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Record W3197672705 · doi:10.3390/en14175484

Design and Modeling of Metallic Bipolar Plates for a Fuel Cell Range Extender

2021· article· en· W3197672705 on OpenAlexaff
Uwe Reimer, Ekaterina Nikitsina, Holger Janßen, Martin Müller, Dieter Froning, Steven Beale, Werner Lehnert

Bibliographic record

VenueEnergies · 2021
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsQueen's University
Fundersnot available
KeywordsCoolantAnodeCathodeHeat exchangerMaterials scienceMechanical engineeringNuclear engineeringFlow (mathematics)Computer scienceElectrical engineeringEngineeringMechanicsChemistryElectrodePhysics

Abstract

fetched live from OpenAlex

Fuel cells, designed for mobile applications, should feature compact and low-weight designs. This study describes a design process that fulfills the specific needs of target applications and the production process. The key challenge for this type of metallic bipolar plate is that the combination of two plates creates three flow fields, namely an anode side, a cathode side, and a coolant. This illustrates the fact that each cell constitutes an electrochemical converter with an integrated heat exchanger. The final arrangement is comprised of plates with parallel and separate serpentine channel configurations. The anode and cathode sides are optimized for operation under dry conditions. The final plate offers an almost perfect distribution of coolant flow over the active area. The high quality of this distribution is almost independent of the coolant mass flow, even if one of the six inlet channels is blocked. The software employed (OpenFOAM and SALOME) is freely available and can be used with templates.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0020.000
Insufficient payload (model declined to judge)0.0070.002

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 head0.022
GPT teacher head0.206
Teacher spread0.184 · 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 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

Citations6
Published2021
Admission routes1
Has abstractyes

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Same venueEnergiesSame topicFuel Cells and Related MaterialsFrench-language works237,207