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Record W4406385776 · doi:10.51501/jotnafe.v39i1.65

Forensic Engineering Investigation of a High-Voltage Transmission Line Anchor Shackle Failure

2022· article· en· W4406385776 on OpenAlexaboutno aff
Daniel P Couture

Bibliographic record

VenueJournal of the National Academy of Forensic Engineers · 2022
Typearticle
Languageen
FieldEngineering
TopicMechanical stress and fatigue analysis
Canadian institutionsnot available
Fundersnot available
KeywordsShackleHigh voltageTransmission lineElectric power transmissionLine (geometry)EngineeringForensic engineeringVoltageElectrical engineeringReliability engineeringNuclear engineeringMechanical engineeringMathematics

Abstract

fetched live from OpenAlex

A forged alloy steel anchor shackle, one of a batch of more than 2,600 produced for the project, failed catastrophically in service on a newly erected 66-kilometer high-voltage transmission line in northern Canada. A failure analysis led to a hypothesis that forging laps had created the critical crack size to initiate propaga-tion under cold weather conditions. An extensive Charpy fracture toughness test program based on CAN/CSA C83.115-96 parameters was performed on 150 shackles, but the data did not support the initial hypothesis of temperature dependence. The forensic engineering team designed experimental tensile tests at ambient tem-peratures as low as -40°C to evaluate the propagation response of lap cracks in a statistically valid sampling of shackles. The trimmed forging flash area disguised laps from the manufacturing process, and subsequent galvanizing steps prevented detection by magnetic particle inspection. A focused recommendation for removal and replacement of the shackles was issued for those bearing major loads in the tower array.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.342
Threshold uncertainty score0.470

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 integrity0.0000.001
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 head0.015
GPT teacher head0.221
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

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