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Record W2087883890 · doi:10.1002/er.1363

A review on macro-level modeling of planar solid oxide fuel cells

2007· review· en· W2087883890 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Energy Research · 2007
Typereview
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsUniversity of Ontario Institute of TechnologyCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsExergyOxideSolid oxide fuel cellHeat transferOhmic contactModeling and simulationMacroFuel cellsThermodynamicsConvectionMass transferMaterials scienceProcess engineeringMechanical engineeringChemistryComputer scienceChemical engineeringEngineeringAnodePhysicsSimulationElectrodePhysical chemistryMetallurgy

Abstract

fetched live from OpenAlex

In this review paper, a comprehensive literature survey on macro-level modeling of solid oxide fuel cells (SOFCs) is presented. First, the current status of the SOFC modeling is assessed. Second, modeling techniques are discussed in detail. These include the thermodynamics, electrochemistry and heat transfer aspects of the modeling. Thermodynamic relations for pure hydrogen as the fuel and then gas mixture as the fuel are given. Additionally, exergy destructed due to polarizations is shown. Then, modeling equations for ohmic, activation, and concentration polarizations are given. Handling the carbon deposition problem in the modeling is discussed. The inclusion of the convection and radiation heat transfer processes to the modeling is explained. Finally, the models in literature are compared in terms of the methodology used and suggestions for increasing the accuracy of the future models are given. Copyright © 2007 John Wiley & Sons, Ltd.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.870
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0000.001
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 head0.298
GPT teacher head0.506
Teacher spread0.208 · 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