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Record W2086871916 · doi:10.1002/etep.328

Laboratory performance tests on aluminum splices for power conductors

2009· article· en· W2086871916 on OpenAlexaff
M. Runde, R. S. Timsit, N. Magnusson

Bibliographic record

VenueEuropean Transactions on Electrical Power · 2009
Typearticle
Languageen
FieldEngineering
TopicElectrical Contact Performance and Analysis
Canadian institutionsCampbell Scientific (Canada)
Fundersnot available
KeywordsCable glandConductorElectrical conductorspliceCompression (physics)Structural engineeringEngineeringMaterials scienceMechanical engineeringElectrical engineeringComposite material

Abstract

fetched live from OpenAlex

Abstract The paper reviews the results of laboratory testing of compression and bolted splices installed on stranded aluminum power conductors. The tests on compression splices involved connectors of 10 different designs using 240 mm2stranded aluminum cable. Testing on the bolted splices was performed on connectors of 16 different designs installed on stranded aluminum cable with dimensions of 50 and 240 mm2. Splice performance was assessed on the basis of resistance measurements during short‐circuit tests and thermal cycling as specified by the International Electrotechnical Commission (IEC) 61238‐1 standard, and from inspections of cross‐sectioned connections. Differences in splice performance are related to such factors as physical properties of the materials in contact, splice assembly procedures, number of compression indentations or number of bolts, and other relevant parameters. The influence of conductor deformation on the ability to disrupt aluminum oxide films on the conductor surface during connector installation is addressed. The laboratory data indicate that large mechanical deformations in a splice significantly improve connector performance. For compression splices, relatively soft (annealed) conductors lead to inferior performance than hard‐drawn conductors, unless the soft conductor hardens significantly when it is deformed during installation. The sequence in which the compression indentations are made may influence connector performance. Copyright © 2009 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.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.007
GPT teacher head0.214
Teacher spread0.206 · 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

Citations6
Published2009
Admission routes1
Has abstractyes

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