Experimental Characterization of Raw Earth Properties for Modeling Their Hygrothermal Behavior
Bibliographic record
Abstract
Raw earth is one of the oldest building materials of mankind. Almost a third of the world’s population is living in an earth-based house. However, their use remains low compared to conventional materials such as concrete, steel, and wood. Although these geosourced materials are abundant, recyclable, and have a low environmental footprint, their use is very limited in the construction sector. This can be explained by the lack of data regarding their hygrothermal behavior. In this context, the present work aims to highlight the properties of cob construction material with straw addition. An experimental characterization of hygrothermal and microstructural properties has been carried out. Thermal conductivity, specific heat, sorption isotherms, moisture storage capacity, moisture buffer value (MBV), and water vapor permeability are obtained experimentally. Then, the collected data are used as input parameters of a numerical prediction model to numerically assess the thermal and hygric behavior. Cob is then compared to other more commonly used materials to highlight the benefits of its use within the context of the energetic and environmental transition. Our results will allow better understanding of the behavior of the new geosourced material thanks to experimental and numerical investigation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".