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Record W2332433390 · doi:10.1115/pvp2011-57957

The Evolution of Stress and Strain Tensors in Welds With Mitigation of Residual Stress and Distortion

2011· article· en· W2332433390 on OpenAlexaff
John Goldak, Mahyar Asadi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWelding Techniques and Residual Stresses
Canadian institutionsCarleton University
Fundersnot available
KeywordsResidual stressCauchy stress tensorDistortion (music)Infinitesimal strain theoryTensor (intrinsic definition)WeldingPlasticityStress (linguistics)Materials scienceStructural engineeringBendingHydrostatic stressDeformation (meteorology)Displacement (psychology)MechanicsGeometryFinite element methodMathematical analysisComposite materialMathematicsEngineeringPhysics

Abstract

fetched live from OpenAlex

By getting the data from an ordered set of Gauss points on the flow line of a material point that passes near the weld pool, the evolution of the stress/strain tensor fields is visualized. The principal plastic strain tensor, principal deviatoric stress tensor, hydrostatic stress and temperature are visualized. This is done for three weld distortion mitigation strategies: i) pre-bending by applying a prescribed displacement, ii) applying a tensile load to the weld and iii) applying side heaters to the weld. Visualizing the evolution of the principal stress and strain vectors gives interesting insight into the mechanics of plastic deformation near a weld pool.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.191
Teacher spread0.183 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2011
Admission routes1
Has abstractyes

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