Hygrothermal Performance Assessment of Wall Systems With Various Concrete and Insulation Configurations
Bibliographic record
Abstract
The moisture performance of building envelope assemblies has always been a major concern of designers. Building envelope is constantly exposed to moisture loads such as exterior and interior humidity, rain, groundwater, snow and construction moisture. Therefore, it is critical to control the moisture migration mechanism within building envelope walls. Moisture accumulation occurs when the wetting potential of building envelope exceeds its drying potential due to applying inappropriate construction materials or configuration designs. Moisture accumulation in mid-rise and high-rise concrete buildings has negative impacts on microbial growth, occupants’ comfort, energy consumption, freeze thaw and compressive and tensile strength of concrete which lead to spent of millions of dollars on the repair in North America every year. Therefore, evaluation and prediction of moisture performance of building envelope components are important design factors that should be considered to minimize the risk of moisture accumulation in concrete buildings. In this paper, the hygrothermal performance of a number of concrete wall systems with various configuration of concrete and insulation are studied. The performance of these systems in wet and cold climates of Vancouver and Winnipeg are evaluated using a hygrothermal model. The water content of concrete layers and moisture fluxes at the interior and exterior surface layers are analysed and the overall performance of the systems as related to moisture storage and drying behaviour are determined. The results indicate that assemblies with thermal insulation placed on the exterior side of concrete have the highest hygrothermal performance while assemblies with concrete layer sandwiched between two wythes of thermal insulations have the poorest hygrothermal performance.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.014 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".