Bibliographic record
Abstract
The performance of ultraviolet (UV) reactors used for water treatment is greatly influenced by the reactor hydrodynamics, due to the non-homogeneity of the UVradiation field. Yet, a present lack of rigorous quantitative understanding of the flow behavior in such reactor geometries is shown to limit the versatile and efficient optimization of UV reactors. In this research, the key characteristics of turbulent flow in annular UV-reactors and its influence on reactor performance were studied using particle image velocimetry (PIV) measurements and computational fluid dynamics (CFD) simulations. Two conceptual reactor configurations, with inlets either concentric (L-shape) or normal (U-shape) to the reactor axis, were investigated experimentally. The time averaged velocity data revealed a strong dependency of the hydrodynamic profile to the inlet position. The frontal inlet of the L-shape reactor resulted in an expanding jet flow with high velocities close to the radiation source (UV-lamp) and areas of recirculation close to the inlet. The perpendicular inlet of the U-shape reactor brought about higher velocities along the outer reactor walls far from the central lamp. Numerical simulations, using a commercial CFD software package, Fluent, were performed for the L- and U-shape reactor configurations. The influences of mesh structure and the Standard n-e, Realizable K-e, and Reynolds stress (RSM) turbulence models were evaluated. The results from the Realizable «-e and RSM models were in good agreement with the experimental findings. However, the Realizable K-e model provided the closest match under the given computational restraints. UV disinfection models were developed by integrating UV-fluence rate and inactivation kinetics with the reactor hydrodynamics. Both, a particle tracking (Lagrangian) random walk model and a volumetric reaction rate based (Eulerian) model were implemented. The performance results of the two approaches were in good agreement with each other and with the experimental data from an industrial prototype reactor. The simulation results provided detailed information on the velocity profiles, reaction rates, and areas of possible short circuiting within the UV-reactor. It is expected that the application of the verified integrated CFD models will help to improve the design and optimization of UV-reactors.
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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) | 0.000 | 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 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".