Modeling Gas Diffusion Layers in Polymer Electrolyte Fuel Cells Using a Continuum-based Pore-network Formulation
Bibliographic record
Abstract
A pore-network formulation is presented to model gas diffusion layers (GDLs) in polymer electrolyte fuel cells (PEFCs) using a continuum-based approach. The formulation can easily be integrated into macroscopic models in CFD codes, thus improving the modeling predictions while keeping a moderate computational cost. The continuum-based pore-network formulation is based on a cubic lattice [1], which is divided into control volumes (cubes) of prescribed size. Pores and throats are placed inside the control volumes, and “connectors” of negligible volume interconnect the control volumes. The “connectors” are used to regulate the invasion-percolation pattern according to the size of the throat that links the pores within neighboring control volumes. Hence, the formulation can account for both invasion-percolation between pores as well as evaporation/condensation in the pore volume inside each control volume. This is a major advantage compared to traditional pore-network models based on a fully discrete formulation where phase-change phenomena are difficult to implement. Local anisotropic effective transport properties (permeability and diffusivity) are determined using a 1D resistor network analogy inside each control volume according to the size of the pore and throats in it. The model is validated against capillary pressure curves and effective transport properties (effective diffusivity and permeability) measured ex situ. In addition, water saturation profiles are compared with distributions obtained using X-ray computed tomography [2]. [1] Jeff T. Gostick, Marios A. Ioannidis, Michael W. Fowler, Mark D. Pritzker, Pore network modeling of fibrous gas diffusion layers for polymer electrolyte membrane fuel cells, J. Power Sources 173 (2007) 277-290. [2] P.A. García-Salaberri, G. Hwang, M. Vera, A.Z. Weber, J.T. Gostick, Effective diffusivity in partially-saturated carbon-fiber gas diffusion layers: Effect of through-plane saturation distribution , International Journal of Heat and Mass Transfer 86 (2015) 319–333.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".