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Record W4399527761 · doi:10.1061/jsendh.steng-12762

RHS Cross-Connections with Fully Offset Branches in Tension

2024· article· en· W4399527761 on OpenAlex
Xiao Ding Bu, Vartkes Davidian, Jeffrey A. Packer, Wei Li

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Structural Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOffset (computer science)Tension (geology)Computer scienceStructural engineeringMaterials scienceEngineeringComposite materialProgramming language

Abstract

fetched live from OpenAlex

This paper primarily presents an investigation into rectangular hollow section (RHS) cross- (or X-) connections with the branches fully laterally offset and loaded in axial tension. A set of 10 full-scale experimental specimens, carefully fabricated with noncritical welds, are tested in the laboratory, and the results are used to validate nonlinear finite-element models. To enhance the range of available data, the calibrated models are varied in an expanded parametric numerical study. A chord failure limit-state model based on a yield-line mechanism, which was identified in prior research on branch compression loading, is verified herein for branch tension loading. Furthermore, the limit state of branch failure is investigated by means of the combined experimental and numerical database produced. Design recommendations for laterally offset cross-connections loaded under branch tension, based on chord and branch failure modes, are presented. The application of current design recommendations for traditional cross-connections (with centered branches) to connections with full-width branches and laterally offset branches is also evaluated.

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.

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 score0.102
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.004
GPT teacher head0.212
Teacher spread0.208 · 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