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Fillet Weld Groups Loaded with Out-of-Plane Eccentricity: Simulations and New Model for Strength Characterization

2012· article· en· W1967633286 on OpenAlexfundno aff
Amit Kanvinde, J. Liu, Xiangyang Fu, Ryan Cooke

Bibliographic record

VenueJournal of Structural Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicMechanical stress and fatigue analysis
Canadian institutionsnot available
FundersCanadian Institute of Steel Construction
KeywordsWeldingStructural engineeringFillet weldFinite element methodMaterials scienceMechanicsFillet (mechanics)PlasticityEngineeringPhysicsComposite material

Abstract

fetched live from OpenAlex

The strength of fillet weld groups, loaded with an out-of-plane eccentricity, is controlled by complex interactions of weld yielding, as well as bearing between the connected parts. Current models that characterize connection strength, including those used in North American design specifications, are highly conservative, leading to oversized welds. These models are phenomenological, because the internal stress distribution within the welds is difficult to characterize experimentally. A new model is proposed for characterizing the strength of these connections. The model is based on insights developed from sophisticated finite-element (FE) simulations that feature accurate measurements of weld profiles, multiaxial plasticity, and simulation of contact and gapping phenomena that strongly influence connection response. The FE simulations reveal that current models do not reflect key aspects of force transfer within the connection, especially on the compression side. The proposed model incorporates these insights by using stress profiles and mechanisms consistent with those implied by the FE simulations. The model is evaluated against 79 experiments from three test programs. It is determined that the new model greatly reduces the conservatism of the existing models, resulting in an average test-to-predicted ratio of 1.01. This is in contrast to previous models, for which the average test-to-predicted ratios are in the range of 1.33–1.77. The efficacy of the proposed model is analyzed with respect to various parameters, and its limitations are outlined.

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 score0.448
Threshold uncertainty score0.358

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 head0.020
GPT teacher head0.218
Teacher spread0.198 · 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

Citations3
Published2012
Admission routes1
Has abstractyes

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