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Record W4240886722 · doi:10.1115/1.2043200

Introduction of the Element Interaction Technique for Welding Analysis and Simulation

2005· article· en· W4240886722 on OpenAlexaff
Ihab F. Z. Fanous, Maher Y. A. Younan, Abdalla S. Wifi

Bibliographic record

VenueJournal of Pressure Vessel Technology · 2005
Typearticle
Languageen
FieldEngineering
TopicWelding Techniques and Residual Stresses
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsWeldingButt weldingMechanical engineeringFillet (mechanics)Electric resistance weldingFinite element methodResidual stressMaterials scienceStructural engineeringEngineering drawingEngineeringMetallurgy

Abstract

fetched live from OpenAlex

The residual stresses generated due to welding in pressure components may have several harmful effects, such as decrease in the resistance to cycling load and corrosive environments. The analysis of the welding process has been developed extensively in two and three dimensions. The element movement technique has been shown to be very effective in simulating the filler material deposition leading to a reduction in the analysis time. However, when attempted for wider fields of applications, it had some limitations, especially when moving the elements toward the base-plate. In this paper, the element interaction technique is introduced utilizing the concepts of both the element movement and element birth techniques. The new technique is verified versus the currently developed procedures. In this technique, the elements of the weld pool are held in place in contact with the elements of the base plate, and the interaction is made to be a function of time. This gave several flexibilities in modeling the welding process. Hence, the technique is then used to analyze simple fillet welding of a plate and circumferential butt welding of a pipe.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.843
Threshold uncertainty score0.218

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 head0.007
GPT teacher head0.259
Teacher spread0.253 · 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
Published2005
Admission routes1
Has abstractyes

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