Do we understand the drying of porous materials?
Bibliographic record
Abstract
Convective drying at pore scale is studied by a two-component two-phase lattice Boltzmann model at pore scale showing the important influence of capillary pumping from large to small pores and pinning of contact lines in dual porosity materials. Capillary pumping and pinning explains the first drying period with almost constant drying rate. The drying rate during the first drying period is found to depend on air velocity or Reynolds (Re) number, and a logarithmic relation between average drying rate and Re is found. This analysis allows to better understand first and second drying period and their dependence on air velocity and pore structure. In an upscaling example, the evaporative cooling effect of a two-layer porous pavement with optimal wetting protocol is analyzed for a square in Zurich. The top layer of the pavement enhances drying during first drying period due to capillary pumping, while the second layer prevents loss of sprayed water to the subsoil. The evaporative cooling from pavements enhances the thermal comfort, but has to be combined with other measures like shadowing from trees. The proposed multiscale approach upscaling from pore to continuum scale is believed to enhance the understanding of drying of porous materials and its application in urban and building physics.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.002 | 0.008 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".