Numerical study of the effects of lamp configuration and reactor wall roughness in an open channel water disinfection UV reactor

Robust optimization of a novel ultraviolet (UV) photoreactor for water disinfection: A neural network approach

To optimize the ultraviolet (UV) water disinfection process, it is crucial to determine the ideal geometric dimensions of a corresponding model that enhance performance while minimizing the impact of uncertain photoreactor inputs. As water treatment directly affects people's lives, it is crucial to eliminate the risks associated with the non-ideal performance of disinfection photoreactors. Input uncertainties greatly affect photoreactor performance, making it essential to develop a robust optimization algorithm in advance to mitigate these effects and minimize the physical and financial resources required for constructing the photoreactors. In the suggested algorithm, a two-objective genetic algorithm is integrated with a non-intrusive polynomial chaos expansion (PCE) technique. Additionally, the Sobol sampling method is employed to select the necessary samples for understanding the system's behavior. An artificial neural network surrogate model is trained using sufficient data points derived from computational fluid dynamics (CFD) simulations. A novel type of UV photoreactors working based on exterior reflectors is chosen to optimize the process with three uncertain input parameters, including UV lamp power, UV transmittance of water, and diffusive fraction of the reflective surface. In addition, four geometrical design variables are considered to find the optimal configuration of the photoreactor. The standard deviation (SD) and the reciprocal of log reduction value (LRV) are set as the objective functions, calculated using PCE. The optimal design provides a LRV of 3.95 with SD of 0.2. The coefficient of variation (CoV) of the model significantly declines up to 7%, indicating the decreased sensitivity of the photoreactor to the input uncertainties. Additionally, it is discovered that the robust model exhibits minimal sensitivity to changes in reflectivity in various flow rates, and its output variability aligns with the SD obtained through robust optimization.

Dose Distribution Scaling and Validation of Ultraviolet Photoreactors Using Dimensional Analysis

Ultraviolet (UV) disinfection is commonly applied in the treatment of drinking water and wastewater. The performance of UV disinfection systems is governed by the UV dose distribution delivered to the fluid, which is an intrinsic characteristic of the reactor under a given operating condition. Current design and validation approaches are based on empirical methods that are expensive to apply and provide limited information about the UV photoreactor behavior. To address this issue, a dose distribution scaling method was developed based on dimensional analysis (i.e., application of the Buckingham-π theorem). Three dimensionless groups representing UV dose, reactor geometry, and UV absorption behavior were defined. Using these groups, the approach was applied for the analysis of 15 operating conditions, defined by process variables of volumetric flow rate, UV transmittance, and lamp power. The approach was demonstrated to allow scaling of the dose distribution with these critical, dimensionless variables and yielded close agreement between predictions of disinfection efficacy against MS2 and E. coli based on the scaling approach with conventional CFD-E' modeling results. The approach thus provides a low-cost, rapid method for predicting the performance of UV disinfection systems across a wide range of operating conditions and against essentially any microbial challenge agent.

Computational fluid dynamics modelling of quasi-collimated beam apparatus - a typical bench scale UV apparatus for water treatment

Quasi-collimated beam apparatus (QCBA), a typical bench scale UV apparatus, is crucial for the biodosimetry determination of UV dose in target reactors. However, the key parameters for the QCBA construction are usually estimated via rule-of-thumb calculations. Computational fluid dynamics models are applied in this study to simulate the UV fluence rate (FR) distributions in QCBAs. QCBAs with either a cylindrical tube or successive apertures irradiate quasi parallel light into selected dishes. The simulated Petri factors (PF) in the target QCBAs with a single aperture were all >0.84, and increased with the extended distance (L₁) from the UV lamp to the upper aperture. QCBAs with two successive apertures are recommended compared with those with three apertures or cylindrical tube. A trend of FR distribution from dispersed to concentrated is observed when L₁ or the interval distance between each aperture increases in a dual-aperture QCBA. QCBAs with multiple lamps were favorable to increase the UV output power, while having a nearly negligible loss of parallelism. An actual QCBA was constructed, and the maximal and average FR and PF values in a 60-mm dish were 0.159 and 0.164 W/m², and 0.967, respectively, in accordance with the simulated results.

A Novel System for Water Disinfection with UV Radiation

We present a novel system for water disinfection with ultra-violet (UV) radiation. In this system, the UV lamps do not come into contact with the water and hence remain free of fouling. The system incorporates a diffusor and a nozzle, with stationary guide vanes built into each. Their combined purpose is to reduce the hydraulic losses while imparting a strong swirl component to the flow. The swirl significantly enhances turbulent mixing processes and provides a self-cleansing mechanism that renders the system tolerant to high levels of turbidity and scaling. The hydrodynamic performance of the system was optimized using Computational Fluid Dynamics, while the manufacture of its key components was accomplished using advanced mechanical design software and three-dimensional (3D) printing. Biodosimetry testing with the bacteriophage MS2 indicated the delivery of a UV dose of 215.6 mJ/cm2. This produced a 6.9 log10 reduction of E. coli and 7.12 log10 reduction of MS2. Assessment of the system with hard water containing high Ca, Mg, and Fe concentrations, and with water with turbidity of 18 NTU indicated that the log10 removal of E. coli remained above 5.