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Testing and Analysis of Steel Pipes under Bending, Tension, and Internal Pressure

2009· article· en· W2045268395 on OpenAlexafffund
Istemi F. Ozkan, Magdi Mohareb

Bibliographic record

VenueJournal of Structural Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsUniversity of Ottawa
FundersOntario Innovation Trust
KeywordsBending momentInternal pressureBucklingFinite element methodCurvatureTension (geology)Structural engineeringMaterials scienceShell (structure)Moment (physics)BendingYield (engineering)Pure bendingMechanicsComposite materialEngineeringUltimate tensile strengthMathematicsGeometryPhysicsClassical mechanics

Abstract

fetched live from OpenAlex

This paper reports a full-scale experimental program consisting of six pipe specimens made of X65 material (specified minimum yield strength=448MPa ) with 508mm outer diameter, and a diameter-to-thickness ratio (D∕t) of 81.2 subjected to combinations of bending, axial tension, and internal pressure. The study is aimed at determining whether the pipes are able to attain their modified plastic moment as predicted by analytically derived plastic interaction relations. The moment versus curvature relations, peak moment values, and local buckling behavior of the specimens as obtained from the experiments are documented. The peak moments obtained are compared to the analytically predicted moments. A nonlinear shell finite-element model is also developed using the finite-element analysis (FEA) simulator ABAQUS in order to predict the moment capacity and the local buckling behavior. Test results compare well with FEA results. It is observed that under certain combinations of axial tension and internal pressure, pipes with D∕t=81.2 are able to attain their plastic moment resistances.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.218
Teacher spread0.210 · 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

Citations22
Published2009
Admission routes2
Has abstractyes

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