Investigation on membrane fouling in ultrafiltration of latex solution
Bibliographic record
Abstract
The low-pressure membrane applications are considered to be the most effective and sustainable methods of addressing environmental problems in treating water and wastewater that meets or exceed stringent environmental standards. Nevertheless, membrane fouling is one of the primary operational concerns that is currently hindering a more widespread application of ultrafiltration (UF) with a variety of contaminants. Membrane fouling leads to higher operating costs, higher energy demand, reduced membrane life time, and increased cleaning frequency. As a consequence, an efficient and well-planned UF process is becoming a necessity for consistent and long-term monetary returns. Examining the source and mechanisms of foulant attachment to the membrane’s surface is critical when it comes to the research of membrane fouling and its potential practical implementation. A mathematical model was developed in this study in order to predict the amount of fouling based on an analysis of particle attachments. This model was developed using both homogeneous and heterogeneous membranes, with a uniform and non-uniform pore sizes for the UF of simulated latex effluent with a wide range of particle size distribution. The objective of this mathematical model was to effectively identify and address the common shortcomings of previous fouling models, and to account for the existing chemical attachments in membrane fouling. The mathematical model resulting from this study was capable of accurately predicting the mass of fouling retained by the membrane and the increase in transmembrane pressure (TMP). In addition, predictive models of fouling attachments were derived and now form an extensive set of mathematical models necessary for the prediction of membrane fouling at a given operating condition, as well as, the various membrane surface charges. Polycarbonate and Polysulfone flat membranes, with pore sizes of 0.05 μm and a molecular weight cut off of 60,000 respectively, were used in the experimental designs under a constant feed flow rate and a cross-flow mode in UF of the simulated latex paint effluent. The TMP estimated from the model agreed with the experimentally measured values at different operating conditions, mostly within 5.0 - 8.0 % error, and up to 13.0% error for the uniform, and non-uniform pore size membranes, respectively. Furthermore, different types of membranes with a variety of molecular weight cut-off (MWCO) values were tested so as to evaluate the accuracy of the models for a generalized application. In addition , a power consumption model, incorporating fouling attachment as well as chemical and physical factors in membrane fouling, was developed in order to ensure accurate prediction and scale-up. Innovative remediation techniques were likewise developed and applied in order to minimize membrane fouling, enhance the membrane performance, and save energy. Fouling remediation methodologies included the pre-treating of the latex effluent, so as to limit its fouling propensity by using different types of surfactants as cationic and anionic, in addition to the pH change. The antifouling properties of the membranes were improved through the implementation of the membrane pH treatment and anionic surfactant treatment. Increasing the ionic strength of latex effluent or enhancing the membrane surface hydrophilicity facilitated a significant increase in the cumulative permeate flux, a substantial decrease in the total mass of fouling, and a noticeable decrease in the specific power consumption.
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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) | 0.001 | 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".