MétaCan
Menu
Back to cohort

Prediction of welding deformations of large stiffened panels using average plastic strain method

2011· article· en· W2151494658 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

VenueScience and Technology of Welding & Joining · 2011
Typearticle
Languageen
FieldEngineering
TopicWelding Techniques and Residual Stresses
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsMaterials scienceWeldingFillet (mechanics)Structural engineeringComposite materialPlasticityFillet weldStrain (injury)Residual stress

Abstract

fetched live from OpenAlex

Curved or flat stiffened steel panels used in ships and offshore structures are fabricated mainly by fusion welding. It leads to heat induced plastic strains, distortions and residual stresses. These distortions may adversely affect the subsequent fit-up and alignment of the adjacent panels. A solution methodology named average plastic strain method was developed and adopted based on evaluation of average plastic strains of butt and fillet joints of small scale specimens. These were obtained using the conventional thermomechanical analysis. These plastic strains were then used to determine the overall distortions of large stiffened plate panels. The results obtained were compared with those of established inherent strain method for prediction of distortion of large stiffened plate panels. Computational efficiency of the average plastic strain method was found to be comparable with the inherent strain method. However, the accuracy in the plastic strain method was found to be better than that in the inherent strain method.

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)0.001
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 score0.151
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.045
GPT teacher head0.269
Teacher spread0.224 · 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