Effective Transport Coefficients for Porous Microstructures in Solid Oxide Fuel Cells
Bibliographic record
Abstract
A numerical framework to compute the effective transport coefficients for porous electrode microstructures is presented. The anode and cathode electrodes of solid oxide fuel cells are discretized as porous microstructures that are formed by randomly distributed and overlapping spheres with particle size distributions that match those of actual ceramic powders. The technique involves the construction of the composite electrode microstructure based on measureable starting parameters and the subsequent numerical evaluation of the effective transport coefficients. We use both the finite volume method and the Monte-Carlo simulation to enumerate effective transport coefficients. The results of the calculations are compared with experimental data for electron conductivities for a range of solid-matrix compositions. Comparisons are also made with theoretical correlations for effective coefficients. The effect of Knudsen diffusion on effective gas diffusivity is also addressed in this paper. Numerical results are compared with a harmonic average approximation based on Bosanquet's formula.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".