Combined Eulerian–Eulerian Multiphase Frost model and solidification and melting model to predict the cooling performance of subcooled eutectic plates
Bibliographic record
Abstract
To limit the environmental footprint of refrigeration, transport of frozen goods based on natural fluids and phase change materials (PCMs) may be a promising solution. However, frost formation on the surface of the PCM encasing might limit the heat exchange and overall efficiency of the frozen food transport. The present work reports the numerical modeling of the heat and mass transfer for a flat plate cooled by a melting PCM located inside an air channel on which frost develops. Eulerian–Eulerian multiphase model is employed in conjunction with the k − ω Shear Stress Transport (SST) model to simulate the frost formation on the surface of the PCM encasing. It is first favorably validated against a number of published experimental and numerical data. Then the melting model based on the so-called enthalpy-porosity approach is applied as a User-Defined Function (UDF). The solidification and melting model as an applied UDF has been also validated against experimental and numerical works for lauric acid as PCM. The combined Eulerian–Eulerian Multiphase frost model and the solidification and melting model show that the flow must be below the PCM rather than above, in order to promote the formation of the Rayleigh–Bénard convection cells within the PCM when the melting process begins. Otherwise, the heat released from the frost formation on the surface of the PCM encasing and the heat transferred from the high temperature humid air are not effectively diffused within the PCM and results in localized high-temperature zones within the PCM. • Numerical model analyzes frost on a PCM-encased plate in an air channel. • Frost on PCM encasing can hinder heat exchange with the surrounding air. • The multiphase model simulates frost formation, validated by experimental and numerical data. • The melting model shows that flow under PCM prevents localized high-temperature zones.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".