Effect Of Surface Wettability On Nucleate Pool Boiling Under Low Gravity Conditions
Bibliographic record
Abstract
Surface wettability plays a significant role in determining the heat transfer characteristics associated with a growing bubble in nucleate pool boiling (NPB).Most of the prior works have considered the growth of the bubble under terrestrial gravity conditions.The process of NPB can also be employed as a promising method for heat transfer in devices and equipment working under low gravity conditions.The advancement in computational techniques offers improvement to numerically investigate the impact of surface wettability on NPB heat transfer at various gravity levels so as to design the enhanced surface in a rational manner.The present work focuses on the growth and detachment of a bubble on a horizontal surface with varying wettability in order to understand its contribution on heat transfer process at different gravity levels.The computational domain consists of two regions.The interface between the liquid and vapor in the macro-region has been captured by the VOF method.Micro-layer evaporation underneath the bubble base has a significant contribution on overall heat transfer to the vapor bubble in the process of NPB.This has been calculated on the basis of conductive heat transfer model.The phase change process is modeled by using 'saturated-interface-volume' phase change model.Water has been taken as the working fluid in the current study.The influence of surface wettability on bubble morphology and associated heat transfer behaviour has been investigated at different values of gravity levels.Computations have been performed by providing different heat flux (q) to the heating surface in order to study the effect of gravity level and contact angle (Ca) on bubble growth and heat transfer.It has been found that the impact of wettability modulation is more pronounced for weakly wetted surfaces at higher q value under relatively low gravity conditions.
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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".