Assessing the Energy, Indoor Air Quality, and Moisture Performance for a Three-Story Building Using an Integrated Model, Part Two: Integrating the Indoor Air Quality, Moisture, and Thermal Comfort
Bibliographic record
Abstract
In this paper, an integrated model that coupled CONTAM and WUFI was developed to assess the indoor air quality (IAQ), moisture, and thermal comfort performance. The coupling method of CONTAM and WUFI is described based on the exchange of airflow rate control variables as infiltration, natural and mechanical ventilation parameters between heat and moisture flow balance equations in WUFI and contaminant flow balances equations in CONTAM. To evaluate the predictions of the integrated model compared to single models of CONTAM and WUFI, four scenarios were used. These scenarios are airtight-fan off, airtight-fan on, leaky-fan off, and leaky-fan on, and were defined for a three-story house subjected to three different climate conditions of Montreal, Vancouver, and Miami. The measures of the simulated indoor CO2, PM2.5, and VOCs obtained by CONTAM; the simulated indoor relative humidity (RH), predicted percentage of dissatisfied (PPD), and predicted mean vote (PMV) obtained by WUFI; and those obtained by the integrated model are compared separately for all scenarios in Montreal, Vancouver, and Miami. Finally, the optimal scenarios are selected. The simulated results of the optimal scenarios with the integrated model method (−28.88% to 46.39%) are different from those obtained with the single models. This is due to the inability of the single models to correct the airflow variables.
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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) | 0.001 | 0.001 |
| 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) | 0.001 | 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".