Salt Scaling of Pervious Concrete: Optimizing a Test Method and The Effects of Different Deicers
Bibliographic record
Abstract
There is currently no standard test method for evaluating the resistance of pervious concrete to salt scaling. In this study, a number of test methods were evaluated to determine an effective test method. A number of parameters were varied, including sample geometry, cycle length, level of submersion, and the effects of various deicers. The optimum cycle length was found to be 24 hours with the submersion of the bottom 10 mm of the pervious concrete samples made with 14 mm aggregate. Cylinder samples with a diameter of 100 mm and height of 150 mm are recommended as they provide consistent results. Using these samples, a mass loss failure criterion of 3 to 5% is proposed. The deicers that caused the most damage are NaCl, CaCl2, and urea, followed by MgCl2, K acetate, Na acetate, and CMA. More testing is needed to validate the effects of different deicers. i
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".