Characterization of performance of full-scale tertiary membranes under stressed operating conditions
Bibliographic record
Abstract
This study sought to identify factors responsible for enhanced fouling of ultrafiltration membranes used in tertiary wastewater treatment under challenging conditions of high flow and low temperature. A detailed analysis of full-scale membrane operating data was conducted, and this was supported by data gathered through a field sampling campaign. Higher average fouling rates and average recoveries were observed during periods of highest flows and lowest temperatures. The results demonstrated that the negative impact of seasonal changes on short-term fouling are readily reversible, while hydraulically irreversible fouling, which is responsible for intermediate and long-term fouling rates, is not effectively recovered by maintenance cleans (MCs) but is recovered by recovery cleans (RCs). An examination of membrane feedwater quality revealed that high fouling rates correlated to an increase in dissolved organic carbon (DOC) concentrations, with the biopolymer fraction of the DOC being most important. Increased capillary suction time (CST) values, which indicate reduced sludge dewaterability, were also observed during high fouling events. It was concluded that seasonal variations result in the increased release of extracellular polymeric substances (EPS) by microorganisms, which leads to higher membrane fouling and worsened dewaterability of the activated sludge.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 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".