A submodel for spherical particles undergoing phase change under the influence of convection
Bibliographic record
Abstract
ABSTRACT This work is devoted to the development and validation of a subgrid model describing heat transfer between the bulk flow and moving particles undergoing phase change under the influence of forced and free convection. Such kinds of submodels play the role of “scale bridges” between microscale (e.g. interfacial heat transfer) and macroscale (e.g. bulk flow) phenomena. Applied to multiscale modelling of particulate flows with phase change phenomena, our model serves as a coupling between equations describing particle movement in Lagrangian space and the mass and heat conservation equation defining melt flow in Eulerian space. The input parameters in our model are the particulate Reynolds number (Re), the Grashof number (Gr), the Stefan number (Ste), and the Prandlt number (Pr). The model has been validated against experimental data published recently in the literature applied to the melting of ice spheres under different flow conditions. Good agreement between our model predictions and published experimental data (Shukla et al.[16] and Hao and Tao[14]) is observed.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".