Determining through numerical modeling the effective thermal resistance of a foundation wall system with low emissivity materials and furred - airspace
Bibliographic record
Abstract
A numerical model was developed to investigate the effect of foil emissivity on the effective thermal resistance of a foundation wall system with foil bonded to expanded polystyrene foam in a furred assembly having airspace next to the foil. This model simultaneously solved the energy equation in the different material layers, surface-to-surface radiation equation in the furred ? airspace assembly, and the coupled compressible Navier-Stokes equation and energy equation in the airspace. A parametric study was then conducted to determine the effective thermal resistance (R-value) of the foundation wall system as a function of foil emissivity. Consideration was also given to a accumulation of dust and condensation on the foil surface as these may also affect the emissivity of the foil. The results showed that when the furring was installed horizontally a low foil emissivity of 0.05 can increase the wall R-value to as much as ~10%. In the next phase of this work, the present model will be benchmarked against test results and it will also be used to determine the effective thermal resistance of foundation wall systems when the furring is installed vertically. The outcome of these efforts will be reported at a later date.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".