Rapid Assessment of Concrete Resistance to Physical Sulfate Attack: Effects of the Binder, the Water-to-Binder Ratio, and the Entrained Air
Bibliographic record
Abstract
Concrete surfaces in the evaporation zone above sulfate-rich soils are subject to severe damage from scaling. Such a physical sulfate attack (PSA) on concrete is a consequence of a cyclic regime between hot-dry and cold-wet environments, during which sodium sulfate crystals expand within the porous media (binder matrix or aggregate) and exert high pressure on the pore walls. Currently, no accepted standard exists for evaluating the resistance of concrete to the PSA phenomenon. In this study, an accelerated physical sulfate attack test protocol was used to determine the effect of blended cement and water-to-binder ratio on concrete resistance to PSA. The testing included a preconditioning protocol for presaturating concrete specimens in a 10% sodium sulfate solution for 15 days, with heat-drying specimens at 50°C before and after immersion. Specimens were then partially immersed in a 10% sodium sulfate solution and subjected to a cyclic regime composed of hot-dry [40°C, 30% RH] and cold-wet [8°C, 85% RH] conditions for 19 h each, separated by a 4-h transition at room temperature. Silica fume (GUb-SF), limestone (GUL), and slag (GUb-S) blended cements were used and compared with general use (GU) cement. A fifth binder (GUL-GP) contained 20% glass powder as a partial replacement of the limestone—portland cement was also used. Three different water-to-binder ratios were used for each binder: 0.35, 0.45, and 0.55. As expected, mixes with lower water-to-binder ratios showed the best performance against PSA, i.e., the lowest mass loss after 15 cycles of exposure (30 days). GUb-SF cement improved the resistance of mixtures with a high water-to-binder ratio compared to GU mixtures. Contrary to silica fume and slag, limestone reduced the resistance of concrete to PSA and showed the highest rate of visual damage for all water-to-binder ratios.
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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".