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Record W2526211107 · doi:10.1177/1464420715621930

Understanding the occurrence of the surface turbulence in a nonpressurized bottom gating system: Numerical simulation of the melt flow pattern

2015· article· en· W2526211107 on OpenAlexaff
Ali Kheirabi, Amir Baghani, Ahmad Bahmani, Morteza Tamizifar, Parviz Davami, Mohsen Ostad Shabani, Ali Mazahery

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part L Journal of Materials Design and Applications · 2015
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTurbulenceEntrainment (biomusicology)GatingMechanicsMaterials scienceLiquid metalFree surfaceFlow (mathematics)VortexComputer simulationAir entrainmentMetallurgyPhysicsAcoustics

Abstract

fetched live from OpenAlex

Surface turbulence during the filling of the mold triggers the entrainment of oxide films, which appears to be detrimental to the soundness of the final casting. Nonpressurized and bottom-gating systems have been employed in order to avoid such casting defects by reducing the surface velocity of the liquid metal. However, recent studies have shown that the melt front velocity in the mold entrance may exceed the critical value in the nonpressurized and bottom-gating systems. Therefore, a study was conducted on numerical simulation melt flow pattern in nonpressurized and bottom-gating systems. It was noted that the liquid metal enters the gate and then mold cavity with a higher velocity by formation of dead zones and vortex flows in runner's end. Therefore, the current designs based on conventional gating system ratio seem to be not optimized and unable to avoid the surface turbulence. Numerical results were in complete agreement with experimental observations. Understanding the reasons for occurrence of the surface turbulence in nonpressurized and bottom-gating systems provides information on the required steps to improve the design of the gating systems and minimize the entrainment of oxide films during the filling of the mold.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.701
Threshold uncertainty score0.237

Codex and Gemma teacher scores by category

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

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 head0.050
GPT teacher head0.237
Teacher spread0.187 · 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 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".

Quick stats

Citations16
Published2015
Admission routes1
Has abstractyes

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