Improving the Fire-Resistance Rating of Concrete Masonry Walls using Insulations An Experimental and Numerical Study
Bibliographic record
Abstract
For non-loadbearing applications, the 15 cm blocks are usually used. They are lightweight, easy to install, and are cost effective. The fire resistance rating of the 15 cm block is about 1 h, while that of a 20 cm block is about 2 h. This reduced fire resistance rating is due to smaller cells which leads to more convective and radiative heat transfer inside of the block cells, as well as the reduced face cells that cause the blocks to heat up quicker. With the use of lightweight insulation materials as cell fillers, an improvement in the fire resistance rating was achieved for the 15 cm block. These materials were able to reduce the convective and radiative heat transfer in the cells. For the experimental and numerical analysis carried out, vermiculite, and gypsum were able to improve the fire ratings by at least 1h.
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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".