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Record W3024432148 · doi:10.1149/ma2020-01381606mtgabs

Modeling Gas Diffusion Layers in Polymer Electrolyte Fuel Cells Using a Continuum-based Pore-network Formulation

2020· article· en· W3024432148 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsGaseous diffusionThermal diffusivityMaterials scienceElectrolytePercolation theoryPorosityPermeability (electromagnetism)BarrerTortuosityPercolation (cognitive psychology)Capillary actionThermodynamicsMechanicsChemical engineeringComposite materialFuel cellsMembraneChemistryConductivityPhysicsElectrodeEngineering

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.203
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it