Compartmentalization and ventilation system impacts on air and contaminant transport for multifamily buildings
Bibliographic record
Abstract
Provision of acceptable indoor air quality in multifamily buildings (MFBs) depends on the interior air flows that impact dilution of contaminants, cross-contamination between units and building energy use. The airtightness of interior partitions and design of ventilation systems in MFBs determine the flows across building partitions. These flows change the total ventilation rate for the building and individual units, and impact the mixing of air and contaminants between apartment units or with common spaces. This study examines the changes in air flow and contaminant transport in MFBs using combined CONTAM/EnergyPlus models. Key parameters were systematically varied, including climate, apartment airtightness, and mechanical ventilation system type. Simulations were performed for mid-rise buildings with and without an enclosed common corridor, and a 20-story high-rise building. Contaminants simulated in the analysis were PM2.5, formaldehyde, water vapor, and CO2. Key results of this work are that current airtightness requirements in ASHRAE 62.2 sufficiently limit transport of key contaminants, independent of the type of ventilation system across all three building typologies, and significantly reduce energy use in colder climates. The results of this work are intended to assist codes and standards bodies in setting appropriate airtightness limits and ventilation system design guidelines for MFBs.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".