Bibliographic record
Abstract
In Iran, the buildings sector is responsible for large consumption of energy and corresponding GHG (Greenhouse Gases) emissions.The insulation of buildings is a relevant technology to reduce such energy consumption and GHG emissions.According to Paris agreement 2016 all countries in the world are obliged to reduce their GHG emission and Iran as a developing country should contribute to international agreement.This paper seeks Iran's building sector role in mitigating national GHG emission.The main objective of this study is to minimize the building environmental impacts by proper insulation.For this purpose, five details for applying thermal insulation thickness, recommended by Iran national building code were selected.The most conventional thermal insulation materials produced in Iran are selected as thermal insulation material.First, thermal insulation thickness was optimized for all surfaces comprising a single cubic thermal zone in climate of Tehran.The results are evaluated in reducing, net environmental saving and energy demand for a typical residential building located in Tehran.The results of this study represents optimized insulation thickness for all building envelope surfaces, in accordance to mandatory thermal performance, in order to optimize energy consumption of the building and minimizing its environmental footprint.The results shows that by accommodating proper insulation total environmental impact of building can reduce to more than 70% percent.
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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) | 0.999 | 0.984 |
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; both teacher heads agree on what is shown here.
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".