Experimental Study on the Heat Transfer Performance of Al<sub>2</sub>O<sub>3</sub> - Ethylene Glycol/Water-Based Nanofluid as Coolant in Vehicle Radiator
Bibliographic record
Abstract
In this research, the heat transfer efficiency of the vehicle radiator cooling system was experimentally investigated by mixing at different volume concentrations of an aluminum oxide (Al2O3) nanoparticle (NPs) in the regular coolant i.e. a 1:2 ratio mixture of ethylene glycol and distilled water.The sol-gel process was used to synthesize the NPs and characterized using UV-Vis spectroscopy.TATA TIAGO XZ+ was used for this investigation in an idling condition and remained motionless throughout the test.Inlet air temperature, flow rate, outlet temperature, and surface temperature were all recorded at different concentrations of NPs.Experimental results showed that the overall heat transfer coefficient of the nanofluids was improved by 33.63%, 65.4%, and 83.5% at 0.2%, 0.5%, and 1% concentrations, respectively.Thus, the results displayed that the cooling capacity can be increased with the increment of Al2O3 NPs concentration within a certain range in the normal coolant.
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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 | 0.000 |
| 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) | 0.001 | 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".