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Record W4394777796 · doi:10.62913/engj.v47i1.974

Impact of Diaphragm Behavior on the Seismic Design of Low-Rise Steel Buildings

2010· article· en· W4394777796 on OpenAlexafffundabout
Colin A. Rogers, Robert Tremblay

Bibliographic record

VenueEngineering Journal · 2010
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsMcGill UniversityPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDeckBracingStructural engineeringRoofEngineeringTension (geology)Seismic analysisStiffnessDiaphragm (acoustics)BraceCompression (physics)Geotechnical engineeringMaterials science

Abstract

fetched live from OpenAlex

Modern building codes allow engineers to use reduced seismic loads in design provided that the seismic load resisting system (SLRS) of the structure is adequately designed and detailed to withstand strong ground shaking through ductile inelastic response. This approach has been adopted by the North American model codes which typically include special provisions to achieve satisfactory inelastic seismic performance. Single-story buildings often incorporate a steel roof deck diaphragm that is relied on to transfer lateral loads to the vertical bracing bents. The vertical braces are usually selected as the energy dissipating fuse element, while the diaphragm and other elements in the SLRS should be designed such that their capacity exceeds the nominal resistance of the braces. Steel bracing members designed for compression inherently possess significant reserve strength when loaded in tension, which means that large brace tension loads must be considered in the design of the surrounding protected structural components. Capacity design seismic provisions have led to the need for much thicker roof deck panels and more closely spaced diaphragm connection patterns compared with past practice in Canada. This paper describes the current U.S. seismic design approach and provides examples as it is applied to single-story buildings and their diaphragms. An overview of the related aspects of an on-going research project on the flexibility and ductility of the roof diaphragm in low-rise steel buildings is also included.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0020.000

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 head0.008
GPT teacher head0.217
Teacher spread0.209 · 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

Citations5
Published2010
Admission routes3
Has abstractyes

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