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Record W4241704257 · doi:10.32920/ryerson.14635773.v1

RBS moment connection analysis using a solid model

2021· preprint· en· W4241704257 on OpenAlexaff
Mikaela Coello-Mena

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsFlangeStructural engineeringWeldingConnection (principal bundle)Beam (structure)Ductility (Earth science)Materials scienceMoment (physics)Stress (linguistics)BrittlenessPredictabilitySection (typography)Joint (building)Deformation (meteorology)EngineeringComputer scienceComposite materialCreepMathematicsPhysics

Abstract

fetched live from OpenAlex

The unpredictability of the steel beam welding connection has led to many solutions, including the are of focus for this research Reduced Beam Section ( Moment Connections The RBS in steel moment connection facilitates the calculation and predictability of failure in design The RBS section is created by cutting out part of the flanges in a beam This creates a plastic hinge where the beam will fail first 1 This creates a model of predictability on the durability and strength of the beams Creating a RBS connection increases the overall ductility of the steel frame The RBS section reduces the flange width which causes stress concentration on the reduced section and this then lowers the stress on the welds. The lower stress then prevents unexpected brittle fracture in the welding a predicted plastic deformation of the RBS section during a seismic event 2 3 The research is focused on optimizing the RBS connection Finite models will be created using ANSYS to investigate how different RBS connections react in different situations and what is the most efficient design in terms of safety and cost.

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 categoriesMeta-epidemiology (narrow)
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 score0.331
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
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 head0.028
GPT teacher head0.270
Teacher spread0.242 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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