Optimization of an External Nanofiltration Anaerobic Membrane Bioreactor Treating a High-Strength Starch-Based Wastewater
Bibliographic record
Abstract
Membrane and reactor performance for an anaerobic membrane bioreactor (AnMBR) treating a high-strength starch-based wastewater [average chemical oxygen demand (COD) of 84.8±8.9 g/L] was examined under six varied cleaning protocols to find optimal operating conditions. The AnMBR was composed of a 1,000-L anaerobic continuous stirred tank reactor (CSTR) integrated with an external, tubular nanofiltration membrane module operated in cross-flow mode. The polyvinylidene fluoride–based membrane module had a nominal pore size of 30 nm, a total membrane area of 0.42 m2, and a cross-flow velocity of 2.5 m/s. The different cleaning protocols were provided by varying the membrane’s permeate backwash duration, frequency, and flow rate and by incorporating chemically enhanced backwash cycles with the use of a mixed 250-ppm sodium hydroxide and 250-ppm hypochlorite solution. Reactor performance did not appear to be cleaning protocol dependent; however, a decline in reactor-specific methanogenic activity (SMA) was noticed over the duration of the study. A single, longer-duration chemically enhanced backwash offered the highest improvement in membrane performance over all other cleaning protocols.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".