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Record W2048029860 · doi:10.1115/ipc2004-0233

In-Line Stress Measurement by the Continuous Barkhausen Method

2004· article· en· W2048029860 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venue2004 International Pipeline Conference, Volumes 1, 2, and 3 · 2004
Typearticle
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutionsnot available
FundersSouthwest Research Institute
KeywordsBarkhausen effectBarkhausen stability criterionMagnetic flux leakagePipeline transportPipeline (software)AcousticsStress (linguistics)Magnetic fieldExcitationNoise (video)Magnetic fluxField (mathematics)Mechanical engineeringEngineeringElectronic engineeringElectrical engineeringComputer scienceMagnetPhysicsArtificial intelligenceMagnetization

Abstract

fetched live from OpenAlex

This paper describes a novel concept for measuring pipe wall stress. Southwest Research Institute® (SwRI®) pioneered the use of the Barkhausen effect for stress measurement in the 1960s, and the method is still in use today. University researchers in Canada are using the technique for determining stress magnitude and direction by making measurements at quite high resolution. Their technique, which follows from the early SwRI work, requires an alternating magnetic excitation field and an inductive sensor that responds to the Barkhausen magnetic transitions. In contrast, the Continuous Barkhausen concept does not require an alternating excitation field, relying instead on the field transition already present as a magnetic flux leakage (MFL) pig moves through a pipeline. All MFL pigs in use today create Barkhausen noise as they move through the pipeline. The only requirement for using those signals to reveal information about the pipe is to provide suitable sensors and amplifiers to develop a data interpretation procedure. This paper reports on work sponsored by the U.S. Department of Transportation in which SwRI and their commercializing partner, H. ROSEN Engineering, performed laboratory and pull-test experiments to validate the technique using MFL pig hardware in a test line having artificially induced stress anomalies. Details of the technique, laboratory experimental results, and pull-test results are presented, along with recommendations for the application of the method to operating pipelines.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.784
Threshold uncertainty score0.701

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)0.0000.000

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 head0.021
GPT teacher head0.268
Teacher spread0.247 · 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