Properties of vacuum insulation panels: results from experimental investigations at NRC Canada
Bibliographic record
Abstract
Many samples of commercially available vacuum insulation panels were tested in the laboratory to determine their physical properties such as thermal resistance, water vapour permeance of the foils and sorption characteristics of the core material. The effect of various exposure conditions, which includes 32 ºC, relative humidity up to 90 % and 5 bar over-pressure, on the thermal resistance was determined. Also, the edge effects when panels were put side by side were evaluated. The performance of the sealing foils and seams in the manufactured products was checked in terms of water vapour permeance and air permeance. The tested products seem to with stand major environmental loads. High humidity, higher temperature and even higher pressure have not significantly changed their thermal resistances in two years. Air permeance across the foils is immeasurably low. Water vapour does permeate, albeit at a very low rate(1 to 3 ng m-2 s-1 Pa-1), across the foils and seams. However, precipitated silica as a core material has appreciable capacity to adsorb and store water molecules. Though the central portions of the panels show remarkable thermal resistances, the edge effect for the same reason is significant. The joining point of the four corners of four high performance panels is only as efficient as a high performance cellular plastic insulation.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".