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Record W1965077221 · doi:10.1115/1.4004620

Welding Induced Distortions and Strains of a Built-Up Panel, Experiment and Numerical Validation

2012· article· en· W1965077221 on OpenAlexaff
Christopher Bayley, John Goldak

Bibliographic record

VenueJournal of Pressure Vessel Technology · 2012
Typearticle
Languageen
FieldEngineering
TopicWelding Techniques and Residual Stresses
Canadian institutionsCarleton University
Fundersnot available
KeywordsWeldingFinite element methodMaterials scienceCladding (metalworking)Distortion (music)Residual stressStructural engineeringResidualComposite materialMechanical engineeringEngineeringComputer science

Abstract

fetched live from OpenAlex

Weld build-up or weld cladding is a welding process in which weld metal can be deposited in order to reclaim the material thickness. In certain applications, welding induced distortions must be controlled while simultaneously minimizing welding induced residual strains. In order to examine the relative effect of the weld build-up region on welding induced distortion and residual strains, two panels were fabricated with either a small 100 × 100 × 3 or large 200 × 200 × 3 mm depression that was subsequently filled by welding. During welding, the strains, displacements, and temperature were continuously monitored in order to compare the transient solution with companion finite element method (FEM) models of the same structures. The coupled thermo-mechanical problem was solved using Goldak Technology Inc., vrsuite program, with the level of agreement of the measured distortions, strains, and temperature profiles dependent on their location and history. Both the numerical and experimental tests showed that despite the differences in the geometry, both panels developed the same strain state, although the large welded patch had greater peak value and larger distortions.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.338

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 head0.030
GPT teacher head0.277
Teacher spread0.248 · 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 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

Citations2
Published2012
Admission routes1
Has abstractyes

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