Influence of Magnesium Sulfate on Self-Compacting Alum Sludge Concrete Incorporating with Pozzolanic Materials
Bibliographic record
Abstract
Self-compacting concrete (SCC) is a new revolution in concrete technology that made with no vibration equipment in placing and compaction. Totally, filling formwork and accomplishing full compacting under its own weight only, even when is attendance of crowded reinforcement. One of the issues that impact SCC durability is sulphate attack. The influence of magnesium sulfate attack was investigated for SCC having treated alum sludge (TAS) with ordinary Portland cement (OPC) at replacement ratios of 5%, 10%, 15% and 20% as well as, six SCC containing TAS, fly ash (FA), silica fume (SF) and natural zeolite (NZ) replaced cement by15%, 15%, 6% and 10%, respectively. By visual inspection of all samples of SCC, there was no indication of deterioration on the surface of samples after 90 days and 180 days. In terms of compressive strength, there was developed with samples substituted OPC by 15% TAS compared with control SCC and the others SCC replacement levels. A similar conclusion was observed of the characteristics of SCC on weight compared with control SCC. Results proved that the SCC contain TAS have higher resistance against sulfate attack as well as the maximum value of mass loss and variation in weight are noted for the control SCC compared with SCC content TAS. Finally, in spite of the system of blended in SCC was investigated in several studies and so far, more investigations are required to fully explore its behavior, especially with new materials which is alum sludge that refer to the pioneering aspect of the present.
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 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 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".