Studies on Rheocasting Using Cooling Slope
Bibliographic record
Abstract
In the present work, a cooling channel is employed to produce semi-solid A356 alloy slurry. To understand the transport process involved, a 3D non-isothermal, multiphase volume averaging model has been developed for simulation of the semi-solid slurry generation process in the cooling channel. For simulation purpose, the three phases considered are the parent melt, the nearly spherical grains and air as separated but highly coupled interpenetrating continua. The conservation equations of mass, momentum, energy and species have been solved for each phase and the thermal and mechanical interactions (drag force) among the phases have been considered using appropriate model. The superheated liquid alloy is poured at the top of the cooling slope/channel, where specified velocity inlet boundary condition is used in the model, and allowed to flow along gravity through the channel. The melt loses its superheat and becomes semisolid up to the end of cooling channel due to the evolving -Al grains with decreasing temperature. The air phase forms a definable air/liquid melt interface, i.e. free surface, due its low density. The results obtained from the present model includes volume fractions of three different phases considered, grain evolution, grain growth rate, size and distribution of solid grains. The effect of key process variables such as pouring temperature, slope angle of the cooling channel and cooling channel wall temperature on temperature distribution, velocity distribution, grain formation and volume fraction of different phases are also studied. The results obtained from the simulations are validated by microstructure study using SEM and quantitative image analysis of the semi-solid slurry microstructure obtained from the experimental set-up.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".