PIV Study of Turbulent Flow in Asymmetric Converging and Diverging Channels
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Bibliographic record
Abstract
An experimental investigation of turbulent flow subjected to variable adverse and favorable pressure gradients in two-dimensional asymmetric channels is reported. The floors of the diverging and converging channels were flat while the roofs of the channels were curved. Adverse pressure gradient flows at Reh=27,050 and 12,450 and favorable pressure gradient flow at Reh=19,280 were studied. A particle image velocimetry was used to conduct detailed measurements at several planes upstream, within the variable section and within the downstream sections. The boundary layer parameters were obtained in the upper and lower boundary layers to study the effects of pressure gradients on the development of the mean flow on the floor and roof of the channels. The profiles of the mean velocities, turbulence intensities, Reynolds shear stress, mixing length, eddy viscosity, and turbulence production were also obtained to document the salient features of pressure gradient turbulent flows in asymmetric converging and diverging channels.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it