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Record W2900435772 · doi:10.1115/ipc2018-78538

Calibration of a Nondestructive Toughness Tester (NDTT) for Measuring Fracture Toughness of Pipeline Steel

2018· article· en· W2900435772 on OpenAlexaff
Steven D. Palkovic, Simon Bellemare, K. K. Botros, Xiande Chen, Richard Kania

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsTransCanada (Canada)Nova Chemicals (Canada)
Fundersnot available
KeywordsCharpy impact testMaterials scienceFracture toughnessNondestructive testingPipeline transportComposite materialCompact tension specimenUltimate tensile strengthFracture mechanicsToughnessStructural engineeringFracture (geology)EngineeringMechanical engineeringCrack growth resistance curveCrack closure

Abstract

fetched live from OpenAlex

In-ditch/in-service characterization of pipelines using nondestructive evaluation (NDE) can provide valuable data for confirming operating pressure and qualifying pipelines for transporting natural gas of different quality or gas mixture, as well as for determining repair criteria for integrity management programs. This is especially relevant for vintage pipelines that may not have material test reports (MTR) available, and for aging infrastructure that have been subjected to suspected or unknown integrity threats. However, measurement of material fracture toughness currently requires the removal of large samples for laboratory testing, such as compact tension (CT) fracture testing or Charpy impact testing. The present work introduces a new concept, the Nondestructive Toughness Tester (NDTT), that provides a NDE solution for measuring the fracture toughness of pipeline steel in a superficial layer of material (∼0.005 inches). The NDTT uses a specially designed wedge-shaped stylus to generate a Mode I tensile loading that results in a ductile fracture response. NDTT tests are performed in multiple orientations on 8 different pipeline steel samples covering 3 different grades to compare the NDTT material response with the fracture toughness measurements from laboratory CT specimens. Analysis of these results indicate that the height of a fractured ligament that remains on the sample surface after NDTT testing exhibits a linear relationship with traditional CT J-integral measurements normalized by its yield strength. This type of behavior is analogous to the crack-tip-opening-displacement (CTOD) calculated through elastic-plastic fracture mechanics. Tests conducted on the pipe outer diameter and in the longitudinal direction near the pipe mid-wall indicate that the NDTT can measure differences in fracture toughness for different crack orientations. Furthermore, the results show that outer diameter tests provide a conservative estimate of the overall steel fracture toughness. These observations indicate that the NDTT is a viable method for assessing toughness properties of steel materials. Additional research is required to further refine the implementation of the NDTT concept and understand the relationship with laboratory test results on pipe cutouts, but the progress is already a significant step towards obtaining additional material toughness data for integrity management.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.019
GPT teacher head0.233
Teacher spread0.214 · 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 designBench or experimental
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
Published2018
Admission routes1
Has abstractyes

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