Use of the Accelerated Mortar Bar Test to Evaluate the Effectiveness of LiNO3 Against Alkali-Silica Reaction—Part 2: Comparison with Results from the Concrete Prism Test
Bibliographic record
Abstract
Abstract For the time being, the concrete prism test (CPT) CSA A23.2-14A or ASTM C1293 remains the most reliable test method to evaluate the effectiveness of lithium nitrate against alkali-silica reaction (ASR) in concrete; however, the extended testing period of two years has often limited its acceptance by practitioners. In its actual form, the popular accelerated mortar bar test (AMBT) CSA A23.2-25A or ASTM C1260 cannot be used to predict this effectiveness, thus it needs to be modified accordingly. Part I of this study looked at the influence of a number of parameters on the effectiveness of lithium to control expansion of mortar bars incorporating a variety of reactive aggregates from Canada and the United States. The second part of this study (Part II) compares the results obtained in modified versions of the AMBT with those from the CPT performed on the same aggregates, with the objective of proposing the best accelerated test procedure for determining the minimum amount of lithium nitrate necessary to counteract ASR expansion in concrete. The results obtained in this study have shown that the effectiveness of lithium nitrate greatly varies from one reactive aggregate to another while not being correlated with the degree of reactivity or the petrographic nature of the reactive aggregates to counteract. A safe method of predicting the effective [Li]/[Na+K] to used in concrete is proposed which uses two AMBTs, one of which involves adding lithium to both the mortar bar and the soak solution. It allows the prediction of an effective [Li]/[Na+K] for aggregates that respond relatively well to lithium. The method allows the identification of aggregates that respond particularly badly to the lithium, for which the concrete prism test is recommended for evaluating the minimum lithium dosage to use for ASR control.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".