Drying Response of Wood-Frame Construction: Laboratory and Modeling
Bibliographic record
Abstract
Recent research in the assessment of hygrothermal response of building enclosures focuses on both laboratory experimentation and modeling in which the results from both processes are compared. Evidently such type of studies can potentially offer useful information regarding the benchmarking of models and related methods to assess hygrothermal performance of wall assemblies. This paper reports on experimental results and the use of an advanced hygrothermal computer model called hygIRC to assess the hygrothermal response of various components in wood-frame wall assemblies when subjected to nominally steady-state environmental conditions. There was interest in obtaining information on the drying rates of wall components, in particular, oriented strand board (OSB), featuring several different types of membrane in contact with OSB given that such results could provide direct evidence of the degree to which membranes may retain moisture and affect moisture migration. On this basis, the drying responses of mid-scale specimens of approximately (0.8×1 m2) and full-scale specimens (2.44×2.44 m2) were assessed in a series of experiments undertaken in a controlled laboratory setting. The results were subsequently used to help benchmark simulation results obtained from hygIRC in which a comparison is made between experimental and simulation results.
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 | 0.000 | 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 | 0.001 | 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 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".