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Record W36701278 · doi:10.5006/c2005-05138

Factors Affecting the Rate and Extent of Disbondment of FBE Coatings

2005· article· en· W36701278 on OpenAlexaffabout
Jenny Been, R. Given, Katherine Ikeda-Cameron, Robert Worthingham

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMaterial Properties and Processing
Canadian institutionsTransCanada (Canada)Nova Chemicals (Canada)
Fundersnot available
KeywordsMaterials scienceMetallurgyCorrosion

Abstract

fetched live from OpenAlex

Abstract External fusion bond epoxy (FBE) pipeline coatings have provided excellent protection and long-term service. However, field reports describe periodic blistering and coating disbondment. An investigative program consisting of a laboratory program and a program of field examinations had been initiated in order to understand the magnitude and causes of these phenomena. The laboratory experiments are described in this paper and the results are discussed in relation to the field experiences. FBE coating disbondment was tracked over time in four test environments that represent conditions on Canadian pipelines and was assessed as a function of cathodic potential, temperature, coating defect, the presence of oxygen, and time. Some long-term tests were monitored for up to 18 months. Conditions that promoted a continuous growth of the disbondment area versus those that resulted in no further growth of the disbondment area are presented and related to controlling disbondment mechanisms. In the presence of cathodic protection, blistering and disbondment of FBE coatings does not appear to present a pipeline integrity threat.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.017
GPT teacher head0.207
Teacher spread0.190 · 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 designObservational
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

Citations7
Published2005
Admission routes2
Has abstractyes

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