Response of Concrete to Incremental Aggression of Sulfuric Acid
Bibliographic record
Abstract
Abstract There is lack of standardized tests for specifically evaluating the resistance of concrete to sulfuric acid attack, which has caused great variability, for example, in terms of solution concentration, pH level/control, etc., among previous studies in this area. Accordingly, there are conflicting data about the role of key constituents of concrete (e.g., supplementary cementitious materials [SCMs]) and uncertainty about building codes’ stipulations for concrete exposed to sulfuric acid. Hence, the aim of this study was to assess the behavior of the same concretes, prepared with single and blended binders, to incremental levels (mild, severe, and very severe) of sulfuric acid solutions over 36 weeks. The test variables included the type of cement (general use [GU] or portland limestone cement [PLC]) and SCMs (fly ash, silica fume, and nanosilica). The severe (1 %, pH of 1) and very severe aggression (2.5 %, pH of 0.5) phases caused mass loss of all specimens, with the latter phase providing clear distinction among the performance of concrete mixtures. The results showed that the penetrability of concrete was not a controlling factor under severe and very severe damage by sulfuric acid attack, whereas the chemical vulnerability of the binder was the dominant factor. Mixtures prepared from the PLC performed better than those prepared from GU. While the quaternary mixtures that consisted of GU or PLC, fly ash, silica fume, and nanosilica showed the highest mass losses after 36 weeks, the binary mixtures incorporating GU or PLC with fly ash had the lowest mass losses.
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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) | 0.001 | 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".