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Transmission Structure Corrosion Due to Stray Currents and Inspection Techniques: A Review

2023· review· en· W4391422392 on OpenAlexaff
Chenyang Wang, Shaikat Chowdhury, Xiaodong Liang

Bibliographic record

Venuenot available
Typereview
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsUniversity of SaskatchewanManitoba Hydro
Fundersnot available
KeywordsCorrosionTransmission (telecommunications)Stray voltagePower transmissionElectric power transmissionTransmission lineEngineeringForensic engineeringComputer scienceElectrical engineeringReliability engineeringPower (physics)Materials scienceMetallurgyPhysics

Abstract

fetched live from OpenAlex

Transmission structures cost about 50% of project budget on material for transmission grids, and the structural failure is always a major concern. Corrosion of transmission structures is a primary cause of in-service equipment degradation and is becoming an increasing engineering and economic problem, with utilities spending more of their maintenance budget on inspection and refurbishment of corroded structures each year. The increasing congestion from shared Right-of-Ways (ROWs) with other infrastructures also negatively impacts transmission structures through stray current interactions. This paper reviews the impact of below-grade corrosion on electric power transmission line structures with a focus on electrolytic corrosion due to stray current interference. Corrosion inspection techniques are also reviewed. The future research direction is recommended in this important but rarely researched area.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.045
GPT teacher head0.355
Teacher spread0.310 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2023
Admission routes1
Has abstractyes

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