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Record W1981278155 · doi:10.1115/ipc2006-10491

A Tiered Approach to Girth Weld Defect Acceptance Criteria for Stress-Based Design of Pipelines

2006· article· en· W1981278155 on OpenAlexaff
Yong-Yi Wang, Ming Liu, David Horsley, Gery Bauman

Bibliographic record

VenueVolume 3: Materials and Joining; Pipeline Automation and Measurement; Risk and Reliability, Parts A and B · 2006
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsTransCanada (Canada)
Fundersnot available
KeywordsGirth (graph theory)Acceptance testingFlexibility (engineering)WeldingComputer sciencePipeline transportReliability engineeringRisk analysis (engineering)EngineeringMathematicsSoftware engineeringStatisticsMechanical engineering

Abstract

fetched live from OpenAlex

Alternative girth weld defect acceptance criteria implemented in major international codes and standards vary significantly. The requirements for welding procedure qualification and the allowable defect size are often very different among the codes and standards. The assessment procedures in some of the codes and standards are more adaptive to modern micro-alloyed TMCP steels, while others are much less so as they are empirical correlations of test data available at the time of the standards creation. A major effort funded jointly by the US Department of Transportation and PRCI has produced a comprehensive update to the girth weld defect acceptance criteria. The newly proposed procedures have two options. Option 1 is given in an easy-to-use graphical format. The determination of allowable flaw size is extremely simple. Option 2 provides more flexibility and generally allows larger flaws than Option 1, at the expense of more complex computations. Option 1 also has higher fracture toughness requirements than Option 2, as it is built on the concept of plastic collapse. In comparison to some existing codes and standards, the new procedures (1) provide more consistent level of conservatism, (2) include both plastic collapse and fracture criteria, and (3) give necessary considerations to the most frequently occurring defects in modern pipeline constructions. This paper provides an overview of the technical basis of the new procedures and validation against experimental test data.

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 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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.768
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.026
GPT teacher head0.237
Teacher spread0.211 · 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 teacher head, 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

Citations5
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueVolume 3: Materials and Joining; Pipeline Automation and Measurement; Risk and Reliability, Parts A and BSame topicFatigue and fracture mechanicsFrench-language works237,207