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Plastic Interaction Relationships for Square Hollow Structural Sections: Lower Bound Solution

2004· article· en· W1981652973 on OpenAlexaff
Magdi Mohareb, Istemi F. Ozkan

Bibliographic record

VenueJournal of Structural Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSquare (algebra)Bending momentPlasticityShearing (physics)MathematicsUpper and lower boundsBendingShear forceStructural engineeringMathematical analysisMaterials scienceGeometryEngineeringComposite material

Abstract

fetched live from OpenAlex

General interaction relationships for hollow structural square sections subjected to general combinations of normal force, twisting moments, biaxial bending moments, and biaxial shearing forces are developed. The lower bound theorem of plasticity is employed to obtain the fully plastic resistance of the section as determined by the maximum distortional energy density criterion. Previously established interaction relationships for hollow structural sections subjected to bending moments, axial force, and twisting moments are recovered as a special case of the general solution. The developments are expressed as universal, nondimensional relationships suitable for limit state design. Consideration is given to the limits of applicability of the interaction relations. Simplifying assumptions are made and their effects are discussed. A stress resultant transformation scheme is developed in order to reduce the number of interaction relations to be developed from 20 cases to only three fundamental cases.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.015
GPT teacher head0.232
Teacher spread0.217 · 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

Citations2
Published2004
Admission routes1
Has abstractyes

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