Consolidation behavior and shear strength characteristics of polymer-paste tailings barrier
Bibliographic record
Abstract
Waste containment facilities, such as landfills and tailings storage facilities, rely on barrier (liner, cover) materials to prevent hazardous contaminant migration. Recently, polymer-enhanced paste tailings (PP) barriers, made from a compacted mixture of paste tailings and superabsorbent polymer (SAP), have emerged as a promising solution for sustainable waste containment due to their low permeability. However, although compacted PP shows promising hydraulic properties, its mechanical characteristics relevant to barrier functionality, such as consolidation behavior and shear characteristics, are not yet understood. No studies have assessed these mechanical characteristics. This study investigates the consolidation behavior and shear strength characteristics of polymer-paste tailings (PP) barriers incorporating superabsorbent polymers (SAPs). Compacted PP samples with different concentrations of SAP (0.0%, 0.2%, 0.5%) were prepared, and the samples were subjected to consolidation and shear tests. Consolidation behavior was investigated using oedometer tests, monitoring settlement over time under different stress conditions. In addition, shear characteristics were assessed by direct shear tests to evaluate the material's resistance to shearing and deformation under different normal stresses. The results indicated that increasing SAP content accelerates the consolidation process. In contrast, the shear strength of the material increases with SAP content up to 0.2%, after which it decreases when the SAP content reaches 0.5%. This means that the shear strength of the compacted PP is strongly dependent on the amount of SAP concentration. Specifically, the cohesion increases with higher SAP content, whereas the friction angle decreases with increasing SAP content. These findings highlight the importance of balancing SAP content to achieve a stable and efficient barrier system. The findings position this PP material as an attractive option for barrier design, offering the benefits of minimizing waste management and lowering the expenses associated with tailings management at the earth's surface.
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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) | 0.003 | 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".