Nano-modified slag-based cementitious composites reinforced with multi-scale fiber systems
Bibliographic record
Abstract
This thesis responds to the need for improving the overall performance of concrete infrastructure to achieve longer service life, fewer cycles of repair, and reduced life-cycle costs. Novel high-performance fiber-reinforced cementitious composites were developed, which comprised high content (50%) slag by mass of the base binder as well as nano-silica (NS) or nano-crystalline cellulose (NCC). In addition, nano-fibrillated cellulose (NFC), and a novel form of basalt fiber strands protected by polymeric resins: basalt fiber pellets (BFP), representing nano-/micro- and macro-fibers, respectively were incorporated in the composites. The response surface method was used in the statistical modeling part to evaluate the impact of key factors (NS, NCC, NFC, BFP) on the performance of 15 mixtures. The composites were assessed in terms of setting times, early- and late-age compressive strength, flexural performance, and resistance to freezing-thawing cycles, and the bulk trends were corroborated by fluid absorption, thermogravimetry and microscopy tests. Moreover, selected high-performance composites were extracted from laboratory testing and numerical optimization scenarios to access their suitability as a repair/overlay option for concrete flatwork. While the addition of BFP reduced the compressive and flexural capacity of the composites by an average of 20% and 37%, respectively, after 28 days, the co-existence of NCC and/or NFC alleviated this trend. Furthermore, all nano-modified composites with multi-scale fibers showed notable improvement in terms of post-cracking flexural performance (residual strength up to 7.9 MPa, and toughness up to 46.8 J) and resistance to ingress of fluids (absorption less than 2.5%) and frost action (durability factor more than 90%. Generally, all composites selected for use as a repair/overlay option showed superior qualities: high mechanical and durability properties, as well as mechanical compatibility with substrate concrete. In particular, composites incorporating (up to 3.75%) NS and (0.0375–0.1) NCC in slag-based composites, with (0.25–0.375) NFC and (4.5%) BFP, which can be an effective option for flatwork toppings requiring balance between high-strength, ductility and durability.
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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".