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Record W4312428434 · doi:10.1115/ipc2022-87165

Gaps in the Current Strain-Based Dent Assessment

2022· article· en· W4312428434 on OpenAlexaff
Rick Wang, Ken Zhang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsAlberta Energy
Fundersnot available
KeywordsIndentationFailure assessmentMaterials scienceStructural integrityFracture mechanicsFracture (geology)Structural engineeringForensic engineeringEngineeringComposite material

Abstract

fetched live from OpenAlex

Abstract Dents in pipelines, especially when associated with crack formation, pose a significant pipeline integrity threat. With crack formation during the initial indentation process, the fatigue life and failure pressure can dramatically reduce compared with crack-free dents. Over the past decade, cracks associated with the dent-formation process were typically assessed using strain-based engineering critical assessment (ECA), which compares the dent strain and curvature measured by in-line inspection (ILI) geometry tool, with industry-established damage criteria. However, in recent dent management practice, TC Energy has observed cracks in several shallow dents with strain levels much lower than any established fracture criteria. Cracks were found at some dents with measured depth at only 1.3% outer diameter (OD), and the calculated strain with ASME B31.8 nonmandatory method was ∼4% [6]. It is believed that the strain-based assessment solely based on post-formation shape measured by ILI geometry tool likely requires improvement to capture additional aspects that might contribute to formation of dent-cracks. Various dent formation processes were reviewed, and the multiple potential contributing factors are discussed in this paper, including loading rate sensitivity, temperature effect, stress triaxiality and geometrical influence. The effects of these factors on material responses, dent-crack formation and fracture damage are outlined. Observed gaps in the current strain-based dent assessment process are also outlined, and a multi-element approach to assess dents and identify dent-induced cracks is proposed, which includes evaluation of combined Caliper, magnetic flux leakage (MFL), electromagnetic acoustic transducer (EMAT) and axial flaw detector (AFD) data, enhanced dynamic testing and ductile failure damage indicator (DFDI) determination, materials modeling and finite element analysis (FEA) techniques. Results of two case studies using multiple real-life dent features are described to illustrate effectiveness of the proposed approach.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.002
Science and technology studies0.0000.001
Scholarly communication0.0030.003
Open science0.0040.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.016
GPT teacher head0.279
Teacher spread0.263 · 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 designNot applicable
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

Citations2
Published2022
Admission routes1
Has abstractyes

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