Simulation of Forced Convection Ice Slurry Flow in a Heated Tube
Bibliographic record
Abstract
This paper compares the numerically predicted steady state, laminar hydrodynamic and thermal fields of an ice slurry (water with 15% ethanol and 12.26% ice particles) and a homogeneous binary, single phase mixture (water with 17.1% ethanol) entering identical constant temperature tubes (Tw = 274.16 K) with the same temperature (T0 = 264.16 K) and Reynolds numbers (Re = 500). The isothermal length of the tube is preceded and followed by adiabatic zones. The fluids are considered to be Newtonian and the governing partial differential equations are coupled since their properties depend on the temperature and, in the case of the ice slurry, on the ice concentration which is not uniform due to heat transfer. The results show significant differences between local values of the wall shear stress, the friction factor, the bulk temperature and the Nusselt number of these two flows. Specifically, the local Nusselt number for the ice slurry is higher throughout the developing region and its bulk temperature decreases in the downstream adiabatic zone due to radial conduction and an axial increase of the bulk ice concentration.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".