FIXED-GRID SIMULATIONS OF STEADY, TWO-DIMENSIONAL, ICE-WATER SYSTEMS WITH LAMINAR NATURAL CONVECTION IN THE LIQUID
Bibliographic record
Abstract
A numerical investigation of steady, two-dimensional, ice-water systems with laminar buoyancy-driven natural convection in the water and conduction in the ice is presented. The calculation domains were rectangular enclosures, cooled and heated on opposite vertical side walls, and insulated (adiabatic) on the top and bottom walls. The long-term goal is to contribute to the development of mathematical models and numerical solution methods suitable for use as cost-effective computational tools in the design of enhanced ice-water seasonal cold-storage (IWSCS) systems. A fixed-grid, co-located, finite volume method (FVM) was adapted for use in this work. Predictions were obtained using a variable-property model (VPM) and also a constant-property model (CPM). In simulations with the CPM, all properties of liquid water, except its density, were evaluated at several different reference temperatures and assumed constant, and the thermal conductivity of ice was pegged to its value at the melting temperature. The reference temperature that leads to the lowest differences between the results yielded by the VPM and CPM was determined, and it is the main contribution of this work. The reasons for seeking such a reference temperature are two-fold: 1) the CPM facilitates cost-effective simulations for designing IWSCS systems optimized for specific applications; and 2) porous metal foams are often embedded in IWSCS systems to improve their performance, and practical volume-averaged approaches to the modeling of fluid flow and heat transfer in such composite systems are usually based on a CPM. The computed streamlines, water-ice interface positions, and values of the average Nusselt number on the hot wall are also presented for the cases considered.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".