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Record W2069015188 · doi:10.1115/ipc2010-31091

Validation of Latest Generation EMAT In-Line Inspection Technology for SCC Management

2010· article· en· W2069015188 on OpenAlex
Jim Marr, Stephan Tappert, Elvis San Juan Riverol, Andy Mann, Jo ̈rg Weislogel, Jiangang Sun

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

Venue2010 8th International Pipeline Conference, Volume 1 · 2010
Typearticle
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutionsTransCanada (Canada)
Fundersnot available
KeywordsElectromagnetic acoustic transducerPipeline (software)Pipeline transportEngineeringLine (geometry)SizingIntegrity managementComputer scienceReliability engineeringAcousticsMechanical engineeringUltrasonic testingUltrasonic sensor

Abstract

fetched live from OpenAlex

TransCanada typically manages the integrity of sections of gas transmission pipelines that are susceptible to stress corrosion cracking (SCC) by periodically performing hydrostatic testing. Interest in an alternative approach to manage pipeline integrity in the presence of SCC and other forms of longitudinally oriented defects resulted in the endorsement of the latest generation of dry coupled in-line inspection tool. GE’s EMAT In-Line Inspection (ILI) tool uses the electromagnetic acoustic transducer technology to meet this requirement. This paper will summarize field experience results of the latest generation Emat In-Line inspection tool, which is commercial available since September 2008. It demonstrates, that the challenges have been overcome, the targets have been achieved, and the tool delivers the information of a distinguished ability of detection, sizing and discrimination performance, key parameters to conduct an effective pipeline integrity program.

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 score0.661
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.024
GPT teacher head0.269
Teacher spread0.245 · 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