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Record W2532500327 · doi:10.1115/ipc2000-190

Experimental Database for Corroded Pipe: Evaluation of RSTRENG and B31G

2000· article· en· W2532500327 on OpenAlex

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 Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Waterloo
KeywordsCorrosionFailure assessmentMaterials sciencePipeline transportUltimate tensile strengthStructural engineeringMetallurgyDatabaseComposite materialComputer scienceEngineeringFracture mechanicsMechanical engineering

Abstract

fetched live from OpenAlex

The evaluation and development of the current corrosion defect assessment procedures for pipelines has been based on experimental burst tests of line pipe. In these tests, external corrosion has often been simulated with machined defects of simple geometry. As a result, assessment procedures which model the corrosion defect geometry with only a few parameters, such as ASME B31G, show reasonable agreement with the experiments. However, the degree of conservatism in these assessment methods is undefined when they are applied to complex corrosion defects. The authors have burst over 40 pipes removed from service due to corrosion defects. All corrosion defects on each pipe were measured in detail and the material properties were determined from tensile tests. The currently accepted assessment procedures for corroded line pipe (B31G and RSTRENG) have been applied to the database. The degree of conservatism in these procedures is quantified and a statistical model for the failure predictions is proposed.

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 categoriesInsufficient payload (model declined to judge)
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 score0.505
Threshold uncertainty score0.999

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)0.0020.000

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 head0.030
GPT teacher head0.291
Teacher spread0.261 · 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