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Record W4388709589 · doi:10.11159/ijci.2023.010

Finite Element Study of HSS-to-HSS Moment Connection with Eccentricity: Flexural Behavior under Cyclic Loading

2023· article· en· W4388709589 on OpenAlexvenueno aff
Lila Bahadur Khatri, Jianwei Huang

Bibliographic record

VenueInternational Journal of Civil Infrastructure · 2023
Typearticle
Languageen
FieldEngineering
TopicMechanical stress and fatigue analysis
Canadian institutionsnot available
Fundersnot available
KeywordsConnection (principal bundle)Eccentricity (behavior)Finite element methodStructural engineeringFlexural strengthMoment (physics)EngineeringPhysicsPsychologyClassical mechanicsSocial psychology

Abstract

fetched live from OpenAlex

Hollow structural sections (HSS) are suitable for various structural applications, such as columns, bracing members, cladding supports, and truss members.Recently, HSS members have been researched as one type of moment resisting frame systems for structures.Several studies have been conducted on the behaviors of HSS-to-HSS concentric moment connections subjected to cyclic loading, however, studies on the cyclic bending behaviors of eccentric connections are very limited.This paper aims to investigate the effects of the connection eccentricity on the load capacity of the HSS-to-HSS moment connection subjected to cyclic loading by using finite element (FE) simulations.Two connection configurations were examined with different beam width-to-column width ratios (β); both unreinforced and reinforced connections were examined for each configuration.The results from this study showed that the moment capacity of an unreinforced HSS-to-HSS moment connection increases as the connection eccentricity increases, whereas the connection eccentricity has minimal effects on the moment capacity of a reinforced HSS-to-HSS moment connection.Also, with the same connection eccentricity, the connection with a higher beam width-to-column width ratio (β) demonstrates a higher moment capacity for both unreinforced and reinforced moment connections.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.754
Threshold uncertainty score0.462

Codex and Gemma teacher scores by category

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

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 head0.014
GPT teacher head0.266
Teacher spread0.252 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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