Steady-state and dynamic hygrothermal performance of rendered straw bale walls
Bibliographic record
Abstract
Wheat straw, in the form of compacted bales, is increasingly used as thermal insulation in the external walls of buildings. Common practice is to use a render finish, applied directly to surface of the straw bales, to protect them from decay, and enhance structural performance and fire resistance. Coatings are typically made of water vapour permeable materials, such as lime or earth-based renders. Such coatings should allow water vapour to diffuse through, minimising the risk of liquid moisture build up within the thickness of the wall, reducing likelihood of decay. However, to date there has been very limited scientific study of this behaviour in rendered straw bale walls. The aim of the work presented in this paper was to develop understanding of the hygrothermal performance of lime rendered wheat straw bales. A test panel was subjected to varying environmental conditions, including a thermal shock, dynamic freeze–thaw exposure and hot humid conditions. Key scientific contributions of this work include data on the dynamic and steady-state hygrothermal characteristics wheat straw bale walls, combined with the application of heat and moisture modelling. This work will further support uptake of straw bale construction by designers and their wider use in energy-efficient construction projects.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".