A comparative study on best configuration for heat enhancement using nanofluid
Why this work is in the frame
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Bibliographic record
Abstract
Nanofluid is a class of fluid which enhances the heat extraction from a hot surface. The concentration of nanoparticles enhances the conductivity of the fluid; however, it may change the fluid from Newtonian to a non-Newtonian. In addition, the type of base fluid plays a significant role in heat extraction. In this present study, three different configurations (porous block, porous straight channel and porous wavy channels) setups were investigated numerically using four different types of nanofluids mainly, 0.5% vol Al2O3/Water, 0.5% vol TiO2/Water, 0.5% vol Al2O3/Ethylene Glycol and 0.5% vol TiO2/Ethylene Glycol. Different parameters were assessed such as the local Nusselt number, the friction coefficient, the pressure drop, the temperature uniformity and the efficiency index. It was found that each nanofluid have a different performance for different configuration. If one relies on the efficiency index which combine the Nusselt number and the pressure drop, the nanofluid of 0.5% vol Al2O3 in water base provided the highest efficiency index.
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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 it