Nucleate Boiling Heat Transfer Investigation Using Micro and Nanostructured Plates
Bibliographic record
Abstract
In this study, heat transfer performance of micro and nanostructured plates embedded into a rectangular microchannel was experimentally investigated for their potential use in cooling applications. A simple and environmentally friendly technique was proposed to provide the micro and nanostructured plates having superhydrophilic property. Aluminium alloy (Al Alloy) 4041 substrates of 1.5 1.5 cm were roughened by sandblasting method using medium size aluminum oxide abrasive to provide microfeatures; followed by hot water treatment (HWT) process in which nanograss structures were developed on the microstructured substrates. The micro and nanostructured plates were placed near the exit of an aluminum (Al) microchannel with a length, width, and depth of 14 cm, 1.5 cm, and 500 m, respectively. Four cartridge heaters connected to a DC power supply were utilized to apply heat to the test section. De-ionized (DI) water was used as the working fluid and passed through the microchannel using a micro gear pump at three mass fluxes of 100, 300, and 500 kg/m 2 s. The test section dimensions and experimental parameters were selected such that fully developed flow conditions were obtained. The results from the microchannel with untreated Al alloy surfaces were considered as the baseline data. Experimental results of the micro and nanostructured plates revealed that there is no significant change in nucleate boiling heat transfer compared to the control sample. The reason is related to wettability and roughness of the micro and nanostructured plates.
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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".