MétaCan
Menu
Back to cohort
Record W2176563686 · doi:10.1149/06403.0593ecst

Investigating Inlet Condition Effects on PEMFC GDL Liquid Water Transport through Pore Network Modeling

2014· article· en· W2176563686 on OpenAlexafffund
Mohammadreza Fazeli, James Hinebaugh, Aimy Bazylak

Bibliographic record

VenueECS Transactions · 2014
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Toronto
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsInletSaturation (graph theory)Materials scienceMechanicsPercolation (cognitive psychology)Petroleum engineeringGeologyGeomorphology

Abstract

fetched live from OpenAlex

In this work, the influence of the liquid water inlet boundary conditions at the GDL/catalyst layer interface on the spatial distribution of liquid water within the GDL was studied. We used pore network modeling with invasion percolation to simulate liquid water transport in a commercially available GDL, where the detailed, 3D microstructure of the GDL was obtained through X-ray imaging. Three inlet boundary conditions were studied: uniform pressure (single reservoir), uniform flux (completely discretized reservoirs), and distributed uniform pressure (random spatial- and size-distributions of reservoirs). We presented the distributed uniform pressure boundary condition as a more realistic inlet, where inlets are randomly distributed reservoirs that are connected to multiple inlet pores. It was found that the overall saturation ranged from 13% to 23% when the number of inlets ranged from 20 to 300; however, the microporous layer/catalyst layer delamination dominated water transport behaviour.

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.

How this classification was reachedexpand

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 score0.341
Threshold uncertainty score0.703

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 head0.008
GPT teacher head0.198
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueECS TransactionsSame topicFuel Cells and Related MaterialsFrench-language works237,207