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Record W1979490424 · doi:10.1364/ao.45.003372

Distributed Brillouin fiber sensor for detecting pipeline buckling in an energy pipe under internal pressure

2006· article· en· W1979490424 on OpenAlexaff
Lufan Zou, Xiaoyi Bao, Fabien Ravet, Liang Chen

Bibliographic record

VenueApplied Optics · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBucklingMaterials scienceInternal pressureTension (geology)BendingCylinder stressPressure sensorCompression (physics)Ultimate tensile strengthBrillouin zoneStructural engineeringComposite materialOptics

Abstract

fetched live from OpenAlex

A distributed Brillouin fiber sensor has been employed to detect localized pipe-wall buckling in an energy pipe by measuring the longitudinal and hoop strain distributions along the outer surface of the pipe for the first time. The locations of the localized pipe-wall buckling are found and distinguished using their corresponding strain-load data. The formation of the buckling process for the compression and tension characters is studied in the longitudinal and hoop directions. For the pipe with internal pressure, concentric load, and bending load, a localized pipe-wall buckling takes place away from the middle of the pipe on the compressive side and a strain peak with an overall buckling occurs on the tensile side according to the longitudinal strain distributions along the pipe. Different strains on two neutral lines are also observed in the hoop strain distribution, which should be caused by the pipe weld joint.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.009
GPT teacher head0.221
Teacher spread0.212 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations41
Published2006
Admission routes1
Has abstractyes

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