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Record W4394745785 · doi:10.62913/engj.v44i2.906

Improving the Seismic Stability of Concentrically Braced Steel Frames

2007· article· en· W4394745785 on OpenAlexafffundabout
Robert Tremblay, Laure Poncet

Bibliographic record

VenueEngineering Journal · 2007
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsPolytechnique MontréalDessau-Soprin (Canada)Research Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBucklingBraced frameStructural engineeringBracingInstabilitySeismic analysisModalStability (learning theory)EngineeringCompression (physics)Frame (networking)BraceComputer scienceMaterials scienceMechanical engineeringComposite materialMechanics

Abstract

fetched live from OpenAlex

An analytical study was performed to examine the seismic stability of multi-story concentrically braced steel frames. The building height was varied from 4 to 16 stories and three braced frame systems were studied: conventional braced frames, buckling-restrained braced frames, and dual buckling-restrained braced frames. All structures were designed according to Canadian seismic provisions. Different force modification factors were used and both the equivalent static load procedure and the modal response spectrum analysis were considered in design. P-delta effects were accounted for in the design of some of the buildings. The performance of the various structures is evaluated and compared by means of incremental dynamic analysis. The results show that the potential for instability for conventional braced frames is higher for taller structures or when the design loads are reduced. Tall buckling-restrained braced frames were also found to be prone to dynamic instability. Dual buckling-restrained braced frames exhibit a more robust response and represent a promising solution for tall braced steel frames.

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: Bench or experimental · Consensus signal: Bench or experimental
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 science0.0000.000
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 head0.006
GPT teacher head0.193
Teacher spread0.187 · 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

Citations20
Published2007
Admission routes3
Has abstractyes

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