Hygrothermal performance of building envelopes: uses for 2D and 1D simulation
Bibliographic record
Abstract
A building's durability depends on controlling heat and moisture within its envelope. Moisture diffuses through porous materials that may suffer mould growth and decay (if wood-based) when left moist and warm for too long. Designers try to keep vulnerable components dry, but materials can start to deteriorate before reaching the dew point temperature. Researchers use two-dimensional hygrothermal modeling to calculate time-varying moisture content and temperature at points on a plane through the building envelope thickness. One-dimensional versions of several research programs have been written to assist designers and other building envelope specialists in their work. This paper compares moisture and temperature histories in two building envelopes exposed to a variety of climatic conditions over three years, as calculated by 2D and 1D versions of one such computer program. The 2D calculations come from reports on a methodology for moisture management of wood-frame walls, published in 2003 by a consortium of industry and research partners. Results for a face-sealed stucco wall with rain entry by diffusion only (no seal deficiencies) showed reasonable agreement between 2D and 1D, whereas those for a brick wall with a ventilated air space diverged considerably. With due respect for limitations, 1D simulation can give a first indication of the differences in performance of a wall exposed to different climates, or between different wall assemblies. In some cases the user should consider following up with 2D simulation or field monitoring.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".