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Record W3215214098 · doi:10.1115/1.4053116

Interaction Assessment of Diagonally Spaced Identical Corrosion Defects and Fully Aligned Unequal-Sized Corrosion Defects Under Combined Loads

2021· article· en· W3215214098 on OpenAlexaff
Shulong Zhang, Wenxing Zhou

Bibliographic record

VenueJournal of Pressure Vessel Technology · 2021
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsWestern University
Fundersnot available
KeywordsMaterials scienceCorrosionParametric statisticsFinite element methodStructural engineeringInternal pressureCompression (physics)Composite materialEngineeringMathematics

Abstract

fetched live from OpenAlex

Abstract In this study, the interaction effects of closely spaced corrosion defects on the burst capacity of oil and gas pipelines under combined internal pressure and longitudinal compression are investigated by using parametric three-dimensional elasto-plastic finite element analyses. Full-scale burst tests reported in the literature are used to validate the finite element model. It is observed that the interaction effects of diagonally spaced defects on the burst capacity are strongly related to the overlapping portion of the defect width or circumferential spacing between the two defects. The analysis results indicate that the strongest interaction between diagonally spaced defects under combined loads occurs if the defects have zero circumferential separation. The interaction weakens as the defects are more and more overlapped or separated circumferentially. It is also observed that the interaction effect associated with longitudinally or circumferentially aligned, unequal-sized corrosion defects is negligible under the internal pressure only or combined loads.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.009
GPT teacher head0.266
Teacher spread0.257 · 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 designSimulation or modeling
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

Citations3
Published2021
Admission routes1
Has abstractyes

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