Investigation of Alkali-Silica Reactivity in Sustainable Ultrahigh Performance Concrete
Bibliographic record
Abstract
Considering its superior engineering properties, ultrahigh performance concrete (UHPC) has emerged as a strong contender to replace normal strength concrete (NSC) in diverse construction applications. While the mechanical properties of UHPC have been thoroughly explored, there is still dearth of studies that quantify the durability of UHPC, especially for sustainable mixtures made with local materials. Therefore, this research aims at investigating the alkali-silica reactivity (ASR) potential in sustainable UHPC in comparison with that of NSC. Sustainable UHPC mixtures were prepared using waste untreated coal ash (CA), raw slag (RS), and locally produced steel fibers. UHPC and benchmark NSC specimens were cast for assessing the compressive strength, flexural strength, and ASR expansion. Specimens were exposed to two curing regimes: accelerated ASR conditions (as per ASTM C1260) and normal water curing. UHPC specimens incorporating RS achieved higher compressive and flexural strengths in comparison with that of identical UHPC specimens made with CA. ASR expansion of control NSC specimens exceeded the ASTM C1260 limits (>0.20% at 28 days). Conversely, experimental results demonstrate that UHPC specimens incurred much less ASR expansion, well below the ASTM C1260 limits. Moreover, UHPC specimens incorporating steel fibers exhibited lower expansion compared to that of companion UHPC specimens without fibers. It was also observed that the mechanical properties of NSC specimens suffered more drastic degradation under accelerated ASR exposure compared to UHPC specimens. Interestingly, UHPC specimens exposed to accelerated ASR conditions attained higher mechanical properties compared to that of reference identical specimens cured in normal water. Therefore, it can be concluded that ASR exposure had insignificant effect on sustainable UHPC incorporating CA and RS, especially for specimens incorporating fibers. Results indicate that UHPC is a robust competitor to NSC for the construction of mega-scale projects where exposure to ASR conducive conditions prevails.
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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".