Effect of grain size on service life of MSW landfill drainage systems
Bibliographic record
Abstract
A numerical model “BioClog-2D” is used to examine the service life and clogging of leachate collection systems with granular drainage material of different grain sizes. The modelling shows that the leachate characteristics at the end of the drainage pipe are significantly different from those in the leachate entering the leachate collection system and this reduction in leachate strength corresponds to an accumulation of clog mass within the saturated drainage layer. The calculated clog mass within the saturated drainage layer is dominated by the inorganic material, which is in encouraging agreement with field-observed data. The service life of leachate collection systems is increased with an increase in the grain size of the drainage material and decreased with an increase in the length of the drainage path. The service life of the drainage layer is shown to vary from a few years to over 100 years depending on the design of the system. The results indicate that in addition to the particle size of the granular material, the infiltration rate and leachate strength history greatly affect the estimated service life of leachate collection systems.
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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 | 0.002 |
| 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 | 0.001 | 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".