Effect of plastic fragments on hydraulic characteristics of pretreated municipal solid waste
Bibliographic record
Abstract
A systematic study was undertaken of the granular composition and hydraulic properties of municipal solid waste (MSW) produced by mechanical–biological pretreatment (MBP–MSW) from three different treatment plants with the aim of evaluating the potential application of MBP–MSW as an alternative barrier material for landfill final cover systems. Despite its coarse granular composition, MBP–MSW has low hydraulic conductivity. Long-term permeability tests show that the hydraulic conductivity decreases with time. The most likely explanation for the long-term changes in permeability is the swelling of organic material contained within the compost. In the case of saturated flow, the virtually impermeable plastic fragments embedded in the material impede fluid flow. In the unsaturated case, such fragments slow down the drying process by disrupting fluid flow and allowing pooling of water above horizontally oriented fragments. The larger the number and size of the plastic fragments, the greater the influence on hydraulic conductivity and shrinkage. These processes can be better understood with the newly developed conceptual model, the thin-sheet model. Based on this conceptual model, laboratory tests were undertaken to compare natural soil material with mixtures of soil material and plastic fragments. Corresponding numerical simulations of some experiments verified the influence of plastic fragments on the hydraulic properties of MBP–MSW.Key words: mechanical–biological pretreatment, municipal solid waste (MSW), thin-sheet model, plastic fragment, hydraulic conductivity, drying test.
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 | 0.000 | 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 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".