Experimental Investigation of Nanofluid Heat Transfer in a Plate Heat Exchanger
Bibliographic record
Abstract
An experimental study was carried out to determine the forced convective heat transfer and hydraulic characteristics of a chevron-type two-channel industrial PHE when used with a nanofluid. The PHE is composed of two fluid passages formed by three corrugated plates, which have a herringbone pattern and the corrugations are of a trapezoidal shape. Heated water is used on the hot side. On the cold side a mixture of 29nm-diameter CuO nanoparticles in suspension in water is forced. Collected data for the nanofluid side covers two particle volume fractions, 2% and 4.65%, and the range of Reynolds number up to 1000. Results have shown that, for a given Reynolds number, CuO-water nanofluid clearly exhibits a higher friction factor compared to that of water. Calculated Nusselt numbers have shown no significant heat transfer enhancement when using the 2% nanofluid. A decrease of heat transfer was even observed with the 4.65% nanofluid. The laminar-turbulent transition was also observed for the nanofluids studied.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".