Evaluation of the induced mechanical deterioration of ASR-affected concrete under varied moisture and temperature conditions
Bibliographic record
Abstract
Moisture and temperature are critical for developing alkali-silica reaction (ASR) in concrete. However, the influence of these exposure conditions on ASR-induced deterioration, specifically mechanical property losses, has not been well studied. To further our understanding, concrete cylinders made with Spratt reactive coarse aggregates and boosted in alkalis to 5.25 kg/m³ N a 2 O e q were manufactured and stored at three different temperatures (i.e., 21 °C, 38 °C, and 60 °C) under numerous relative humidities (i.e., 100 %, 90 %, 82 %, 75 %, and 62 %). The reduction in mechanical properties was assessed using the stiffness damage test (SDT), direct shear and compressive strength tests. Overall, most results for mechanical properties showed a strong linear trend with expansion, with the exception of the modulus of elasticity and shear strength. In low moisture conditions that experienced both drying shrinkage and ASR, the expansion level associated with a given mechanical property loss differs from that in high moisture conditions due to early age cracks that developed in the cement paste. In most published research, expansion is the primary criteria used in assessing role of exposure conditions. However, it was found that expansion levels alone are not reliable indicators of induced deterioration due to the coupled mechanism. Furthermore, the impact of this phenomenon varies with the different mechanical properties assessed. Additionally, the moisture threshold required for the reaction was evaluated by considering the impact on mechanical properties.
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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 | 0.000 | 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) | 0.000 | 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".