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Record W2325496662 · doi:10.1061/9780784412367.146

Seismic Behavior of Steel HSS X-Bracing of the Conventional Construction Category

2012· article· en· W2325496662 on OpenAlexaff
Alexandre Gélinas, Robert Tremblay, Ali Davaran

Bibliographic record

VenueStructures Congress 2012 · 2012
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsBracingBraceStructural engineeringQuasistatic processBrittlenessCompression (physics)Connection (principal bundle)Intersection (aeronautics)EngineeringQuasistatic loadingBraced frameTension (geology)Computer scienceMaterials scienceMechanical engineeringFrame (networking)Composite material

Abstract

fetched live from OpenAlex

This paper presents the results of an ongoing research project on the seismic performance of concentrically braced steel frames of the Conventional Construction category designed according to NBCC 2010 and CSA-S16 seismic provisions. The braced frames studied are of the tension-compression X-bracing configuration and special attention is devoted to the response of the connection at the brace intersection point. Numerical simulations were performed to determine the inelastic demand on the braces and brace connections. A test program including four full-scale quasistatic cyclic tests was carried out to verify the findings of the numerical simulations. The results indicate that the behaviour of the bracing members is influenced by the type of mid-connection. In particular, connections with single lap splices at the intersection of the braces may be prone to local instability. In all tests, failure occurred in the connections, indicating that more attention must be paid in design to prevent premature and brittle failure in connections.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.010
GPT teacher head0.226
Teacher spread0.216 · 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

Citations11
Published2012
Admission routes1
Has abstractyes

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