Application of a Whole-Building Hygrothermal model in energy, durability, and indoor humidity retrofit design
Bibliographic record
Abstract
A building shall be classified as high performance building if it is energy efficient and durable and at the same time provides comfortable and healthy indoor environment for occupants. To achieve this objective, the hygrothermal performance of alternative building designs should be evaluated based on the simultaneous analysis of these three functional requirements rather than separately. In this article, a Whole-Building Hygrothermal model is used for evaluation of various retrofit design parameters that potentially enhance the overall performance of an existing residential house. The retrofit options considered in this study include changes to the reference house’s ventilation rate and operation, windows, insulation level, and various combinations of these options. Energy efficiency, building envelope and moisture management potential, indoor humidity control, and window condensation potentials are considered to be the four performance indicators in searching for a retrofit option that delivers an optimal performance. The hygrothermal simulation results indicate that changing a design parameter to improve one of the design goals may result in less optimal results in the other one or both goals, or even in some cases result in severe negative consequences.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".