An Experimental Characterization of Automatic Transmission Fluid Flowing Through Air Cooled Microchannel Heat Exchanger
Bibliographic record
Abstract
Narrow-channel Heat Exchangers have received diversified research and application interests due to the miniaturized geometry, elevated heat transfer characteristics, and better energy efficiency. Automatic Transmission Fluid (ATF) cooling is one of the most important challenges in recent automotive industries due to the quick response to thermo-physical properties with temperature variations. Although a wide range of investigation on characterization of heat transfer and fluid-flow in Minichannel Heat Exchanger (MICHX) for various fluids is available, literatures examining ATF heat transfer and Fluidflow behaviors in the MICHX are scarce. In the current study, attempts have been made to justify the suitability of MICHX application in cooling of ATF. Experimental investigations have been conducted in a well-equipped closed loop integrated thermal wind tunnel test facility using wavy finned-MCHX as a test specimen. The inlet temperature of the ATF was maintained at a constant 75°C throughout the experiment. Air velocities of 6, 10, 14 and 18 m/s were applied. The entering air temperatures were varied at 15, 22, 29, 36 and 43°C while ATF Reynolds number was varied from 3.00 to 30.00 within the air temperature range. The effects of ATF Reynolds number on heat transfer coefficient, and Nusselt number, as well as Heat Exchanger effectiveness-NTU for the air-flow Reynolds number of 1450-5200, were examined. ATF Nusselt number correlation with Reynolds number and Prandtl number was established as a power-law function while considering a variable property ratio. The analysis showed an enhanced result in heat transfer characterizations and good agreement with established phenomena of the multi-port Minichannel Heat Exchanges in open literature.
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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) | 0.000 | 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".