Thermal Resistance and Pressure Drop Minimization for a Micro-gap Heat Sink with Internal Micro-fins by Parametric Optimization of Operating Conditions
Bibliographic record
Abstract
In recent years, researchers are investigating several potential applications of two-phase flow in micro-gap heat sinks; electronic cooling is one of them. Further, internal micro-fins are used to enhance the heat transfer rate. However, the pressure drop penalty due to small gap height and fin surfaces is a major concern. Hence, minimization of thermal resistance and pressure drop is required. In this paper, effects of operating conditions, e.g., wall heat flux, pumping power, and inlet void fraction, on total thermal resistance and pressure drop in a micro-gap heat sink with internal micro-fins of rectangular and triangular profiles have been investigated by numerical analysis for the R-134a coolant. Furthermore, optimization of these parameters has been carried out by response surface methodology. Simulation results show that rectangular micro-fins show superior performance compared to triangular fins in reducing thermal resistance. Finally, for an optimum condition (7.1202×10-5 W pumping power, 1.2×107 Wm-2 heat flux, and 0.03 inlet void fraction), thermal resistance and pressure drop are reduced by 56.3% and 87.2%, respectively.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".