Applicability of a Heat Recovery Ventilator Retrofit in a Vancouver Residential House
Bibliographic record
Abstract
Heat recovery systems are increasingly recognized as key energy conservation measures in residential buildings. But their effectiveness is highly sensitive to operational conditions. This study used a calibrated OpenStudio simulation, which is validated against monthly utility data, to investigate the feasibility of implementing a heat recovery ventilator in an existing single-detached house in Vancouver under two scenarios: existing passive ventilation without a heat recovery ventilator versus the proposed balanced mechanical ventilation with a heat recovery ventilator. The findings indicate that employing an HRV in an existing house lacking balanced ventilation would lead to higher annual space heating energy consumption (75.49 GJ electricity and 56.70 GJ natural gas with HRV compared to 73.64 GJ and 52.70 GJ, respectively, without an HRV). Therefore, for existing houses without balanced ventilation, improving the existing building envelope’s airtightness through retrofits should always be carried out before installing a heat recovery ventilator. Additionally, the heat recovery ventilator should be appropriately sized to compensate for any shortfall in natural infiltration to ensure the sufficient indoor air quality while minimizing the outdoor air-induced space heating energy usage. Furthermore, the recommended break-even point of the infiltration rate for the house studied in this work to avoid increased space heating energy use due to the retrofit with a heat recovery ventilator is 0.281 air change per hour.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".