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Record W4386962889 · doi:10.3390/engproc2023043035

Behaviour and Design of I-Shaped Aluminium Sections

2023· article· en· W4386962889 on OpenAlexaffabout
Sahar Dahboul, Tristan Coderre, Liya Li, Nicolas Boissonnade

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsUniversité de SherbrookeUniversité Laval
Fundersnot available
KeywordsEurocodeAluminiumParametric statisticsConsistency (knowledge bases)Structural engineeringFinite element methodStrain hardening exponentReliability (semiconductor)Computer scienceEngineeringMaterials scienceMathematicsMetallurgyStatistics

Abstract

fetched live from OpenAlex

Aluminium alloys exhibit a non-linear stress–strain material response with significant strain-hardening effects. Whereas the latter shall be considered in the design of aluminium elements, they are largely ignored in most design codes, such as Eurocode 9 and the Canadian Standards. Preliminary studies on typical aluminium I-shapes indeed indicated that as much as 40% extra resistance could be reached through more accurate and appropriate design recommendations. Accordingly, an original design approach based on the Overall Interaction Concept (O.I.C.) is developed to better account for the actual behaviour of aluminium structural shapes. In this respect, non-linear finite element models are developed within ABAQUS and further validated against experimental data. Subsequently, comprehensive parametric studies are performed to collect numerical reference results, and comparisons are performed with resistance predictions from well-known design standards. The performance of the newly developed O.I.C.-based design approach is shown to significantly improve accuracy, safety, consistency, and reliability levels.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.621
Threshold uncertainty score0.192

Codex and Gemma teacher scores by category

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 science0.0000.000
Research integrity0.0000.000
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 head0.023
GPT teacher head0.231
Teacher spread0.208 · 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 teacher head, 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

Citations0
Published2023
Admission routes2
Has abstractyes

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