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Record W4400961972 · doi:10.1061/jpsea2.pseng-1625

Numerical Investigation of Strain Variations along Steel Pipelines in Four-Point Bending Tests

2024· article· en· W4400961972 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

VenueJournal of Pipeline Systems Engineering and Practice · 2024
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsQueen's University
Fundersnot available
KeywordsPipeline transportStructural engineeringBendingGeotechnical engineeringEngineeringThree point flexural testGeologyForensic engineeringMaterials scienceMechanical engineering

Abstract

fetched live from OpenAlex

Four-point bending tests have been widely applied for investigating flexural behavior of different materials. However, there are no guidelines or standards relating to four-point bending tests for pipes. A steel pipe with a diameter of 154 mm and 3.4-mm wall thickness was instrumented with distributed fiber-optic strain sensors and tested in four-point bending. The measured strains at the crown, springlines, and invert deviated from results calculated using beam theory. This strain deviation is investigated using numerical analyses, and it is found that local deformations along the length of the pipe due to concentrated loads at load and support locations contributed to the deviation. Parametric studies are conducted using different geometries of wood support blocks, specimen lengths, and pipe thicknesses to investigate their impact on the strain distribution with the pipe. Recommendations for reducing the strain deviation at the midspan of the specimen are given for four-point bending tests carried out on the steel pipes.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.548
Threshold uncertainty score0.538

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.265
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