Hydrodynamics and Energy Analysis in Suspended Catalyst Photocatalytic Membrane Reactors
Bibliographic record
Abstract
Photocatalysis is a non-selective advanced oxidation process (AOP) that can be effective for degradation of toxic compounds. Its main drawback however has been high processing costs compared to other AOPs. Suspended catalyst photocatalytic membrane reactors (SPMR) are promising design configuration for implementation of the technology. This work involves experimental and theoretically analysis of the hydrodynamics and energy consumption in a SPMR under crossflow and oscillatory shear conditions. An optimization approach is presented for intensification of the reactor performance that considers the coupling effects of the applied shear and the transmembrane pressure on the hydrodynamics and the specific energy consumption (kWh/m 3 ). The results showed that the optimum shear rate decreases with increasing the membrane area due to the relatively high contribution of the permeate pumping power to the energy consumption which makes the advantages of operating at higher shear rate relevant. This trend changes for larger membranes areas where the energy consumption due to higher shear outweighs the advantage of its performance enhancement resulting in increasing the system specific energy consumption. In general, the latter was found to be higher for a crossflow system compared to an oscillatory membrane design, which in addition to its smaller footprints, can make such design an attractive option for confined and/or limited space applications.
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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 | 0.000 | 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) | 0.000 | 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".