Effects of Working Fluid, Fill Ratio and Orientation on Looped and Unlooped Pulsating Heat Pipes
Bibliographic record
Abstract
Improved miniaturization and a trend towards increasingly dense and compact architectures have led to unmanageably high heat fluxes in electronic components. In order to keep temperatures at operational levels more advanced cooling solutions are being required that go beyond the solid heat sink and forced convection. Pulsating heat pipes made out of multi port extrusion tubing are a proposed solution. Typically, gas-liquid slug flow occurs in the serpentine channel imbedded in the pulsating heat pipe. Vapour is produced in the heated section and condensed in the cooled section located at opposite ends of the heat pipe. In this work, experiments were conducted on four Multi-Port Extruded (MPE) aluminum tubing heat pipes with different internal structures: rectangular channel looped, rectangular channel unlooped, triangular channel looped, and triangular channel unlooped. The effect of changing the working fluid (ethanol or de-ionized water), fill ratio, and orientation were measured and compared for the different heat pipes. It was found that most of the heat pipes performed better with ethanol than de-ionized water. Only the looped rectangular channel heat pipe performed satisfactorily with de-ionized water, which is attributed both to the larger channel size and the looped architecture. The unlooped heat pipes performed best at the lowest fill ratios (10%) while the looped heat pipes showed their best performances between 30 and 50% with marked decrease at the lower and higher fill ratios. Both looped heat pipes performed poorly in horizontal orientation as compared to vertical, however, the unlooped heat pipes performed quite well in both orientations. This may be more the effect of the fill ratio on horizontal performance as literature suggests that horizontal orientation requires a lower fill ratio to perform satisfactorily.
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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".