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Record W3088816661 · doi:10.1149/09809.0305ecst

Combined Two-phase Co-flow and Counter-flow in a Gas Channel/Porous Transport Layer Assembly

2020· article· en· W3088816661 on OpenAlexaff
Steven Beale, Martin Andersson, Norbert Weber, Holger Marschall, Werner Lehnert

Bibliographic record

VenueECS Transactions · 2020
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsQueen's University
Fundersnot available
KeywordsFlow (mathematics)Materials scienceMechanicsTwo-phase flowCapillary actionProton exchange membrane fuel cellPorous mediumElectrolyteVolume (thermodynamics)PorosityElectrodeChemistryChemical engineeringThermodynamicsFuel cellsComposite materialPhysicsEngineering

Abstract

fetched live from OpenAlex

This paper considers a detailed numerical analysis of combined liquid-gas co-flow in a gas channel, with liquid-gas counter-flow in a porous transport layer, as is typically found on the cathode side of a polymer electrolyte fuel cell. The geometry is obtained by digital reconstruction of nano-computer tomography images. From this, the domain is tessellated with an unstructured castellated or octree mesh, upon which the equations of mass and momentum are solved by means of a volume of fluid method. Liquid water is produced from an electrode where gaseous oxygen is simultaneously consumed by electrochemical reduction; Liquid-gas counter flow in the porous transport layer results in liquid drops being entrained in co-flow in the gas channels and convected by the gas downstream.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.235
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations4
Published2020
Admission routes1
Has abstractyes

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