Utilization of Sewage Sludge Ash in Self-Compacted Concrete
Bibliographic record
Abstract
Rapid urbanization throughout the world resulted in a considerable amount of sewage sludge, which is commonly considered a great environmental concern.Also, the rapid growth of self-compacting concrete (SCC) marks a significant milestone in enhancing the construction industry's effectiveness.Hence, an experimental program was carried out to study self-compacting concrete (SCC) properties incorporating sewage sludge ash (SSA) as a partial replacement of cement.Mixes were prepared with two percentages (0 and 20% by mass) of SSA as partial replacement of cement.The slump flow, T50 flow time, J-ring, and V-funnel were evaluated for the fresh SCC.Hardened properties of SCC were assessed by measuring compressive strength, rapid chloride penetration, bulk electrical resistivity, water absorption rate (i.e., sorptivity), and water permeability.Test results indicated that SCC made with SSA must incorporate a higher dosage of admixtures than the control mix to achieve satisfactory workability, passing ability, and viscosity.SSA contributed to the concrete mix's late strength development and led to durable concrete with a low chloride permeability resistance and a high electrical resistivity.There was a negligible increase in the rate of water absorption and water permeability.However, the water absorption rate and permeability are expected to reduce with age due to the pozzolanic reaction of SSA.SSA was found to have the potential to be used as partial cement replacement in making SCC, which could lead to a profound impact on solid waste management and sustainable development in the construction industry.
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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) | 0.000 | 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 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".