Modelling species fate and porous media effects for landfill leachate flow
Bibliographic record
Abstract
A numerical, multiple-species, reactive transport model, coupled to models of kinetic biodegradation, precipitation, and particle attachment and detachment for predicting landfill leachate-induced clogging in porous media for one-dimensional flow systems, is described. The finite-element method is used for transport modelling, with reactions incorporated into point-source or sink terms. The species modelled include three volatile fatty acids, active and inert suspended biomass, dissolved calcium, and inorganic particles. The clog matter consists of active biofilm, inert biofilm, and inorganic solids. A biofilm model is used to simulate the growth and decay of active biomass and removal of substrate. Precipitate accumulation and calcium removal are simulated by a model of calcium carbonate precipitation. Interphase movement between clog matter and fluid includes the processes of attachment and detachment. A geometric representation of the porous media allows porosity and specific surface to be estimated from the thickness of the accumulated clog matter. The porosity of the media can thus change spatially and temporally. The behaviour of the model is demonstrated with a hypothetical example.Key words: clogging, landfills, leachate collection systems, modelling, biofilms, mineral precipitation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".