Smart wetting of permeable pavements as an evaporative-cooling measure for improving the urban climate during heat waves
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
An urban microclimate model is used to design a smart wetting protocol for multilayer street pavements in order to maximize the evaporative cooling effect as a mitigation measure for thermal discomfort during heat waves. The microclimate model is built upon a computational fluid dynamics (CFD) model for solving the turbulent air, heat and moisture flow in the air domain of a street canyon. The CFD model is coupled to a model for heat and moisture transport in porous urban materials and to a radiative exchange model, determining the net solar and thermal radiation on each urban surface. A two-layer pavement system, previously optimized for maximal evaporative cooling applying the principles of capillary pumping and capillary break, is considered to design a smart wetting protocol answering the questions “when,” “how much,” and “how long” a pavement should be artificially wetted. It was found for the current optimized pavement solutions that a daily amount of 6 mm wetting over 10 min in the morning, preferentially between 8:00 and 10:00, guarantees a maximal evaporative cooling for 24 h during a heat wave.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| 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 it