Sulfate Resistance of Recycled Aggregate Concrete with GGBS and Fly Ash-Based Geopolymer
Bibliographic record
Abstract
There is a constant drive for the development of ultra-high-performance concrete using modern green engineering technologies. These concretes have to exhibit enhanced durability and incorporate energy-saving and environment-friendly functions. The object of this work was to develop a green concrete with an improved sulfate resistance. In this new type of concrete, recycled aggregates from construction and demolition (C&D) waste were used as coarse aggregates, and granulated blast furnace slag (GGBS) and fly ash-based geopolymer were used to totally replace the cement in concrete. This study focused on the sulfate resistance of this geopolymer recycled aggregate concrete (GRAC). A series of measurements including compression, X-ray diffraction (XRD), and scanning electron microscopy (SEM) tests were conducted to investigate the physical properties and hydration mechanisms of the GRAC after different exposure cycles in a sulfate environment. The results indicate that the GRAC with a higher content of GGBS had a lower mass loss and a higher residual compressive strength after the sulfate exposure. The proposed GRACs, showing an excellent sulfate resistance, can be used in construction projects in sulfate environments and hence can reduce the need for cement as well as the disposal of C&D wastes.
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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 | 0.001 | 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".