Applicability of the Accelerated Mortar Bar Test for Alkali-Silica Reactivity of Recycled Concrete Aggregates
Bibliographic record
Abstract
Abstract Using recycled concrete aggregate (RCA) as a replacement for natural aggregate in new concrete is a promising way to increase the overall sustainability of new concrete. This has been hindered, however, by a general perception that RCA is a sub-standard material because of the lack of technical guidance, specifically related to long-term durability, on incorporating RCA into new concrete. The goal of this research was to determine whether current testing methods (namely, ASTM C1260) for assessing natural aggregate susceptibility to alkali-silica reactivity could be used to assess the potential reactivity of concrete incorporating RCA. Seven different RCA sources were investigated. It was determined that ASTM C1260 was effective in detecting reactivity, but expansion varied based on RCA processing. Depending on the aggregate type and the extent of processing, up to a 100 % increase in expansion was observed. Replicate testing was performed at four university laboratories to evaluate the repeatability and consistency of results. The authors recommend modifications to the mixing and aggregate preparation procedures when testing the reactivity of RCA using ASTM C1260.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".