The performance and durability of concrete with ternary blends of silica fume and blast-furnace slag
Bibliographic record
Abstract
In a harsh service environment such as Canada's, concrete must be resistant to many physical and chemical deterioration processes. Supplementary cementing materials (SCM's) are commonly employed to increase the durability performance of concrete. However, incorporating a single SCM to improve a concrete's rheology or a specific durability property has associated limitations with its use. Using a single SCM to address one durability concern may result in failure due to another. For example, the replacement level of a single SCM needed to prevent ASR expansion may create other problems or concerns. The incorporation of 50% slag or greater than 20% fly ash needed to ensure adequate protection against ASR may lead to poor resistance to deicer salt scaling. Another example of material incompatibility is the incorporation of silica fume at levels greater than 10% by mass of cement. Such replacement levels are necessary to prevent ASR expansion, but typically lead to problems with the workability of the fresh concrete as well as difficulties adequately dispersing the silica fume. The primary objectives of this study were as follows: (1) To establish effective combinations of Portland cement, silica fume, and blastfurnace slag to mitigate deleterious ASR expansion with Canadian reactive aggregates; (2) To assess the durability performance of ternary blends considering deterioration mechanisms experienced in Canada; (3) To characterize the mechanisms by which silica fume and blastfurnace slag affect ASR in concrete; (4) To provide advice on the use of ternary blends with Canadian reactive aggregates to produce durable and stable concretes. The effectiveness of ternary blends in controlling deleterious expansion due to alkali-silica reaction with Canadian aggregates was assessed, and advice was provided to allow the appropriate selection of ternary blends containing silica fume and blastfurnace slag. The understanding of the effect of ternary blends on pore solution alkalinity, the primary mechanism by which SCM's control ASR expansion, was also furthered. As well, the efficacy by which calcium hydroxide is removed by ternary mixtures (pozzolanically and by dilution) was investigated. Based on expansion testing and mechanisitic studies, predictive empirical and statistical models were developed. Information on the durability performance of ternary blended concrete was provided in both a laboratory setting as well as in an outdoor field exposure setting. Thus providing an opportunity to evaluated and correlated laboratory experience to outdoor field exposure. (Abstract shortened by UMI.)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".