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Record W4306318802 · doi:10.1784/insi.2022.64.10.560

Application of a chord transducer for ultrasonic detection and characterisation of defects in MDPE butt fusion joints

2022· article· en· W4306318802 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInsight - Non-Destructive Testing and Condition Monitoring · 2022
Typearticle
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsUltrasonic sensorTransducerUltrasonic testingAcousticsChord (peer-to-peer)Materials scienceButt jointJoint (building)Nondestructive testingStructural engineeringEngineeringComputer science

Abstract

fetched live from OpenAlex

Butt fusion (BF) is the standard method for joining polyethylene (PE) pipes during gas and water pipeline construction. The joints require simple, inexpensive and effective non-destructive testing techniques. Ultrasonic inspection is the most suitable approach; however, joint geometry requires specific configuration of the acoustic beam. In this article, a custom-designed ultrasonic chord transducer optimised for a specific pipe diameter is described. It is demonstrated how variations of sound speed and attenuation in pipe material with temperature variations affects the operation of this type of transducer. A variety of common defects, including cold fusion, dust, dirt, grass contamination, voids, etc, are simulated inside the joint and used for technique development. Analysis of an A-scan produced in pitch-catch mode allows for the evaluation of joint quality and the classification of defect type.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.586
Threshold uncertainty score0.952

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 head0.017
GPT teacher head0.244
Teacher spread0.227 · 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