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Record W4380450663 · doi:10.52202/069179-0161

SEISMIC PERFORMANCE OF BOLTED GLULAM TIMBER BRACE CONNECTIONS WITH INTERNAL STEEL PLATES

2023· article· en· W4380450663 on OpenAlexaffabout
Zoe Baird, Joshua E. Woods, Christian Viau, Ghasan Doudak

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsUniversity of OttawaCarleton UniversityQueen's University
Fundersnot available
KeywordsBraceStructural engineeringBolted jointMaterials scienceEngineeringFinite element method

Abstract

fetched live from OpenAlex

Mass timber braced frame systems achieve their ductility through the brace connections.Canadian design standards currently lack guidance on how to detail bolted brace connections to achieve a target system-level ductility as defined in the National Building Code of Canada.The objective of this research is to develop guidelines on how to detail bolted glulam timber brace connections to achieve moderate or limited ductility.To accomplish this objective, a 4-storey prototype building was designed to determine realistic brace design forces as well as investigate how different parameters (e.g., fastener diameter and number of slotted-in plates) can impact the design of a timber braced frame.Based on the prototype structure, a connection with two internal steel plates was designed and detailed, which included consideration for the fastener slenderness and spacing to achieve ductile behaviour.To validate the performance of the proposed connection, full-scale testing under monotonic and cyclic loading was conducted.This paper discusses the results of the experimental testing, including connection stiffness, strength, ductility, as well as its energy dissipation capacity.

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
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)0.0040.001

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 head0.201
Teacher spread0.192 · 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

Citations5
Published2023
Admission routes2
Has abstractyes

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