Modeling the effect of dual-core energy recovery ventilator (ERV) unit on the energy use of houses in northern Canada compared with the single-core ERV unit
Bibliographic record
Abstract
The conventional preheating defrost used in the single-core energy recovery ventilator (ERV) is not optimal for housing in northern Canada due to its significant energy consumptions. Therefore, the recirculation defrost and dual-core operation have been the focus for addressing the frosting issues of the ERV in northern Canada. The use of single-core ERV using the defrost by air recirculation has the disadvantage of reducing the outdoor air supplied to the house, which might affect the indoor air quality. First, this thesis presents new correlation-based models of the single-core ERV with recirculation defrost, based on laboratory-controlled experimental data, of supply air temperature and humidity after the single-core ERV unit during normal and defrost operation modes. Then the dual-core ERV model, in compliance with the manufacturing schedules in each unit, is developed based on the single-core correlation-based models. Second, the seasonal energy use for space and ventilation of houses are simulated in TRNSYS program at three arctic locations with heating degree-days (HDD) of 8798, 8888 and 12208, respectively, and Montreal (4356) as the reference. The ERV unit is studied in the Net Zero Energy Housing (NZEH)model and Conventional Northern Housing (CNH) and Northern Sustainable Housing (NSH) northern housing models for the following cases: i) with and without single-core ERV, ii) different threshold temperatures for defrost, iii) preheating and iv) dual-core operation. The single-core ERV unit reduces heating energy use, compared with the case without heat recovery, by 24% (Montreal), 26% (Inuvik), 27% (Kuujjuaq), and 27% (Resolute), respectively. However, the outdoor airflow rate during the defrost is smaller than minimum standard requirements for 1038 hours (19% of time) in Inuvik, 701 hours (13%) in Kuujjuaq, 1320 hours (24%) in Resolute, and 223 hours (4.7%) in Montreal, respectively. The factory schedules are recommended since the increase of normal operation time leads to a significant increase in the energy use of heating the outdoor air. The preheating defrost is not economical to use in northern Canada because it significantly increases the energy use of heating the outdoor air, compared with the single-core ERV with the recirculating defrost and dual-core ERV units. The dual-core ERV unit removes the frost while continuously supplying the minimum required outdoor air to the indoors. This advantage comes at the cost of minor increases in the heating and fans energy use compared with the single-core ERV unit.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 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".