Arbitrary shaped ice particle melting under the influence of natural convection
Bibliographic record
Abstract
This work is devoted to numerical simulations of an arbitrary shaped ice particle melting inside water under the influence of natural convection. Specifically, four different shapes of the ice particle have been studied: sphere, cylinder, cross shaped cylinder, and irregular sphere with radial bumps on its surface. A 2D axisymmetric particle‐resolved numerical model has been employed on a fixed grid to study the detailed melting dynamics of an ice particle. The solid‐liquid interface is treated as a porous medium characterized by the permeability coefficient which is used to damp the velocity values inside the interface. The model results have been compared with an existing experimental results produced by A. Shukla et al. (Metal Mater Trans B. 2011; 42(1):224–235). Very good agreement between our predictions and experimental data have been achieved. Based on the analysis of numerical simulation results, melting process is found to advance through two distinct regimes, namely, establishment of the natural convection and active melting of ice particle exhibiting substantial amount of fluid‐particle interactions. A set of dimensionless parameters have been identified to distinguish between regimes. Finally, we developed a semi‐empirical to predict the melting of any arbitrary shaped ice particle and validated it against the particle‐resolved numerical simulation and experimental results. The comparison showed good agreement. Finally, the presented semi‐empirical model can be used as sub‐grid model in Euler‐Lagrange based numerical models to study the phase change phenomena in particulate flow systems. © 2017 American Institute of Chemical Engineers AIChE J, 63: 3158–3176, 2017
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".