Analytical Modeling of Annular Flow Boiling Heat Transfer in Mini- and Microchannel Heat Sinks
Bibliographic record
Abstract
An analytical model is proposed to predict the flow boiling heat transfer coefficient in the annular flow regime in mini- and microchannel heat sinks based on the separated model. The modeling procedure includes a formulation for determining the heat transfer coefficient based on the wall shear stress and the local thermophysical characteristics of the fluid based on the Reynolds’ analogy. The frictional and acceleration pressure gradients within the channel are incorporated into the present model to provide a better representation of the flow conditions. The model is validated against collected data sets from the literature produced by different authors under different experimental conditions, different fluids, and with mini- and microchannels of hydraulic diameters falling within the range of 92–1440 μm. The accuracy between the experimental and predicted results is achieved with a mean absolute error of 10%. The present analytical model can correctly predict the different trends of the heat transfer coefficient reported in the literature as a function of the exit quality. The predicted two-phase heat transfer coefficient is found to be very sensitive to changes in mass flux and saturation temperature. However, it is found to be mildly sensitive to the change in heat flux.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".