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Record W1558795765 · doi:10.1115/imece2014-36748

Numerical Study of a Direct Chill Slab Caster Fitted With a Porous Filter for Aluminum Alloy AA-2024

2014· article· en· W1558795765 on OpenAlexaff
Mainul Hasan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsMcGill University
Fundersnot available
KeywordsMaterials scienceTurbulenceMechanicsHeat transferCasterTurbulence modelingCastingSump (aquarium)Darcy–Weisbach equationFluid dynamicsPorous mediumPorosityMetallurgyComposite materialEngineeringPhysics

Abstract

fetched live from OpenAlex

The present study is undertaken to model an industrial-sized vertical Direct Chill (DC) slab caster fitted with a porous filter near the melt entry region. The modeled alloy is a high strength aluminum alloy AA-2024 which is extensively used by the aerospace industry. The model has incorporated the 3-D turbulent aspect of the melt flow and heat transfer in the liquid sump and the mushy region solidification aspect of this long solidification range (136° C) alloy. The verified 3-D turbulent CFD in-house code is used to study the effects of various parameters of this casting process in order to gain some fundamental understanding of the melt flow and solidification behavior of the process. The studied caster consists of a popular ‘hot-top’ mold fitted with a porous filter above which molten aluminum alloy is delivered with a constant flow-rate across the entire hot-top. Because of two-fold symmetry, a quarter of the domain of the caster is modeled to save computational costs and time. A staggered control volume based finite-difference scheme is used to solve the non-dimensional modeled equations and the associated boundary conditions. The turbulent aspect of the flow in the porous filter is modeled using the latest suggested version of the Brinkman-Forcheimer extended form of Darcy equation for a porous media. The turbulent melt flow and solidification heat transfer in the clear fluid region are modeled using a low Reynolds number version of the k–ε eddy viscosity model. Computed results for the steady-state phase of the casting process are presented for four casting speeds, varying from 100 to 220 mm/min, for three metal-mold contact regions, varying from 20 to 50 mm and for three metal-mold convective heat transfer boundary conditions, varying from 1.0 to 4.0 kW/m2K and all for a fixed inlet melt superheat of 64° C. The permeability of the filter is also varied to ascertain its influence on the predicted results. Computed results of the velocity and temperature profiles, the sump depth and mushy region at the centre of the caster as well as the solidification shell thickness at the exit of the mold are provided and discussed. The present work can provide some useful guidelines in designing and optimizing a vertical DC slab caster for producing good quality casts for the common aluminum alloy AA-2024.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
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 score0.040
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.197
Teacher spread0.188 · 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 designSimulation or modeling
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".

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Citations0
Published2014
Admission routes1
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