A Field-validated Multi-objective Optimization of the Shape and Size of Windows Based on Daylighting Metrics in Hot-summer Mediterranean and Dry Summer Continental Climates
Bibliographic record
Abstract
This study aims to determine the optimum size of windows based on the window-to-floor ratio (WFR) for the main cardinal directions in Hot-summer Mediterranean (Csa) and Dry Summer Continental (Dsa) climates (Köppen–Geiger classification system) by carrying out a multi-objective optimization that relies on three dynamic metrics of Useful Daylight Illuminance (UDI-a (autonomous)), Daylight Autonomy (DA), and Annual Sunlight Exposure (ASE1000,250) in Radiance version 5.1. A validation against field measurements is conducted under an overcast sky with an illuminance of 11000 lux. The Pareto front is used to pick the best solutions for evaluating the most optimized solutions. Accordingly, the minimum standards for cardinal directions in each climate are defined. The minimum suggested WFR for the Dsa and Csa climates for the south-, east-, north-, and west-facing windows are 20%, 15%, 20%, and 15% (Dsa) and 20%, 20%, 25%, and 20% (Csa), respectively. Furthermore, the results show the shape and relative proportions of windows (vertical/horizontal) have a significant effect on the metrics. As a result, this paper introduces the “Proportion Ratio” as a new indicator for designing windows.
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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 | 0.001 |
| 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 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".