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The Influence of Heat Treatments for Laser Welded Semi Solid Metal Cast A356 Alloy on the Fracture Mode of Tensile Specimens

2008· article· en· W2009225115 on OpenAlex
G. Kunene, Gonasagren Govender, L. Ivanchev, R.D. Knutsen, H.P. Burger

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

VenueDiffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena · 2008
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsCanadian Society of Intestinal Research
Fundersnot available
KeywordsMaterials scienceBase metalWeldingSlurryMetallurgyAlloyAluminiumFracture (geology)Ultimate tensile strengthHeat-affected zoneComposite materialButt welding

Abstract

fetched live from OpenAlex

The CSIR rheo-process was used to prepare the aluminium A356 SSM slurries and thereafter plates (4x80x100 mm3) were cast using a 50 Ton Edgewick HPDC machine. Plates in the as cast, T4 and T6 heat treatment conditions which had passed radiography were then butt laser welded. It was found that the pre-weld as cast, T4 and post-weld T4 heat treated specimens fractured in the base metal. However, the pre-weld T6 heat treated specimens were found to have fractured in the heat affected zone (HAZ).

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.002
Research integrity0.0000.001
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 head0.035
GPT teacher head0.297
Teacher spread0.262 · 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