The characteristics of coherent structures in low Reynolds number mixed convection flows
Bibliographic record
Abstract
Turbulent coherent structures generated in a channel flow at low Reynolds numbers during mixed convection have been experimentally studied using the particle image velocimetry (PIV) technique. The measurements are conducted in the channel cross-plane, the streamwise mid-vertical plane and two horizontal planes close to the bottom heated wall to capture the three-dimensional aspect. In the present study, Gr / Re 2 ranged between 9 and 206, implying that the natural convection was dominant over forced convection. An algorithm based on the velocity tensor second invariant ( Q ) is used to detect coherent structures. The location of each detected coherent structure is recorded, and vorticity and kinetic energy associated with each coherent structure are computed. The number and strength of the coherent structures are found to increase with an increase in the bottom wall temperature in all measurement planes. The strength and number of coherent structures show partial dependency on the flow rate. The number of coherent structures is found to be largest in the channel’s lower half, where strong interactions between rising plumes, falling sheets and mean shear flow occur. However, on average, the most energetic coherent structures are present in the channel’s upper region.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".