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Impact properties of Al-Si foundry alloys

2000· article· en· W2559323617 on OpenAlexaff
F. Paray, B. Kulunk, J. E. Gruzleski

Bibliographic record

VenueInternational Journal of Cast Metals Research · 2000
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsMcGill University
Fundersnot available
KeywordsEutectic systemMaterials scienceIntermetallicFoundryAlloyMicrostructureMetallurgyIzod impact strength testImpact energySiliconFracture (geology)Composite material

Abstract

fetched live from OpenAlex

The impact properties of 413, 356, 319 and 332 alloys were assessed using instrumented impact testing equipment. The fracture responses of the impact specimens were studied in terms of total absorbed energy, crack initiation and crack propagation energies. The influence of the microstructure on the impact strength was investigated. The effects of chemical modification and/or heat treatment of 356 alloy were examined by testing unmodified and Sr modified samples in the as-cast condition and T6 condition with different solution heat treatment times and artificial aging times.In the case of the 413 and 356 alloys, the impact strength was found to be influenced by the amount, size and morphology of the eutectic silicon. On the other hand, the intermetallic phases such as CuAl2 in 319 and 332 alloys exert a greater influence than does the eutectic silicon. Solution heat treatment of 356 alloy was found to have a profound effect on the impact properties.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0040.001

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 head0.096
GPT teacher head0.416
Teacher spread0.321 · 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

Citations45
Published2000
Admission routes1
Has abstractyes

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