Numerical analysis of heavy cob walls’ hygrothermal behavior
Bibliographic record
Abstract
The development of building envelope systems with low carbon footprint materials and improved hygrothermal properties is still in progress. For geosourced materials, one of the main objectives is to achieve optimal hygrothermal efficiency. Cob, a material made of clay, plant fibres, and water, stands out for its low carbon footprint and ease of application on timber-framed building structures. The main goal of this study is to assess the hygrothermal performance of eight heavy cob wall systems in eight cities in African, European, and American climates. An extensive laboratory characterization is carried out to measure the hygrothermal properties of each material. The thermal conductivity obtained after the measurements is 0.75 W/m.K and 0.87 W/m.K for red and beige clay samples, respectively, 0.52 W/m.K for the cob with 3 % fibres, and 0.2 W/m.K for the cob with 6 % fibres samples, and the porosity rates are 21, 20, 37, and 45 for the clay and cob samples, respectively. The hygrothermal simulation showed that the interior temperature of the walls made of cob with 6 % fibres and a thickness of 25 cm remained stable, regardless of external climate variations. Applying beige clay plasters to the exterior and interior surfaces of cob walls or timber structures improved thermal performance in terms of heating or cooling energy demand but also increased the walls’ moisture absorption. This increased moisture enhances the risk of mold growth within the wall structure. When used as infill materials in timber structures, the simulated composite systems generally exhibit good hygrothermal performance. However, in cold climate zones with high precipitation and heavily clouded skies, the walls may be exposed to risks of mold development. To prevent mold in these walls, install a rain screen or an air/vapor barrier membrane between the plaster and cob. This helps manage moisture and ensures proper wall drying.
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 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) | 0.000 | 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".