Analysis of the Transient Single-Phase Thermal Performance of Micro-Channel Heat Sinks
Bibliographic record
Abstract
The objective of this study is to examine the transient single-phase thermal behavior of micro-channel heat sinks during startup and over a short-duration power surge, and to investigate the effects of property and geometry parameters on this behavior. The transient analysis required the solution of three-dimensional conjugate heat transfer in the heat sink. These solutions were obtained numerically using the finite control-volume method and the numerical accuracy of the results was carefully assessed. Accuracy of the numerical model was validated by comparisons with available experimental data. The behavior of heat sinks with different values for the fin width, channel width, material thickness between the top of the channels and top of the heat sink, and different sink materials was examined during startup from a uniform initial temperature with a uniform input heat flux, followed by a short-duration power surge from the steady-state condition. It is concluded that increasing the fin width or channel width increases the steady-state and maximum transient temperatures in the solid, and that increasing the material thickness between the heat-sink channels and the chip or using a material with larger density and specific heat increases the transient period and lowers the maximum transient temperature in the solid during the power surge.
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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 | 0.000 |
| 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".