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Record W2170080265 · doi:10.1002/stco.201410020

Seismic design solutions for connections to tubular members

2014· article· en· W2170080265 on OpenAlexaff
A.Y. Elghazouli, Jeffrey A. Packer

Bibliographic record

VenueSteel Construction · 2014
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBracingDissipative systemConnection (principal bundle)Scope (computer science)Seismic analysisStructural engineeringFrame (networking)Section (typography)Column (typography)EngineeringDesign methodsConstruction engineeringComputer scienceMechanical engineeringBrace

Abstract

fetched live from OpenAlex

Abstract A review of seismic design solutions for connections is presented in this paper, with particular focus on methods that are already “pre‐approved” or “acceptable to code” for use by engineers in steel‐framed structures using hollow sections. This review is intended to illustrate the limited options currently available to structural engineers. The survey mainly covers European and North American design solutions, but the latter are also heavily influenced by Japanese practice. The scope includes both braced frame connections (utilizing hollow sections for the bracing members at least) and unbraced frame connections (utilizing hollow section columns), the latter including both rigid and semi‐rigid beam‐to‐hollow section column connections. Dissipative and non‐dissipative connection types are considered where appropriate. Emphasis is placed on connection configurations and concepts rather than detailed design information, but references to other sources are given for further details. Areas in which there is a paucity of established design guidance are noted, and the review concludes with recommendations for further research and development regarding specific types of connections to hollow sections subjected to seismic loading.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.002

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 head0.018
GPT teacher head0.218
Teacher spread0.200 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations9
Published2014
Admission routes1
Has abstractyes

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