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Record W4386860279 · doi:10.3390/engproc2023043031

O.I.C.-Based Design of Aluminum Circular Hollow Sections under Compression or Pure Bending

2023· article· en· W4386860279 on OpenAlexafffund
Liya Li, Sahar Dahboul, Prachi Verma, Pampa Dey, Mario Fafard, Nicolas Boissonnade

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsUniversité LavalNanoQuébec (Canada)Université de Sherbrooke
FundersFonds de recherche du Québec – Nature et technologies
KeywordsBendingBucklingStructural engineeringEurocodeCompression (physics)AluminiumShell (structure)Finite element methodStrain hardening exponentPure bendingMaterials scienceHardening (computing)Yield (engineering)AlloyComposite materialEngineering

Abstract

fetched live from OpenAlex

This paper investigates the ultimate resistance of aluminum circular hollow sections (C.H.S.) under simple load cases as affected by local buckling and material strain hardening. Following the development of advanced non-linear shell finite element models and their validation against existing test data, extensive non-linear numerical analyses were carried out, varying several key parameters such as alloy types, load case (compression or pure bending) and various section dimensions. The numerical results are used as references to analyze the structural performance of aluminum C.H.S., and to assess the accuracy of design equations based on the Overall Interaction Concept (O.I.C.). The O.I.C.-based proposal is shown to yield more accurate, consistent, and continuous resistance predictions than Eurocode 9 recommendations.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.045
GPT teacher head0.255
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 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

Citations1
Published2023
Admission routes2
Has abstractyes

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