Conjugate Mass Transfer in Gas Channels and Diffusion Layers of Fuel Cells
Bibliographic record
Abstract
Prediction of mass transfer effects is a key element in fuel cell design. In this paper, the results of a generalized analysis appropriate to a wide range of designs and flow conditions are presented. Mass transfer in a rectangular gas passage, diffusion layer, and the combination of the two is considered. Fully developed viscous flow is presumed to occur within the passage, while the incompressible form of Darcy’s law is prescribed for the diffusion layer. The mathematical foundations for a simple mass transfer analysis are presented. Detailed calculations are then performed by means of a computational fluid dynamics code. These results are then correlated according to the analytical methodology in terms of nondimensional numbers appropriate to mass transfer analysis; namely, the overall mass transfer driving force as a function of the blowing parameter. Parametric studies are performed for a range of geometries, as characterized by the aspect ratio and blockage factor. It is shown that a simple solution for the overall driving force may readily be obtained from the two individual solutions for the conjugate mass transfer problem. This solution is quite general in its nature, and may readily be used to predict concentration polarization effects for a variety of fuel cells.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".