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Evaluating the influence of detailing on the seismic performance of diagonally reinforced coupling beams

2025· article· en· W4411091525 on OpenAlexafffundabout
Amirhossein Amiri, Jeremy Atkinson, Lisa Tobber

Bibliographic record

VenueEngineering Structures · 2025
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsUniversity of British Columbia, Okanagan CampusKelowna General HospitalRead Jones Christoffersen (Canada)
FundersMitacs
KeywordsStructural engineeringDiagonalCoupling (piping)Reinforced concreteDiagonally dominant matrixEngineeringGeologyPhysicsGeometryMathematicsMechanical engineering

Abstract

fetched live from OpenAlex

Diagonally reinforced coupling beams (DRCBs) play a critical role in energy dissipation and ductility in reinforced concrete core walls subjected to seismic forces. This study evaluates the cyclic response of DRCBs and examines potential limitations in US and Canadian design codes. A database of 51 experimental tests is compiled to assess the influence of embedded longitudinal bars (ELB), axial restraints (AR), and confinement details on force-deformation behavior. Results indicate that specimens with AR or ELB exhibit significant overstrength, which can be estimated using sectional analysis and incorporating the flexural contribution of longitudinal bars in calculations. DRCBs without AR or ELB had a median overstrength around 1.25; however, the presence of AR or ELB can increase shear forces by a further 30 to 40 percent. Specimens with low diagonal reinforcement also demonstrated reduced rotational capacity. Based on these findings, a new force design limit is proposed, and it is recommended that seismic codes introduce lower rotational limits for low-aspect ratio coupling beams to better reflect observed performance.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.116
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.243
Teacher spread0.235 · 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 teacher head, 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

Citations2
Published2025
Admission routes3
Has abstractyes

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