Energy retrofit using vacuum insulation panels: An alternative solution for enhancing the thermal performance of wood-frame walls
Bibliographic record
Abstract
Field monitorings of thermal performance of residential 2 x 6 wood-frame wall systems that had been retrofitted using vacuum insulation panels (VIPs) and extruded polystyrene foam (XPS) panels were undertaken in May 2011 – May 2012 at the Field Exposure of Walls Facility (FEWF) of NRC-Construction. The main objective of this research was to measure the steady-state and transient thermal performance of three wall assemblies (4 ft x 6 ft), two of which incorporated VIPs within an XPS Tongue and Groove (T&G) configuration and VIPs within an XPS Clip-On (C-O) configuration, and a third assembly incorporating only XPS. The three wall assemblies were installed in the FEWF for 1-year cycle of exposure to outdoor natural weather conditions. The hygIRC-C model was used in this study. The results of the model calculations were in good agreement with the experimental data. Given that the VIPs could be punctured during the installation process or could fail during normal operating conditions, additional model calculations were used to predict the thermal resistance in cases where one or more VIPs failed. The model was also used to predict the yearly cumulative heat losses across these wall systems. It is important to point out that the aging effect and the effect of the thermal bridging due to envelope (i.e. skin) of the VIPs are not accounted for in this study. However, sensitivity analysis of the thickness and thermal conductivity of the VIP envelope was conducted to investigate the effect of these parameters on the effective thermal resistance of VIP.
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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 | 0.000 |
| 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) | 0.001 | 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".