Using concrete admixtures for sulphuric acid resistance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The degradation of concrete sewer pipes by sulphuric acid attack is a problem of global scope, resulting in substantial economic losses each year. In this study, five admixtures, which offer a range of potential improvement mechanisms, were used at various dosages to enhance the resistance of concrete made with Type 50E cement to chemical sulphuric acid attack. The resistance to sulphuric acid of concrete specimens incorporating these admixtures was measured and compared to that of control specimens. An attempt was made to determine whether there is a relationship between the effect of the various admixtures on mechanical strength and porosity and the resistance of concrete to H 2 SO 4 attack. Results indicate that metakaolin reduced the mass loss of concrete specimens due to immersion for eight weeks in H 2 SO 4 solutions having concentrations of 7% and 3% (by volume) by 38 and 25%, respectively, compared with that of the control specimens. Other admixtures (OCI, Caltite and Xypex) reduced the mass loss of concrete specimens in the range 12–20% for the 7% H 2 SO 4 solution and in the range 9–16% for the 3% H 2 SO 4 solution. Although silica fume effectively increased compressive strength and reduced the porosity of concrete, its contribution to the resistance of concrete to chemical sulphuric acid was minor. No clear relationship could be established between the mechanical and physical properties of concrete (compressive strength and porosity) and its resistance to sulphuric acid attack. It was also found that the decline in compressive strength of concrete specimens subjected to H 2 SO 4 attack was directly proportional to their mass loss, following a linear relationship.
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.
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 | 0.000 |
| 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 it