Effects of thermal mass on transient thermal performance of concrete-based walls and energy consumption of an office building
Bibliographic record
Abstract
Reducing energy consumption and Greenhouse Gas (GHG) emissions is an essential part of the clean growth and climate change framework recently developed by the Canadian government, which emphasizes the importance of energy-efficient building constructions. In this paper, the effects of thermal mass and placement of the thermally massive layer within wall assemblies on the transient thermal performance of walls and energy performance of a case study office building were studied. Three climate conditions representative of the heating-dominated, temperate, and cooling-dominated climates were considered. As for the assessment of energy demands, two cases for the indoor air temperature were taken into account: (i) indoor temperature was maintained at 20°C throughout the year, and (ii) during summertime, there was a set-point of 24°C and a setback of 35°C during the rest of the day while during wintertime, the set-point and setback values were 22°C and 18°C, respectively. The cases were compared according to the resulting decrement factor, the time required to reach quasi-steady state conditions, amplitudes of changes of heat fluxes and indoor surface temperatures, and the energy demands. The results showed that, for the cases studied, the wall, for which the thermally massive layer is not directly exposed to the indoor and outdoor climate conditions, resulted in the lowest decrement factor, the minimum amplitude of changes of heat fluxes and indoor surface temperatures, and maximum time required to reach quasi steady-state conditions. As for the energy performance, on the other hand, the wall, for which the thermally massive layer is exposed to the interior and exterior climate conditions, performed best amongst the cases investigated.
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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 | 0.000 |
| 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) | 0.001 | 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".