Analysis on Energy Consumption and Economy of an Office Building Equipped with Low-E Window in Beijing
Bibliographic record
Abstract
In this paper,the energy efficiency performance and heat transfer model of Low-E glass were firstly introduced.And then,under six different kinds of glass window conditions,the software of DeST-c was used to simulate the hourly indoor air temperature,energy consumption of an office building in Beijing,also the influences of different seasons and orientations on window types were compared.Thirdly,based on the analysis of energy consumption,the investment and operation cost of the selected window,such as single and assembled windows,and common double window were analyzed and compared.The results indicated that the investment of the assembled window was 59.39% higher than that of the normal one,while the power of 7.42% could be saved each year.As a result,the overspend part of the investment could be took back in only two years.In a conclusion,with the relatively lower investment risk,the assembled window would be the first choice of this office 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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".