Design Improvement of Immobilized Photocatalytic Reactors Using a CFD-Taguchi Combined Method
Bibliographic record
Abstract
An effective optimization design approach which combines CFD modeling and the Taguchi DOE method is presented for immobilized photocatalytic annular reactors used for water treatment. The analyzed reactor design incorporated the use of repeated ribs for improving the external mass transfer to the TiO 2 -coated wall. The CFD model was experimentally evaluated using 2,4-D as a model pollutant, providing close predictions of the photocatalytic degradation performance of the photoreactors over a wide range of Reynolds numbers (300 < Re < 10 000). The statistical analysis showed that the performance of the studied annular photocatalytic reactors was improved up to 60% using the ribs. A comparison of different reactor design factors indicated that better performance can be obtained using small outer tube diameters, large inner/outer tube diameter ratios, large (rib height)/(hydraulic diameter) ratio, and small (rib pitch)/(rib height) ratios. In addition, it was concluded that the (rib height)/(hydraulic diameter) ratio was the design parameter having the greatest impact (57%) on photoreactor performance.
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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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".