Investigation of the Effect of Inlet Turbulence and Reynolds Number on Developing Duct Flow
Bibliographic record
Abstract
This study investigates experimentally the effects of upstream flow conditions and Reynolds number on a developing duct flow. Particle image velocimetry (PIV) and hot-wire (HW) anemometry are employed to explore the flow dynamics in a rectangular duct with an aspect ratio of 2 and a length of 40 hydraulic diameters (Dh). Experiments are employed for two Reynolds numbers, ReDh = 17,750 and 35,500 where the inlet turbulence intensity is controlled using different turbulence grids. The results show that the inlet turbulence intensity and Reynolds number have a substantial effect on the flow evolution, the onset of shear layer interaction zone, and the subsequent relaxation to the fully developed flow. The main effect is linked to the development of the boundary layer, as the turbulence intensity decays rapidly in the core flow. The detailed analysis indicates that transition to turbulence advances upstream as the inlet turbulence intensity is increased, leading to an earlier onset of shear layer interaction and the decrease in entrance length. A similar upstream advancement of laminar-to-turbulent transition is induced as the Reynolds number is increased. However, a delay in the onset of shear layer interaction regime is observed at higher Reynolds number due to lower overall boundary layer growth rate. Thus, the focus of the analysis characterization of the boundary layer development and quantification of the associated changes in the duct flow development.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| 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".