Developing light transmitting concrete for energy saving in buildings
Bibliographic record
Abstract
Energy consumption is constantly increasing all around the world, and one of the substantial energy consumption fields is the electricity required for lighting in buildings. There are various approaches to tackle this problem, among which the use of transparent facades is the common method to reduce electrical energy consumption in modern buildings such as museums; However, these solutions have many problems, such as space security, heat gains during summer, and glare; The main problems related to transparent facades are energy loss through light transmitting seams and visual discomfort. Hence, it is necessary to develop a new method that can pass natural light to enhance visual comfort without damaging the thermal insulation of the building's exterior walls. One solution that can be given to this issue is using light transmitting concrete. In this study, five high-performance light transmitting concrete samples, including the different amounts of optical fiber were made, and their performances in terms of daylight and electricity saving have been analyzed based on simulation with Diva for Rhino software. For a better comparison between different studies, the analysis was done based on the reference office, which had been used in previous relevant studies. As a result, the reference office was modeled in 6 cities (Tehran, Houston, Phoenix, San Francisco, Vancouver, & Chicago). It was found that using this material along with using lighting sensors resulted in 45.7%, 31.5%, and 38.8% electricity saving for offices in Tehran, Vancouver, and Phoenix, respectively, and also can increase UDI (Useful Daylight Illuminance) by about 39% in Tehran.
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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 | 0.000 |
| 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 | 0.000 |
| 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".