Modeling of the evaporation process of a pair of sessile droplets on a heated substrate
Bibliographic record
Abstract
Sessile droplet evaporation is a complex process that involves both mass and heat transfer at the liquid/vapor interface. This process has many practical applications, including cooling microprocessors, and improving heat exchanger efficiency. This work builds upon a previously developed point source model for purely diffusive evaporation, expanding it to account for the effect of heated substrates on the evaporation behavior of a pair of sessile water droplets. Experimental investigations were carried out at various substrate temperatures and droplet separation distances to assess the validity of the diffusive model under these conditions. Results show that as the substrate temperature increases, convection becomes a more prominent factor alongside diffusion, enhancing the evaporation rate. When the temperature difference between the substrate and the ambient is small, diffusion dominates, but as this difference grows, natural convection plays a significant role. It is found that for Ra · L/d < 400, the evaporation rate is governed mainly by diffusion. Likewise, for Ra · L/d > 2400, the contribution of convection and diffusion stabilizes. An empirical correlation was developed to predict evaporation rates, accounting for both diffusion and convection. The proposed correlation shows excellent agreement with experimental data across different conditions, making it a valuable tool for predicting droplet evaporation rates on heated surfaces and its applications in thermal management systems.
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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".