Concentration field based micropore flow rate measurements
Bibliographic record
Abstract
Demand is growing for a larger catalogue of experimental techniques to measure flow rates through micro-/nanoscale systems for both fundamental research and device development. Flow emerging from a hole in a plane wall is a common system of interest in such work for its relevance to membrane separation. In this paper, we consider the possibility of measuring volume flow rates through small scale orifice plates from images of dye dispersions downstream. Based on approximate analytical solutions to the advection–diffusion equation, we show that, at low Reynolds numbers, the concentration in the nearly hemispherical plume that forms increases linearly with inverse distance from the pore and that the slope is proportional to volume flow rate. From micrographs of fluorescent dye plumes taken downstream of micropores of three different diameters, we demonstrate that, at Reynolds numbers below 15, the volume flow rate can be determined by extracting this slope from fluorescence intensity images. At higher Reynolds numbers, laminar jets form. In this regime, we derive an approximate similarity solution for the concentration field and show agreement of imaged dye dispersion shapes with both analytical expressions for the streamlines and isoconcentration contours at Reynolds numbers above 25. The results validate a scalable method for flow rate measurements applicable to small micropores of any geometry in plane walls and to small areas of porous materials relevant to membrane systems.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".