Thermal response of basement wall systems with low-emissivity material and furred airspace
Why this work is in the frame
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Bibliographic record
Abstract
In basement wall systems, airspaces can contribute in obtaining a higher thermal resistance, if a low-emissivity material such as reflective foil is installed within a furred-airspace. In this study, numerical simulations were conducted using the hygrothermal model ‘hygIRC-C’ that was developed at the National Research Council of Canada’s Institute for Research in Construction to investigate the steady-state and transient thermal performance of basement wall systems. This model solves simultaneously the energy equation in the various material layers, surface-to-surface radiation equation in the furred-airspace assembly, Navier–Stokes equation for the airspace, and Darcy and Brinkman equations for the porous material layers. The wall systems used in the simulations incorporate a low-emissivity material (foil with emissivity = 0.04) bonded to a moulded/expanded polystyrene foam that is installed in a furred-airspace assembly. The furring is installed horizontally and covered with a gypsum board. The structural element of the wall (external layer) is a poured-in-place concrete. Walls with and without furred-airspace assembly were considered in this study. Also, consideration was given to investigate the effect of the above-grade and below-grade portions of the wall on the thermal performance when these walls are subjected to two different Canadian climates. Results showed that at steady-state condition, the effective thermal resistance ( R-value) of the wall with a furred-airspace assembly depends on the soil, outdoor, and indoor temperatures. Additionally, these wall configurations resulted in an energy savings of ~17% compared to walls without furred-airspace assembly when these walls are subjected to two different climate conditions.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it