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Record W2555763843 · doi:10.1115/ipc2016-64097

Measuring Critical Strains in Dent Defect of Oil and Gas Pipes

2016· article· en· W2555763843 on OpenAlex
Jandark Oshana-Jajo, Jamshid Zohrehheydariha, Hossein Ghaednia, Sreekanta Das

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPipeline transportFinite element methodDamagesPipeline (software)Forensic engineeringParametric statisticsStructural engineeringPetroleum engineeringGeotechnical engineeringMaterials scienceEngineeringEnvironmental scienceMechanical engineering

Abstract

fetched live from OpenAlex

Steel pipelines are exposed to harsh environmental, geotechnical and other conditions and hence, they can be damaged. The damage can threaten the structural integrity of the pipeline and can cause economic loss and environmental damage if a failure occurs. A common way for pipelines to be damaged is through physical contact, creating a structural imperfection, dent, wrinkle, crack, and/or other damages or defects. A dent disrupts the pipeline’s circularity causing increased strains in concentrated areas. A research program was established and carried out to study the strain concentration of dented pipes. The study was completed using full-scale laboratory testing and numerical analysis at the Centre for Engineering Research in Pipelines (CERP). This study included four lab tests on two different pipe materials (X70 and X56) and finite element analysis (FEA) based parametric study.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.514
Threshold uncertainty score0.178

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.234
Teacher spread0.212 · 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