Study of Motor Oil Cooling at Low Reynolds Number in Multi-Port Narrow Channels
Bibliographic record
Abstract
Mini and micro-scale channels have drawn researchers' attention in the past three decades. The use of these tiny channels in a heat exchanger is considered as one of the pioneered works on the narrow channels as minichannels provide high heat transfer rates per unit volume. Motor oil, known as engine oil, is one of the vital fluids in automotive applications. Its cooling process is confronted by its thermo-physical properties, especially viscosity, which makes this process difficult. In current investigations, experimental endeavors have been performed using a closed loop thermal wind tunnel to verify the aptness of cooling the motor oil through a cross-flow minichannel heat exchanger. The prototype heat exchanger consists of 3 circuits; each circuit has five slabs which are connected to each other by four serpentines. There are 68 channels of 1 mm circular diameter drilled through each slab. The minichannel heat exchanger comprises of wavy fins arranged parallel to the flow of air. The inlet temperature of the motor oil was kept constant at 75°C while the air inlet temperatures were varied within the range of 20°C and 40°C. The flow of the oil fell in the laminar regime due to its high viscosity, which consequently resulted in low Reynolds numbers (Re). The range of was found to be from 0.85 to 3.5 whereas the air flow rates were between 6 m/s and 18 m/s. Correlations were developed between the oil Nusselt number and oil Re and Prandtl numbers. The effect of Re on the heat transfer coefficient, NTU, and effectiveness were investigated. The results were compared with the findings of another highly viscous fluid where a similar test specimen was used and same trends were observed.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".