Thermal mass and thermal bridging effects on transient thermal performance of walls and energy performance of office buildings
Bibliographic record
Abstract
The increased requirements of buildings to reduce energy use has highlighted the importance of accounting for all factors that influence energy use in buildings. Thermal performance of the walls, as part of the building envelope systems, can contribute to the overall energy use and greenhouse gas emissions of the buildings. In this research, effects of thermal mass and thermal bridges on transient thermal performance of walls were assessed. Specifically, the impact of different placements of material layers within wall assemblies on the transient thermal performance of the concrete-based walls, and the energy performance of an office building, were investigated. Three case study sinusoidal outside temperature profiles, representative of heating-dominated, cooling-dominated, and temperate climates, were considered for studying the thermal performance of the walls. It was concluded that placing the thermally massive component in the middle layer of walls led to the lowest amplitudes of heat fluxes and indoor surface temperatures, as well as the lowest decrement factor and the longest time required to reach quasi-steady state conditions. On the other hand, weather conditions of three cities, Montreal, Miami, and Denver, were taken into account for the assessment of energy performance of an office building. It was concluded that the wall whose thermally massive layers are exposed to the indoor and outdoor weather conditions had the best performance amongst the cases studied. The second part of this research was devoted to presenting a method for taking into consideration the effects of steel and wood studs, as the thermal bridging elements, on dynamic thermal behavior of the walls. Three sinusoidal outside temperature conditions were assumed, and thermal performances of two case study walls under these conditions were assessed: a steel stud wall and a wood-frame wall. It was concluded that the maximum deviation between the instantaneous surface heat fluxes of the original steel stud wall and those of the corresponding equivalent wall was less than 5% while the deviations were dependent on the climate conditions for the wood-frame wall case.
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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".