Investigation of Thermal Buffer Zone Effectiveness in Real Buildings
Bibliographic record
Abstract
Global warming is caused by Greenhouse Gas (GHG) emissions produced from the use of fossil fuel-based energy sources. Buildings consume about 30%-35% of the global energy use, which makes buildings a major contributor to the global warming problem. A long-term plan has been established at the Thermal Processing Laboratory (TPL) at McMaster University to investigate the use of various renewable energy-based technologies to achieve Net-Zero Energy Buildings (NZEB) in Canada. This paper presents results of an investigation of the effectiveness of using a thermal buffer zone (TBZ) in real buildings. A TBZ is a closed passage built around the building that allows air to passively re-distribute heat energy from solar radiation received on the south side throughout the building. A TBZ offers an effective solution of the overheating problem usually experienced on the south side of the building and, at the same time, it helps in reducing the heating load of the north side of the building. An experimental setup employing TBZ in a model of a typical building floor has been built. An analytical model of the TBZ has been developed. The experimental data has been used to validate the developed analytical model, which then was used to simulate the performance of a TBZ implemented in a real building floor. Results showed that the effectiveness of TBZ could reach 117% in the winter (cold climate countries). Moreover, the study considered the effect of integrating the TBZ with a fan. Results showed that the use of the fan is beneficial for a certain gap width, beyond which the use of the fan is not recommended. In conclusion, results of this study confirm that the TBZ can offer an effective means of replacing parry of building consumption of fossil fuel-based energy using solar energy.
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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) | 0.024 | 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".