Analysis and feasibility study of a multiple-pass heat and energy recovery ventilator with integrated economizer for residential use
Bibliographic record
Abstract
The feasibility of a novel total energy recovery ventilator (HERV) was studied, through the use of an Excel-based screening tool developed for cost analysis, and through TRNSYS simulations for performance analysis. Cost analysis indicated that the HERV almost always outperformed the conventional systems, whereas its attractiveness could be limited by its high capital investment. Simulation results indicated that the counter-flow HERV provided better control of house humidity towards the setpoint, in the meantime, minimized the annual energy use. The performance of heat recovery (HRV) and energy recovery (ERV) ventilators was investigated side-by-side at the Archetype Sustainable Twins-House located in Toronto, Canada. The ERV sensible efficiency ranged from 76.4% to78.5% at an outdoor temperature of -20°C and 5°C respectively, while the HRV efficiency ranged from 91.0% to 95.0% at -16.6°C and 0.7°C respectively. Freezing caused a dramatic drop in the efficiency that was found to be as low as 50%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".