Predicting the Lifespan of Vacuum Insulation Panels in Buildings Using Hygrothermal Simulation
Bibliographic record
Abstract
To meet the demands for reducing building energy consumption, the insulation level of building envelopes is being increased, by increasing the thickness of building walls or through using better performing materials. Vacuum insulation panels (VIPs) have showed potential for use in buildings as they provide significant insulation levels in thin profiles. VIPs lose thermal performance over time as moisture and air permeate into the panel. A shortcoming of current research is how weather and construction impacts VIP lifespan. This thesis will focus on the use of weather data to model the conditions a VIP is subjected to in a wall, and a lifespan prediction based on these conditions. Including, the construction of a hygrothermal model to simulate the conditions in a wall over a 25-year period. For the Ottawa and Niagara climates, the predicted VIP lifespans were 22.6/19.0 and 23.6/19.6 years for the retrofit and new constructions, respectively.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".