Velocity measurements of a shear flow penetrating a porous medium
Bibliographic record
Abstract
This paper reports an experimental investigation of simple shear flow penetrating a model of a fibrous porous medium. The flow field is established between a stationary inner cylinder and a concentric outer cylinder rotating at a constant speed. The model medium is a regular array of rods which are oriented across the flow and which fill a fraction of the annular space between the cylinders. Rods with circular, square and triangular cross-sections are investigated, and the solid volume fraction of the arrays ranges from 0.01 to 0.16. With a viscous oil as the working fluid, the Reynolds number is much less than unity. Velocity measurements made using particle image velocimetry focus on the region around the edge of each array tested. The measurements reveal that eddies form between the two outermost circles of rods, for solid volume fractions above a minimum value which depends on rod shape. The velocity data are used to find the interfacial slip velocity and the average velocity at the interface between the porous medium and the outer shear flow. The data demonstrate that the slip velocity decays with increasing solid volume fraction, as expected, but the velocity is found to be nearly independent of rod shape and of the number of circles of rods comprising an array. It is also found that the slip velocity is only 24–30% of the value predicted from the Brinkman equation.
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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 | 0.000 | 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".