from commercial heavy jet transports in cruise, with a view to providing insight into the condensation patterns observed visually and sensed by ground-based LIDAR during flight research campaigns by the NRC, DLR and others. For this study, the essential features of the engine-exhaust turbulent jet flow have been considered, amidst the roll-up of the shed vorticity sheet, from the spanwise lift distribution, into a pair of primary, wingtip vortices. Jet-flow entrainment analysis yielded a mass-balancing radial inflow of such a magnitude to be a secondorder effect. The buoyant nature of the jet-core airflow from the gas-generator of turbofan engines, used on large jet transport aeroplanes constituted the principal effect. The degree of mixing between the hot core-flow and the cold bypass jet exhaust flow within the engine installation contributes to the magnitude of buoyancy. In particular, the mixing fraction will be greater in the case of podded-engine installation designs, which mix exhaust streams within the nacelle, compared to a nacelle which does not result in any hot and cold exhaust stream mixing until before discharge into the atmosphere. It is shown that for a hot-stream core-flow exhaust gas temperature of 650°C, upon discharge to the atmosphere in the case of a non-pre-mixed jet-flow, the core-flow detrains from the surrounding cold-stream jet, to rise above and remain above the shed vorticity sheet, essentially non-entrained, whereas the cold flow jet is entrained by the wrapping vorticity sheet. On the other hand, for a 40% hot/cold stream pre-mixing in the engine pod, the warmer core-flow detrains initially, but subsequently is re-entrained downwards under wingtip vortex inducement. Both cases have been observed to occur in the contrails of flight observations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".