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Record W3048796593 · doi:10.1007/s40194-020-00966-4

Stress concentration at cruciform welded joints under axial and bending loading modes

2020· article· en· W3048796593 on OpenAlex

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

VenueWelding in the World · 2020
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsUniversity of Waterloo
FundersPolitechnika Bialostocka
KeywordsCruciformWeldingSolid mechanicsStructural engineeringMaterials scienceFinite element methodBendingJoint (building)Stress (linguistics)Fillet (mechanics)Stress concentrationComposite materialEngineering

Abstract

fetched live from OpenAlex

Abstract The paper is concerned with the problem of stress concentration in cruciform fillet welded joints subjected to axial and bending load. Extended numerical analyses were carried out with the help of the finite element method. It made it possible to estimate stress concentration factors K t for a variety of geometrical parameters defining the geometry of cruciform welded joints. It has been found that approximate K t formulas, available in the literature, have two disadvantages, i.e. an unknown accuracy and small range of application with respect to geometrical parameters defining the weld shape. For these reasons, more general and accurate new formulas for stress concentration factors K t have been derived. Even though the present approach is applicable to all types of welded joints, the analysis presented below has been conducted for a cruciform joint with the weld flank angle of θ = 45°. Final solutions have been given in the form of polynomial expressions, and they can be easily used in computer-aided design procedures.

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 score0.121
Threshold uncertainty score0.389

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 head0.024
GPT teacher head0.228
Teacher spread0.203 · 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