Investigating the impact of thermal bridging calculation methods on building energy performance – a comparative study
Bibliographic record
Abstract
Current energy building codes and standards commonly consider the impact of thermal bridging in assessing building envelope performance. This research examines four thermal bridging calculation methods and provides a comparative study of the challenges, limitations, and effectiveness of each method to evaluate heating and cooling energy demands. \nEach calculation method is applied to 21 different residential buildings covering a variety of building archetypes in Montreal. The equivalent envelope thermal resistance values are reported, and the impact on annual heating and cooling demand is evaluated using building performance simulation. \nThe results show that the underestimation of annual heating demand could reach 37% when the impact of linear thermal bridges is ignored. The annual cooling demand is also shown to be overestimated by 14%. In addition, the variation in Window to Wall Ratio (WWR) and Vertical Surface Area per Floor Area Ratio (VFAR) are highly correlated to the heating and cooling energy demand deviation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".