Use of hygrothermal numerical modeling to identify optimal retrofit options for high-rise buildings
Bibliographic record
Abstract
Using numerical modelling to simulate and predict the hygrothermal (i.e., combined thermal and moisture)performance of building envelopes is very recent. Key questions include: how to model accurately coupled heat-air and capillary moisture transports in building envelope components; a satisfactory definition of a set of representative environmental boundary conditions to be used for long-term hygrothermal calculations; how to characterize the moisture- and temperature-dependent properties; the effect of aging and cyclic environmental conditions on porous building materials; and how to develop sound criteria to predict the moisture durability of building envelope components. This paper presents the findings of a research project involving detailed hygrothermal modelling. The heat, air and moisture results demonstrated that the in-house model could be adapted successfully for high-rise building calculations. The findings also show how the long-term hygrothermal performance of typical wall systems can be assessed using numerical modelling. A short description of an advanced in-house heat, air and moisture model, hygIRC, is also presented.
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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) | 0.000 | 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 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".