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Record W2000327325 · doi:10.1115/pvp2008-61795

Comparison of Neutron Diffraction Residual Stress Measurements of Steel Welded Repairs With Current Fitness-for-Purpose Assessments

2008· article· en· W2000327325 on OpenAlexfundno aff
Anna Paradowska, John W Price, T. R. Finlayson, R. B. Rogge, Ronald L. Donaberger, Raafat N Ibrahim

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWelding Techniques and Residual Stresses
Canadian institutionsnot available
FundersAustralian Research CouncilMonash UniversityNational Research Council CanadaAustralian GovernmentAustralian Nuclear Science and Technology Organisation
KeywordsResidual stressWeldingMaterials scienceNeutron diffractionCarbon steelStringerDiffractionComposite materialStress (linguistics)Structural engineeringMetallurgyCorrosionOpticsEngineering

Abstract

fetched live from OpenAlex

In this research the neutron diffraction technique was used to investigate the residual stress distributions in carbon steel components with weld repairs. Two full penetration weld repairs were studied using a) the stringer bead and b) the temper bead weld techniques in 25 mm thick plate. The welds were not post weld heat treated. The focus of the measurements is on the values of the sub-surface and through-thickness strain/stress variation near the middle of the weld and the toe. The experimental results showed that both processes had high residual stresses particularly through the thickness. The measurements were compared with current fitness-for-purpose approaches, such as BS7910 and R6 showing that these approaches underestimated and overestimated the stresses in various regions.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.087
GPT teacher head0.347
Teacher spread0.260 · 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

Citations8
Published2008
Admission routes1
Has abstractyes

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