Pore Network Modeling of Compressed Fuel Cell Components with OpenPNM
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Pore network modeling is used to model water invasion and multiphase transport through compressed PEFC gas diffusion layers. Networks are created using a Delaunay tessellation of randomly placed base‐points setting the pore locations and its compliment, the Voronoi diagram, is used to define the location of fibers and resultant pore and throat geometry. The model is validated in comparison to experimental capillary pressure curves obtained on compressed and uncompressed materials. Primary drainage is simulated with an invasion percolation algorithm that sequentially invades pores and throats separately with excellent agreement to experimental data, but required a slight modification to account for the higher aspect ratio of compressed pores. Compression is simulated by scaling the through‐plane coordinates in a uniform manner representing a GDL wholly beneath the current‐collector land. The relative permeability and diffusivity show some dependence on uniform compression. In‐plane porosity variations introduced by land‐channel compression are also investigated which have a marked effect on the limiting current. Saturation at breakthrough does not appear to be dependent on compression. However, a more important parameter, namely the peak saturation, is shown to influence the fuel cell performance and is dependent on the percolation inlet conditions.
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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 | 0.000 | 0.000 |
| 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