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Record W2053518421 · doi:10.1115/ipc2012-90201

Identifying Initial Imperfection Patterns of Energy Pipes Using a 3D Laser Scanner

2012· article· en· W2053518421 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutionsTransCanada (Canada)University of Alberta
Fundersnot available
KeywordsScannerPoint cloudCylinderLaser scanningReverse engineeringFocus (optics)Pipeline transportMeasure (data warehouse)UpgradeComputer scienceMechanical engineeringEngineeringLaserOpticsArtificial intelligenceData miningPhysics

Abstract

fetched live from OpenAlex

Measurement of initial imperfections of energy pipes and incorporating them in analytical models has been a major focus of research in the pipeline industry as well as at the University of Alberta. Researchers at the University of Alberta have devised various techniques to measure initial imperfection of pipes prior to testing. The analytical imperfection models developed based on these techniques have proven to be effective in predicting pipe behavior. These techniques, however, are time consuming, error prone to some extent, and yield limited data, in addition to their limitations regarding the size of the pipes that can be measured. The objective of the current study is to overcome the limitations of the previous measurement techniques by utilizing advanced surface profiling technology. A high accuracy 3D laser scanner is used to create three dimensional models of energy pipes. Commercially available reverse engineering and inspection software is used to measure the different geometric attributes of the pipes that are of interest. This new technique enables us to overcome the previous limitations by acquiring data in the field at a faster rate and creating high resolution point clouds. The actual pipe surfaces are compared with the model of a perfect cylinder of uniform nominal diameter. It is possible to locate the axes of the scanned pipes and use these axes as references for measurements. Outer diameter variation, thickness variations, weld geometry variations and deviations from a perfect cylinder are measured. Results indicate that the deviations from a perfect cylinder can be used to describe the pattern of radii variations around the perimeter of the pipes. When described with respect to the seam weld location, distinct patterns of radii variations were identified. Thickness variations showed identical behavior in all the pipes when viewed with respect to the seam weld location.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score0.482

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 head0.032
GPT teacher head0.281
Teacher spread0.250 · 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

Quick stats

Citations6
Published2012
Admission routes2
Has abstractyes

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