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Record W4391506751 · doi:10.1016/j.tws.2024.111677

Experimental and numerical investigations of Frameless CFSCW under combined in-plane shear and axial loads

2024· article· en· W4391506751 on OpenAlexafffund
S. P. Vaze, T.Y. Yang, F. Bagatini-Cachuço, Xiao Pan

Bibliographic record

VenueThin-Walled Structures · 2024
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStructural engineeringBucklingStiffnessFinite element methodShear (geology)Ductility (Earth science)Materials scienceCold-formed steelShear wallEngineeringComposite material

Abstract

fetched live from OpenAlex

This paper presents a comprehensive evaluation of a novel Cold Form Steel Corrugated Walls (CFSCWs), named Frameless CFSCWs, under combined axial and lateral loads. A series of experimental investigations were carried out on full-scale specimens. The influence of different axial loads on the buckling-failure mode, the peak force capacity, the post-buckling stiffness, and the residual force capacity are presented. Subsequently, robust finite element models were developed to simulate the complex bucking behavior of these Frameless CFSCWs. The results of the experimental and numerical investigations revealed that the lateral force-deformation response of Frameless CFSCW is highly influenced by the axial loads. A linearized backbone curve of the Frameless CFSCWs with different axial loads is proposed. Key design parameters such as overstrength and ductility ratios of the Frameless CFSCW panels are identified. The linearized backbone curve can be used by engineer to design Frameless CFSCWs under different axial loads.

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
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.239
Teacher spread0.230 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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