Thermal performance of plastered rice straw bales and walls: a case study
Bibliographic record
Abstract
Straw, as a fi ber, has been used as part of building materials for several years. A carefully constructed strawbale building has excellent thermal performance because of the combination of the high isolative value of the bales and the thermal mass provided by the thick plaster coating of the interiors. This paper addresses the thermal performance of rice straw bales and walls plastered with different cement plaster mixes. The plaster mixes are applied on straw bales of thickness 45 cm. A fi re resistance test is conducted for two complete hurs on the bales using direct fl ame after which the fl ame was discontinued. According to the test results, the mix with equal parts of cement and lime showed acceptable mechanical properties. This mix is chosen to be applied on a prototype straw bale wall compartment with an aim to evaluate the thermal performance of the plastered straw bale walls in arid desert climate at the hottest month of the year in Egypt. The straw bale wall test is undertaken by collecting actual measurements on site. Thermal sensors are installed on both external and internal sides of the wall to record the heat transmission through the plastered walls. The results showed that all the plastered bales survived fi re penetration for the life period of the test. Increasing the lime content and decreasing the cement content of the mix raises the possibility of weak areas in the plaster of straw bale walls causing cracks during direct fi re exposure. Similar width and density of the bales for all the specimen mixes didn't affect the heat transmission through the bales, which did not exceed 5.3C in all samples. The site readings on the straw bale walls showed high range of temperature fl uctuation on the external wall sensor, while in the internal wall sensor the temperature fl uctuation was kept to minimum values. It was concluded that due to their high thermal insulation, straw bale structures require comparatively less energy to sustain thermal comfort conditions.
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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".