Impact of reflective roofs on the overall energy savings of whole buildings
Bibliographic record
Abstract
Many previous studies by the authors of this paper and others have shown that installing white/reflective/cool roofing systems resulted in energy savings. The amount of energy savings depended on the longwave thermal emissivity and the short-wave solar reflectivity of the rooftop surfaces. The question is “what is the percentage energy savings for the whole building as a result of using cool roofing systems instead of conventional/black roofing systems? To answer this question, three-dimensional energy simulations are conducted for typical Saudi buildings when they are subjected to the natural weathering conditions of the Eastern Province of Saudi Arabia. Several Window-to-Wall Ratios (WWRs) having different thermal resistances (R-values) and Solar Heat Gain Coefficients (SHGCs) are considered in the study. The windows are located in the different main solar orientations. To investigate the effect of the area ratio of the roof to the walls on the potential energy saving due to using cool roofs, one storey and two-storey are considered in this study. Results showed that using reflective materials with lower short-wave solar absorption coefficients in the roofing systems have resulted in a decrease in the yearly total energy loads of one-storey building and two-storey building.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".