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Stress Analyses of Deep Plate Girders Used at Oil and Gas Facilities with Rectangular Web Penetrations

2011· article· en· W2106355258 on OpenAlexaffabout
Osama Bedair

Bibliographic record

VenuePractice Periodical on Structural Design and Construction · 2011
Typearticle
Languageen
FieldEngineering
TopicMechanical stress and fatigue analysis
Canadian institutionsAlberta Energy
Fundersnot available
KeywordsGirderStructural engineeringCurvatureStiffnessRadius of curvatureAspect ratio (aeronautics)Stress (linguistics)EngineeringStress concentrationFinite element methodMaterials scienceComposite materialGeometryMathematics

Abstract

fetched live from OpenAlex

Rectangular openings in structural members are used to allow the passage of services. Special design considerations are required to compensate for the reduction in stiffness and to minimize fatigue cracks in the web. The paper investigates the behavior of deep plate girders with rectangular openings with applications to oil and gas facilities. An efficient numerical procedure is first presented for analysis of webs with rectangular penetrations. The limitations of the current AISC guidelines and Canadian design procedures are also highlighted. Recommendations are proposed for structural engineers to minimize web stresses in the girder. The influence of these penetrations on the performance of the plate girder is also illustrated for several loading conditions. It is shown that for openings with aspect ratios (α/β)>1, the stress decreases as the opening radius of curvature (r) increases. Also, the location of the maximum stress is largely influenced by the opening aspect ratio (α/β). It is also shown that a slow increase in the web maximum stress results when the opening curvature (r)<40 mm. For plate girders under shear loading, the web stress decreases by increasing the opening curvature (r).

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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

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 head0.042
GPT teacher head0.256
Teacher spread0.215 · 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 designSimulation or modeling
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

Citations10
Published2011
Admission routes2
Has abstractyes

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Same venuePractice Periodical on Structural Design and ConstructionSame topicMechanical stress and fatigue analysisFrench-language works237,207