Ethylene- and Propylene-Glycol Based Nanofluids: A Litterature Review on Their Thermophysical Properties and Thermal Performances
Why this work is in the frame
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Bibliographic record
Abstract
Nanofluids are considered a promising way to improve the heat transfer capability of base fluids. Water is the most commonly-used heat transfer fluid. However, in refrigeration systems, it may be necessary to mix water with either ethylene- or propylene-glycol to lower its freezing point and prevent from ice formation. In the same way, for car radiators or industrial heat exchangers, the boiling point of water can be pushed up by mixing it with glycol-based fluids. The increasing awareness of energy saving and industrial energy efficiency improvement results in the growing interest in ethylene- or propylene-glycol-based nanofluids for applications in various thermal systems. The present paper proposes an extensive review of the most recent and relevant experimental and numerical works on the thermophysical properties and performances of ethylene- or propylene-glycol-based nanofluids. Research perspectives are also provided with the long-term objective that these nanofluids be more widely considered in real industrial applications.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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