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Record W2100392300 · doi:10.5539/jmsr.v2n3p1

Convection Streams and Macrosegregation Couple Phenomena for Dendritic Solidification Defects in Casting Processes

2013· article· en· W2100392300 on OpenAlexvenueno aff
Mostafa Omar El‐Bealy

Bibliographic record

VenueJournal of Materials Science Research · 2013
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsnot available
FundersKungliga Tekniska HögskolanDeutscher Akademischer AustauschdienstAin Shams UniversityMassachusetts Institute of Technology
KeywordsEquiaxed crystalsMaterials scienceIngotConvectionThermalHeat transferMetallurgyCastingMechanicsWork (physics)AluminiumAlloyThermodynamics

Abstract

fetched live from OpenAlex

An investigation has been performed to study the effects of convection streams and the movement of dendritic solid on the macrosegregation in equiaxed structure of aluminium cast ingots. The investigation combined laboratory work, metallographic examination and mathematical modelling. The laboratory work involved different superheats for Al-10%Si alloy cast ingots. The measurements of grain size of equiaxed crystals and macro-segregation distributions have been conducted to verify the solidification model by using the metallographic study combined macro/micro-structural evolution of cast ingot samples. Two-dimensional mathematical model of fluid flow and heat transfer has been developed to characterise the natural convection streams, thermal fields and macro-segregation distributions taken into account the effect of dendritic solid movements. The model predictions were compared to measurements of cooling curves and macro-segregation distributions where the reasonable agreements were found. The formation of macro-segregation phenomenon has been studied and discussed based on convection streams, the movements of dendritic solid and mushy permeability. Also, some typical cases in conventional casting processes related to increase the occurrence of dendritic solidification defects have been discussed.

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 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)0.002
metaresearch head score (Gemma)0.001
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 score0.008
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.044
GPT teacher head0.315
Teacher spread0.270 · 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 teacher head, 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

Citations3
Published2013
Admission routes1
Has abstractyes

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