Deicer Scaling Resistance of Concrete Mixtures Containing Slag Cement Phase 2: Evaluation of Different Laboratory Scaling Test Methods, TPF-5(100), 2012
Bibliographic record
Abstract
With the use of supplementary cementing materials (SCMs) in concrete mixtures, salt scaling tests such as ASTM C672 have been found to be overly aggressive and do correlate well with field scaling performance. The reasons for this are thought to be because at high replacement levels, SCM mixtures can take longer to set and to develop their properties: neither of these factors is taken into account in the standard laboratory finishing and curing procedures. As a result, these variables were studied as well as a modified scaling test, based on the Quebec BNQ scaling test that had shown promise in other research. \n \nThe experimental research focused on the evaluation of three scaling resistance tests, including the ASTM C672 test with normal curing as well as an accelerated curing regime used by VDOT for ASTM C1202 rapid chloride permeability tests and now included as an option in ASTM C1202. As well, several variations on the proposed draft ASTM WK9367 deicer scaling resistance test, based on the Quebec Ministry of Transportation BNQ test method, were evaluated for concretes containing varying amounts of slag cement. A total of 16 concrete mixtures were studied using both high alkali cement and low alkali cement, Grade 100 slag and Grade 120 slag with 0, 20, 35 and 50 percent slag replacement by mass of total cementing materials. Vinsol resin was used as the primary air entrainer and Micro Air® was used in two replicate mixes for comparison. \n \nBased on the results of this study, a draft alternative test method to ASTM C762 is proposed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.024 | 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 teacher head, 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".