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Record W2001727342 · doi:10.1115/ipc2006-10030

Testing to Determine Whether a PetroSleeve Can be Used for an Electrical Connection to a Pipe for AC Mitigation

2006· article· en· W2001727342 on OpenAlexaff
Robert Smyth, L. E. Cermak

Bibliographic record

VenueVolume 1: Project Management; Design and Construction; Environmental Issues; GIS/Database Development; Innovative Projects and Emerging Issues; Operations and Maintenance; Pipelining in Northern Environments; Standards and Regulations · 2006
Typearticle
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutionsAlberta Energy
Fundersnot available
KeywordsPipeline transportPipeline (software)TraverseCurrent (fluid)Connection (principal bundle)Electrical engineeringAmpereVoltageEngineeringElectrical conductorMechanical engineeringCircuit breakerMarine engineeringGeology

Abstract

fetched live from OpenAlex

The use of a mechanical electrical connection to a pipeline is tested to determine its’ viability. Historically, the installation of a cadweld on pipelines has been the method generally accepted for attaching an electrical connection to pipe. Cadwelds are usually serviceable. In the case of accommodating up to 800 amperes of current, up to 3 CAD welds have been used. In addition, there is a general feeling in the pipeline industry to avoid cadwelds, if possible, because they can create a heat affected zone and the possibility of cracking. Where pipelines traverse or parallel high voltage transmission lines, there exists the possibility of voltage and current induction when phase imbalance occurs. These current flows can approach 800 amps. If a cadweld is the main conduct at the pipe surface, burns, high heat, or connection malfunction can occur. This paper describes the testing undertaken to determine if a PetroSleeve installation could be used as a mechanical electrical connection suitable for conducting up to 800 amperes of current. Following the initial testing, three sleeves were installed on operating pipelines for AC Mitigation.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.446
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.267
Teacher spread0.245 · 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 designObservational
Domainnot available
GenreMethods

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
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueVolume 1: Project Management; Design and Construction; Environmental Issues; GIS/Database Development; Innovative Projects and Emerging Issues; Operations and Maintenance; Pipelining in Northern Environments; Standards and RegulationsSame topicNon-Destructive Testing TechniquesFrench-language works237,207