Natural Dropwise Condensation of Humid Air on an Inclined Flat Surface
Bibliographic record
Abstract
The fundamental understanding of dropwise condensation has been the focus of numerous research studies since the 1930s.In recent years, the focus has been mostly on the development of durable, hydrophobic or hybrid surfaces to enforce dropwise condensation regime and reduce the formation of liquid film.Film formation is undesirable since it acts as a heat transfer barrier in the condensation process.The performance of industrial condensers in an environment with the presence of moist air is an important consideration in numerous energy systems, such as heating/cooling systems, dehumidification, atmospheric water harvesting, and energy storage systems.In the present study, natural dropwise condensation of quiescent moist air is experimentally studied.Several surfaces are made from metal, polymer, and graphite with a range of contact angles and tested under various relative humidity levels and ambient temperatures.Based on the experimental data, a new, comprehensive correlation is developed for the calculation of heat transfer coefficient of humid air condensation on a vertical flat plate as a function of key parameters, including surface subcooling temperature, relative humidity, and contact angle.A correction factor is also added to the proposed correlation to include the effect of substrate inclination.Finally, the proposed correlation is successfully compared with our data to the available data in the literature.The result of this study can be used for a variety of dropwise condensation applications in the presence of humid air, for both hydrophilic and hydrophobic regions.
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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 | 0.000 |
| 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) | 0.001 | 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".