Membrane filtration of the liquid fraction from a solid–liquid separator for swine manure using a cationic polymer as flocculating agent
Bibliographic record
Abstract
The liquid fraction from a solid-liquid separator for swine manure, which used a cationic polymer to promote particle flocculation, was processed by one nanofiltration and two reverse osmosis spiral-wound membranes. Eight different liquid fraction batches (750 to 1750 L) were concentrated at volumetric concentration ratios (VCRs, initial to final volumes) ranging from 2.3 to 4.2. Membrane fouling intensity was highly variable, as water flux recovery after concentration cycles ranged from 13% to 88%. The most severe fouling was caused by a liquid fraction that had relatively low suspended solids (SS) (774 mg/L) and was concentrated at a low VCR of 2.6. Raw manure collected the same day also contained low SS, suggesting that fewer sites were available for polymer adsorption and thus more polymer remained in the liquid. However, because of the high opacity of the samples, residual polymer could not be detected in any feed or concentrate samples. Fouling was not totally irreversible as over 97% of membrane flux could be recovered by cleaning with acidic and alkaline solutions. Further tests with spiked liquid fractions indicated that fouling due to residual polymer in solution started to occur at a polymer concentration of 3 and 11 mg/L in initial and concentrated effluents, respectively. If a cationic polymer is used to pretreat manure, the amount of added polymer would have to be closely related to SS content as opposed to manure volume, in order to leave very little residual polymer in solution.
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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) | 0.002 | 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".