Sustainability performance evaluation of passivhaus in cold climates
Bibliographic record
Abstract
Buildings are one of the major sectors that contribute to significant environmental impacts and energy consumption in the USA. Building sustainability can be realized through enhancing energy efficiency and reducing energy demand. One sustainable strategy for meeting such goals is to adopt high performance building envelopes integrated with an energy efficienct HVAC system. Heat transmission (U-factor) and air infiltration of building envelopes are closely correlated to building energy conservation. The primary goal of this paper is to understand the energy implication of U-factor and air infiltration of building envelopes for energy conservation. The research is based on a case study project, a residential building in Calgary, Alberta, Canada designed based on Passivhaus (PH) criteria. In order to reduce the U-factor of the glazing facades of the case study building, a high performance glazing system is discussed and respective energy saving potentials are estimated using a building energy simulation tool. Air tightness of building envelopes is also discussed as it plays a crucial role in the heating energy consumption of buildings in cold climates. The study confirms that both enhanced U-factor and airtightness reduce energy consumption by 30~40%. The proper choice of window technologies and field quality workmanship that enhance U-factor and air tightness becomes essential in building sustainability in severely cold climates.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".