Assessing the Performance of Passive House Multi-Unit Residential Buildings: An In-Situ Performance Verification and Comparison of Simulation Tools
Bibliographic record
Abstract
In-situ performance verification of enclosure thermal performance and air tightness was conducted on a newly built Passive House (PH) multi-unit residential building (MURB) and a MURB retrofitted to the EnerPHit standard. Wall thermal performance ranged from 60% less to 33% more than the design R-value and window center-of-glass U-values were 20% more than design, both determined using ISO 9869. The air leakage was up to 75% less than the PH requirement of 0.6 ACH50 for new build and 1.0 ACH50 for retrofit. Overall, the enclosure performance was consistent with prior studies, however, exterior temperature estimates likely resulted in inaccuracies of the measured R- and U-values. Building energy simulation tools Passive House Planning Package (PHPP) and CAN-QUEST (CQ) were compared to assess the interchangeability of tools for compliance purposes, using the new PH MURB as a case study. The CQ model had 20% less cooling and 20% more heating energy use and 76% and 40% less heat gains and losses, respectively, than the PHPP Model. Due to these differences in energy use and loads, it is unclear whether the tools are interchangeable for compliance purposes.
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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 | 0.001 | 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 | 0.000 | 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".