Evaluation of Apparatus for Membrane Cleaning Tests
Bibliographic record
Abstract
Membrane cleaning is critical to the operation of membrane processes. This paper studies the impact of using four different types of bench-scale membrane systems to assess the effectiveness of different cleaning steps after the filtration of colored river water. The systems are a stirred ultrafiltration (UF) cell, a SEPA cell, a small cross-flow (CF) cell, and a six-CF-cell-in-parallel system. The effect of cleaning frequency was also investigated. The comparison was implemented in terms of flux recovery, solute removal, solute resistance removal, and changes of contact angles. The stirred UF cell was only reliable and comparable in terms of flux and flux recovery results. The six-cell-in-parallel system requires further development due to their much lower flux. For cleaning at 30-min intervals, the cleaning efficiency of membranes was similar for the three CF systems. For cleaning intervals of 2 and 4 h did not statistically affect the flux recovery for the stirred UF cell and SEPA cell. There was some irreversible fouling that could not be restored completely by clean-in-place method even with rigorous chemical treatment.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".