MétaCan
Menu
Back to cohort
Record W4386640972 · doi:10.1002/cepa.2336

Bracing requirements for a semi‐rigidly connected column considering column lateral stiffness and initial curvature

2023· article· en· W4386640972 on OpenAlexafffund
Linbo Zhang, Lei Xu

Bibliographic record

Venuece/papers · 2023
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBraceBracingStructural engineeringStiffnessCurvatureColumn (typography)BucklingFinite element methodEngineeringConnection (principal bundle)MathematicsGeometry

Abstract

fetched live from OpenAlex

Abstract This paper theoretically assesses the required brace stiffness and strength for a semi‐rigidly connected column with a lateral brace at the mid‐height, by introducing a half‐length column model and adopting the concept of storey‐based buckling. Unlike that in Winter's model, column lateral stiffness and initial curvature associated with column initial out‐of‐straightness are accounted for. A coefficient, which is a function of applied load and column end connection stiffness, is introduced to characterize the effect of column initial curvature on bracing requirements. By comparing the results obtained from the analytical method and current structural steel and cold‐formed steel design standards, it has been found that the required brace strength stipulated in these standards are generally conservative in various degrees for design loads; however, the required brace stiffness should be increased if the effect of column initial curvature is considered. The results obtained from the proposed approach are verified against the finite element analysis, indicating that the proposed approach provides an accurate evaluation of required brace strengths for semi‐rigid columns and is recommended to be adopted for engineering practice.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.020
GPT teacher head0.261
Teacher spread0.240 · 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

Explore more

Same venuece/papersSame topicStructural Load-Bearing AnalysisFrench-language works237,207