Three clean products from co-mingled waste using a novel hydrodynamic separator
Bibliographic record
Abstract
Mixed municipal solid waste currently landfilled contains a high percentage of packaging glass, varying from 33% to 80% by weight according to several sample characterizations, due to the lack of high throughput separation technology.The hydrodynamic separator proposed is a closed-loop device developed to separate co-mingled waste into plastics, glass and other dense particles and organic sludge.The glass and other dense material stream is cleaned by the system, permitting efficient downstream optical sorting to take out metals and ceramics and, if required, glass sorted by colour.The plastics and the organic sludge are separate, processable waste streams.As the solid waste is introduced in the separator, the action of water jets located on the ramps of a fixed sinusoidal-shape bottom and the presence of hydrofoils at the upper part of the tank produce a flow pattern that lead plastics towards its collection point on the surface, while glass and ceramics are settled to the bottom of the tank and transported to the extraction point.Organics and other fine particles are obtained from lamellas, before reintroducing the clarified fluid into the flow loop.The sludge obtained from this process is suitable for feedstock to Anaerobic Digestion processes.In the present paper the equipment and the methodology is described and the physical principles of the separation process are explained.Results from a full scale trial designed to process 9.7 tonnes per hour at a municipal UK waste site operating in Nov 2015 -Feb 2016 are presented.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".