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Record W3018194469 · doi:10.1139/cjce-2019-0642

Analytical study of the seismic performance of all-steel buckling-restrained braces with H-shaped cores

2020· article· en· W3018194469 on OpenAlexvenueno aff
Ali Mansouri, Ghasem Moosavi

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBucklingStructural engineeringParametric statisticsFinite element methodStiffnessBraceCore (optical fiber)Yield (engineering)Stress (linguistics)Materials scienceCompression (physics)EngineeringComposite materialMathematics

Abstract

fetched live from OpenAlex

The seismic performance of an H-shaped core buckling-restrained brace (HBRB) is evaluated through detailed finite element analysis. The numerical model is validated against available experimental data and a parametric study is carried out to investigate the effect of influential parameters on the cyclic behavior and failure modes of HBRB. Several design parameters including the yielding length ratio, the constrained length, the presence of stiffeners and their thicknesses, the length of the transition region, and the gap size are considered in the parametric investigation. Based on the analysis results reducing the yielding length of HBRB increases its post-yield stiffness and the axial strain and stress of the H-section core. Since buckling of the unconstrained region was observed in HBRBs with insufficient stiffener thickness, an analytical method is proposed for evaluating the sufficiency of stiffeners by estimating the critical buckling load of HBRB as a three-segment stepped compression member.

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.011
GPT teacher head0.184
Teacher spread0.172 · 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

Citations12
Published2020
Admission routes1
Has abstractyes

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