Response of concrete to cyclic environments and chloride-based salts
Bibliographic record
Abstract
The shift towards performance-based standards and specifications for concrete requires the development of holistic tests that better correlate to field conditions, which can reliably evaluate the performance of normal and emerging types of concrete. In the current study, the response, in terms of physico-mechanical properties and microstructural features, of concrete made with different types of cement (general use [GU] and Portland limestone cement [PLC]) without or with fly ash and nanosilica to chloride-based de-icing salts (individual and combined) was assessed when cyclic environmental conditions were considered. The results revealed the coexistence of complex deterioration processes in concrete under this combined exposure. The combined salt (MgCl2+CaCl2), which simulates using a synergistic maintenance and protective strategy for concrete in cold regions, was the most aggressive solution. PLC concrete mixtures exhibited better resistance to de-icing salts compared to GU mixtures due to synergistic physical and chemical actions of limestone in the matrix. The incorporation of 30% fly ash had a pronounced effect on improving the durability of concrete to the combined exposure, and this performance was much enhanced when nanosilica was incorporated in the cementitious system.
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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 | 0.001 |
| 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".