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Record W4242529723 · doi:10.1002/9781119274780.ch162

Low Resistance Anode Assembly Using Steel Stubhole Conductors Across The Cast Iron To Carbon Interface

2016· other· en· W4242529723 on OpenAlexaff
W. Berends, S. Haley, Michael L. Gagnon

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEngineering
TopicMechanical stress and fatigue analysis
Canadian institutionsAluminerie Alouette (Canada)Hatch (Canada)
Fundersnot available
KeywordsElectrical conductorMaterials scienceAnodeContact resistanceElectrical contactsStub (electronics)Carbon fibersComposite materialElectrical resistance and conductanceCarbon steelCast ironMetallurgyElectrodeCorrosionComposite numberElectrical engineeringChemistryEngineering

Abstract

fetched live from OpenAlex

Anode assemblies suffer a significant electrical contact resistance across the cast iron to carbon interface that is inversely dependent on contact pressure and area. Industry efforts have incrementally reduced this electrical resistance by increasing stub diameter, changing iron chemistry and by improving the stubhole shape. The additional use of multiple steel conductors to bridge across the cas tiron to carbon interface provides a means to further reduce the electrical resistance. The function of the conductors is independent of the iron to carbon contact pressure, the stub temperature, iron chemistry, and the stubhole shape. The steel conductors are tightly driven into the carbon anode at one end, with the other end bonded into the cast iron. This paper includes in-pot performance testing results which demonstrate the reduced resistance when using stubhole conductors.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.284
Teacher spread0.264 · 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
Published2016
Admission routes1
Has abstractyes

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