Mechanical behaviors of a synthetic paste of tire chips and paper sludge in MSW landfill daily cover applications
Bibliographic record
Abstract
A waste-derived paste of a mixture of paper sludge and tire derived aggregate (TDA) was investigated for daily cover application in municipal solid waste (MSW) landfills. The use of earth materials as daily covers not only consumes valuable landfill space, but also creates a series of operating issues. In this study, an experimental testing program was undertaken with the goal of evaluating the mechanical behaviors of the paste based on the findings of the index properties, compressibility, hydraulic conductivity, stress-induced deformation, stress–strain response, and shear resistance of the materials. The mechanical behaviors of the individual TDA, the sludge, as well as the mixture of the two, were evaluated. When compared to traditional soil covers, the proposed paste was: (i) 2–3 times lighter in weight; (ii) at least two orders of magnitude more impermeable; and (iii) comparable in shear resistance. It was also found that with the addition of TDA to the sludge, the shear strength of the paste was improved considerably. The reinforcing mechanisms were explored and quantified, suggesting an optimal TDA content of about 55% by weight. The results from this study indicate that the proposed paste has mechanical characteristics that are desirable for a potential landfill daily cover.
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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) | 0.001 | 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".