Properties of Fiber-Reinforced Mortars Incorporating Nano-Silica
Bibliographic record
Abstract
Repair and rehabilitation of deteriorating concrete elements are of significant concern in many infrastructural facilities and remain a challenging task. Concerted research efforts are needed to develop repair materials that are sustainable, durable, and cost-effective. Research data show that fiber-reinforced mortars/concretes have superior performance in terms of volume stability and toughness. In addition, it has been recently reported that nano-silica particles can generally improve the mechanical and durability properties of cement-based systems. Thus, there has been a growing interest in the use of nano-modified fiber-reinforced cementitious composites/mortars (NFRM) in repair and rehabilitation applications of concrete structures. The current study investigates various mechanical and durability properties of nano-modified mortar containing different types of fibers (steel, basalt, and hybrid (basalt and polypropylene)), in terms of compressive and flexural strengths, toughness, drying shrinkage, penetrability, and resistance to salt-frost scaling. The results highlight the overall effectiveness of the NFRM owing to the synergistic effects of nano-silica and fibers.
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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".