Clogging of Tire Shreds and Gravel Permeated with Landfill Leachate
Bibliographic record
Abstract
The clogging of tire shreds and gravel is based on four column tests permeated with landfill leachate for up to 2years . Two different types of tire shred (G shred: 100mm×50mm×10mm ; and P shred: 125mm×40mm×10mm with many exposed wires) and a uniformly graded 38mm gravel were examined. The compressibility of the G and P shreds at 150kPa were reported to be 48 and 44%, respectively while the initial hydraulic conductivities were 0.007 and 0.02m∕s , respectively (compared to 0.8m∕s for the gravel). The gravel maintained a hydraulic conductivity greater than 10−5m∕s for about three times longer than a similar thickness of compressed (at 150kPa ) tire shreds. The tests were conducted at an accelerated flow rate of 0.4m3∕m2∕day . At termination of the rubber shred columns after about 1year the hydraulic conductivity at the influent end of the columns had dropped to between 10−7 and 10−8m∕s . At termination of the gravel columns after 2years the corresponding range was 10−6–10−7m∕s . The clog was predominantly calcium carbonate, with calcium making up 29–34% of the total clog material. Aluminum, zinc, iron, and copper leached from the P and G shreds when exposed to typical municipal solid waste leachate, however they were not detected in the effluent leachate. The highest concentration of metals was found in the P-shred clog and this is attributed to the greater abundance of exposed steel in these shreds. It is inferred that gravel should continue to be used in critical zones where there is a high mass loading. The results suggest that an increased thickness of compressed tire shred may be used to give a service life similar to that of a given thickness of gravel in noncritical zones.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".