Durability assessment of masonry specimens built with waste fibre added cementitious composite in acidic environment
Bibliographic record
Abstract
The mortar strengthening method to augment the seismic performance of masonry buildings has become popular due to its easy application and significant improvement. However, the durability aspect of such fibre-reinforced structures is rare in the literature. Hence, the current research focuses on studying the durability of mortar/masonry specimens built with fibre-reinforced mortar against acidic environments. Three waste fibres, i.e., polyethylene terephthalate (PET), coconut, and nylon, with proportions (by weight) of 0.75%, 0.30%, and 0.20%, respectively, were used to reinforce the mortar. The specimens were exposed to 3% H2SO4 (sulphuric acid) solution for 180 and 360 days. Compression tests on mortar cubes and diagonal shear and flexural tests were carried out on masonry wallettes. It was noticed that the acidic solution had the most severe effect on unreinforced specimens compared to fibre-reinforced specimens. The reduction in change in weight (%), compressive strength (%), shear strength (%), and flexural strength (%) in the case of fibre-reinforced specimens was up to 45.1%, 27.4%, 46.5%, and 38.2%, respectively, compared to their corresponding unreinforced specimens. Furthermore, PET and nylon fibre-reinforced specimens outperformed coconut fibre-reinforced specimens. Hence, it was concluded that synthetic fibre-reinforced mortar is the better option for masonry structures for an acidic environment.
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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 | 0.000 | 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) | 0.001 | 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".