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A new procedure for rapid convergence in numerical performance calculations of electrochemical cells

2023· article· en· W4387376741 on OpenAlexaff
Shidong Zhang, Shangzhe Yu, Roland Peters, Steven Beale, Holger Marschall, Felix Kunz, Rüdiger‐A. Eichel

Bibliographic record

VenueElectrochimica Acta · 2023
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsQueen's University
FundersForschungszentrum JülichBundesministerium für Bildung und Forschung
KeywordsConvergence (economics)ElectrolysisCoupling (piping)Stability (learning theory)ElectrochemistryFuel cellsSolid oxide fuel cellComputer scienceElectric fieldMaterials scienceMathematical optimizationChemistryApplied mathematicsElectrodePhysicsMathematicsChemical engineeringEngineeringPhysical chemistry

Abstract

fetched live from OpenAlex

This paper introduces a novel coupled region-to-region numerical procedure for electric field potential calculations. A conventional segregated scheme is also introduced to illustrate the coupling issue that exists in performance calculations in electrochemical devices. Numerical simulations are conducted for a solid oxide cell operating in both fuel cell and electrolysis modes. The cell performance is predicted with both segregated and coupled methods. A comparison between the coupled and segregated schemes shows that the former greatly outperforms the latter, accelerating convergence (from 5000 to 300 iterations) and improving stability. A smaller coupling coefficient contributes to the convergence as well, however, less remarkably. The coupled region-to-region approach may readily be applied to numerous other scenarios, e.g., heat transfer problems between different phases and regions.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.868

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.263
Teacher spread0.250 · 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 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

Citations6
Published2023
Admission routes1
Has abstractyes

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Same venueElectrochimica ActaSame topicAdvancements in Solid Oxide Fuel CellsFrench-language works237,207