Evaporation Mechanisms and Heat Transfer in Porous Media of Mixed Wettabilities With a Simulated Solar Flux and Forced Convection Through the Media
Bibliographic record
Abstract
Abstract An experimental apparatus was designed to study the impacts of wettability on evaporation of water from Ottawa sand. Evaporation rates were measured for: (1) a 5.7-cm-thick layer of hydrophilic Ottawa sand; (2) a 5.7-cm-thick layer with 12% hydrophobic content, consisting of a 0.7-cm-layer of n-Octyltriethoxysilane-coated hydrophobic sand buried 1.8 cm below the surface of hydrophilic sand; and (3) a 5.7-cm-thick layer with mixed wettabilities, consisting of 12% n-Octyltriethoxysilane-coated hydrophobic sand mixed into hydrophilic sand. The sand–water mixtures experienced forced convection above and through the sand layer, while a simulated solar flux (i.e., 112±20 W/m2) was applied. Evaporation from homogeneous porous media is classified into the constant-rate, falling-rate, and slow-rate periods. Wettability affected the observed evaporation mechanisms, including the transition from constant-rate to falling-rate periods. Evaporation entered the falling-rate period at 12%, 20%, and 24% saturations for the all hydrophilic sand, hydrophobic layer, and hydrophobic mixture, respectively. Wettability affected the duration of the experiments, as the all hydrophilic sand, hydrophobic layer, and hydrophobic mixture lasted 17, 20, and 26 trials, respectively. Both experiments with hydrophobic particles lasted longer than the all hydrophilic experiment and had shorter constant-rate evaporation periods, suggesting hydrophobic material interrupts capillary action of water to the soil surface and reduces evaporation. Sand temperatures suggest more evaporation occurred near the test section inlet for higher saturations and the hydrophobic layer experienced more evaporation occur near the outlet. Evaporation fluxes were up to 12× higher than the vapor diffusion flux due to enhanced vapor diffusion and forced convection.
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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) | 0.000 | 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 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".