Development of a hygrothermal simulation tooil (HAM-BE) for building envelope study
Bibliographic record
Abstract
To prevent the building envelope from moisture-related damages, it is essential to predict the building envelope's hygrothermal performance through a scientific approach, and further to improve the design and construction. In this thesis, an advanced numerical tool (HAM-BE) was developed to simulate the combined heat, air and moisture (HAM) transport in the building envelope. The state of the art knowledge of heat and mass transfer in building materials was applied. The major features of HAM-BE are: multi-dimensional and transient coupling of heat and moisture transport; air convection integrated in hygrothermal simulation through Darcy-Boussinesq approximation; heat transfer mechanisms of conduction and convection of sensible and latent heat; moisture transport mechanisms of vapor diffusion, capillary suction and air convection; material database of common building materials in North America; experimental settings or hourly weather data as boundary conditions; and setting moisture loading inside the materials or along the surfaces of the building envelope's hidden or exposed components to simulate the wetting process. A commercial finite element solver was chosen to solve the governing partial differential equations (PDEs) of hygrothermal transport. This approach provided building science researchers the flexibility to build, modify, and maintain their modeling work efficiently. Validation of HAM-BE included inter-model comparison with benchmarking cases of the HAMSTAD project and comparison between numerical simulation with data of the Collaborative Research and Development (CRD) project measured by fellow students under the supervision of Drs Fazio and Rao. Through validation work, HAM-BE was proven to have great potential as an accurate and reliable research tool for the building envelope study. As the extension of the CRD investigation, parametric study was carried out to estimate the drying performance of wood-frame walls under the climatic conditions of Montreal and Vancouver. It is demonstrated that the climate condition has the most significant influence to the drying process of the wet components in wall assemblies. The drying process occurs mainly in the summer season, and is largely restrained in the winter season. To improve outward drying, the cladding materials should have high vapor permeance, especially the sheathing membrane. The sheathing board with higher vapor permeance also facilitates drying. Under the investigated climates, the polyethylene vapor barrier at the warm side of the wall is not beneficial, rather restricts the possibility of inward drying.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".