Influence of Type and Compositions of SCMs on Expansion of Mortar Bars from Alkali Silica Reaction
Bibliographic record
Abstract
The effect of different local pozzolans, as a supplementary cementitious material (SCM), on the expansion of mortar bar due to Alkali Silica Reaction (ASR) were reported in this paper.Accelerated test on specimens using local volcanic aggregates, rhyolite, was used to investigate and to compare the effects of fly ash (FA) and metakaolin (MK) on the suppression of the length change.In this study, three different percentages of FA, namely, 20, 35 and 50 and three of MK, namely, 10, 15 and 20 were used as cement replacement.The results at 14 days showed slight decrease expansions for 20% FA replacement of 0.073% but the lowest expansions were 0.025% and -0.001%, respectively for 35% FA and 10% MK, compared to 0.176 % of the control mix.Increase the SCMs to 50% FA and 15-20% MK yielded reduction of expansion to the innocuous level.Results from 28 days acceleration registered a slight increase in expansion for FA mixes of 35 and 50% and all MK mixes, but still less than 0.10%, the threshold for innocuous level.Chemical composition analysis revealed decrease in CaO/SiO2 and CaO/Al2O3 ratio of the cementitious systems.This correlated with the expansion reduction.But alumina in Al2O3/SiO2 ratio showed the dominant effect on ASR suppression.Microstructures of all materials and casted specimens were also studied in detail.Considering all aspects, these SCMs, used in suitable amount were considered good candidates for ASR prevention in new concrete structures for both short and long term
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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) | 0.000 | 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".