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Record W2000140831 · doi:10.1115/ipc2014-33238

Development of a 150°C Geopig Inertial Mapping Tool for Pipeline Strain Monitoring

2014· article· en· W2000140831 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsSuncor Energy (Canada)
FundersSuncor Energy Incorporated
KeywordsPipeline (software)Pipeline transportInertial measurement unitEngineeringComputer scienceProcess (computing)Systems engineeringEngineering drawingMarine engineeringMechanical engineeringManufacturing engineeringReliability engineeringAerospace engineering

Abstract

fetched live from OpenAlex

Pipeline strain monitoring using inertially-equipped pipeline inspection tools was developed in 1986 and is now an established method to identify pipe movement and associated bending strain. These pipeline inspections, however, are limited by the operating range of the electronics used in the inspection tools; these tools cannot be used for high-temperature pipelines that require strain monitoring. Suncor required that a high-temperature tool be designed and built for their 60 km Hot Bitumen (HotBit) pipeline from Firebag to Fort McMurray. Suncor approached various In-line Inspection providers to design an inertial mapping tool that would operate at temperatures to 150°C. Suncor selected Baker Hughes Incorporated (BHI) for this development project based on their reputation and their historical development with respect to pipeline strain monitoring. This paper outlines the development process chosen for this project, the various technical challenges that were overcome, and presents the results from the In-line Inspections performed at three temperatures spanning 120 degrees.

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 score0.497
Threshold uncertainty score0.362

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 head0.020
GPT teacher head0.238
Teacher spread0.218 · 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