Geotechnical Characterization of a Soil-Water Treatment Sludge Mixture
Bibliographic record
Abstract
Application of soil-water treatment sludge (WTS) mixtures in earth works may reduce land disposal of WTS and exploitation of natural soils. This paper includes the geotechnical characterization and properties of a WTS and a soil-WTS mixture. The sludge was collected in a water treatment plant that generates 60 tons per day of sludge with 20-25% of solids. The investigated soil was a lateritic clayey sand, representative of a significant area of the state of Sao Paulo, Brazil. Compaction curve, plastic and liquid limits, and specific gravity of solids were obtained for WTS, soil and mixture. WTS and soil were also subjected to chemical and mineralogical characterization by X-ray fluorescence and diffraction, respectively. Compaction parameters were determined at standard proctor energy, and one-dimensional consolidation tests were carried out on compacted specimens. Results indicate that the geotechnical characteristics of the mixture are slightly different from those of the soil, and previous air-drying affects the compaction parameters of the mixture: the maximum dry unit weight increased and the optimum water content decreased for lower initial water contents in the compaction tests. Compression index Cc of the mixture is higher than that of the soil, however acceptable for a compacted soil in geotechnical works.
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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 | 0.002 | 0.001 |
| 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".