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Record W16129993

FEM calculation of frequencies variation caused by residual stress distribution in welded structures

2007· article· en· W16129993 on OpenAlexaff
Olivier Charette, Henri Champliaud, Marc Thomas

Bibliographic record

Venueinternational conference on Modelling and simulation · 2007
Typearticle
Languageen
FieldEngineering
TopicWelding Techniques and Residual Stresses
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsResidual stressWeldingFinite element methodStress (linguistics)Structural engineeringResidualMaterials scienceComputer scienceEngineeringComposite materialAlgorithm
DOInot available

Abstract

fetched live from OpenAlex

All manufacturing and forming processes induce residual stress in mechanical parts and experiments have shown that residual stress distribution affects the natural frequencies in structures. In practice, measuring residual stress is still difficult, and cannot always be done without destroying the part. Even if some non-destructive methods exist for measuring the residual stress, they cannot be applicable on all parts and results are sometimes more qualitative than quantitative. Numerical methods such as the finite element method (FEM) provide tools for predicting the state of stress resulting from welding, and using modal analysis has appeared as an interesting alternative for measuring and predicting the residual stress. Simulations of welding on a plate have been done using the commercial software ANSYS. Results show that after the welding simulation, the natural frequencies have risen by about 5 to 7 percent in comparison with a free of stress plate.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.035
GPT teacher head0.287
Teacher spread0.252 · 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 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

Citations1
Published2007
Admission routes1
Has abstractyes

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