Forced Convection in Porous Media Using Al2O3 and TiO2 Nanofluids in Differing Base Fluids
Bibliographic record
Abstract
The following work presents a numerical evaluation of the use of TiO2 and Al2O3 nanofluids operating with ethylene glycol and water as base fluids—as well as an experimental evaluation of Al2O3-water nanofluid. Both numerical and experimental systems were tested and operated under various flow and heat transfer conditions, including four flow rates and three heat fluxes. When compared, the numerical schemes and experimental results showed deviation of under two degrees Celsius. This led the authors to conclude that the numerical scheme accurately reflected the experimental conditions. When all combinations of mixtures were compared numerically, it was found that ethylene glycol provided the highest average Nusselt number, while water offered significantly lower pumping requirements. When comparing nanoparticles, it was found that, in a carrying-fluid of water, TiO2 had superior performance by approximately one percent.
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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".