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Taking the Heat: IEEE Standard 80 and Bimetallic Conductors

2022· article· en· W4385249295 on OpenAlexaff
Robert Southey, Jeffrey T. Jordan, F. Dawalibi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicThermal Analysis in Power Transmission
Canadian institutionsSafe Engineering Services & Technologies (Canada)
Fundersnot available
KeywordsElectrical conductorConductorHeat sinkNuclear engineeringBimetallic stripComputer scienceMechanical engineeringEngineeringReliability engineeringMaterials scienceElectrical engineeringMetallurgyComposite material

Abstract

fetched live from OpenAlex

IEEE Standard 80-2013 provides the substation grounding system designer with simple formulae and tabulated data for the estimation of the maximum fault current that can flow through various types and sizes of conductor, for a given duration, before failure due to fusing occurs. Copper conductors are given exhaustive and reasonably accurate treatment. Other types of conductors, however, are given short thrift. Copper-clad steel (CCS) conductors, whose steel cores provide an effective heat sink, appear not to have been studied at all. As a result, the standard provides only an unrealistic simplified methodology based on fixed physical constants to be used for the calculation of CCS current-carrying limits. Computer modeling and lab testing have demonstrated that the highly non-linear heat absorption characteristics of the CCS core, when properly considered, yield considerably different fault current-carrying capacity than IEEE Standard 80-2013 would lead design engineers to expect. A theoretical framework for the calculation of these values is presented. Computed values are compared with those obtained by an independent accredited high voltage test laboratory.

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 categoriesInsufficient payload (model declined to judge)
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 score0.626
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.216
Teacher spread0.204 · 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.

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

Citations1
Published2022
Admission routes1
Has abstractyes

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