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.

Development and modeling of a novel type of photoreactors with exterior ultraviolet (UV) reflector for water treatment applications.

Ultraviolet (UV) water disinfection method has emerged as an alternative to chemical methods of disinfection. In typical UV photoreactors for water treatment, water flows in the space between the lamp's sleeve and outer shell. The contact of water and sleeve causes fouling, which reduces the effectiveness of UV. To clean the photoreactor, the quartz sleeve must be replaced; this may lead to quartz or lamp breakage and mercury leakage into water during cleaning. In this study, a novel type of multi-lamp UV photoreactors is proposed, in which the UV lamps are placed out of the water channel and their UV irradiation is redirected into the channel using an outer cylindrical reflector. This allows for the installment of a self-cleaning mechanism for the water channel. A well-validated three-dimensional CFD model is utilized to model the performance of this photoreactor for microbial inactivation. The impacts of several geometrical and optical parameters are investigated on the inactivation of microorganisms. The results revealed that the difference in log reduction values (LRV) between fully specular and fully diffuse reflector ranges from 10 to 47% as the lamp-to-channel distance increases. For the volumetric flow rate of 25 GPM, the LRV of a photoreactor with fully diffuse reflector can be 46% higher than a fully specular one. In addition, the performance of the proposed photoreactor is compared against a classic L-shaped annular photoreactor. The results show that the new design can provide equal or better microbial performance compared to the classic photoreactor, but it removes many of their common issues such as quartz fouling, lamp overheating at low flow rates, and sleeve breakage during lamp replacement.

Stochastic simulation of the FDA centrifugal blood pump benchmark.

In the present study, the effect of physical and operational uncertainties on the hydrodynamic and hemocompatibility characteristics of a centrifugal blood pump designed by the U.S. food and drug administration is investigated. Physical uncertainties include the randomness in the blood density and viscosity, while the operational uncertainties are composed of the pump rotational speed, mass flow rate, and turbulence intensity. The non-intrusive polynomial chaos expansion has been employed to conduct the uncertainty quantification analysis. Additionally, to assess each stochastic parameter's influence on the quantities of interest, the sensitivity analysis is utilized through the Sobol' indices. For numerical simulation of the pump's blood flow, the SST [Formula: see text] turbulence model and a power-law model of hemolysis were employed. The pump's velocity field is profoundly affected by the rotational speed in the bladed regions and the mass flow rate in other zones. Furthermore, the hemolysis index is dominantly sensitive to blood viscosity. According to the results, pump hydraulic characteristics (i.e., head and efficiency) show a more robust behavior than the hemocompatibility characteristics (i.e., hemolysis index) regarding the operational and physical uncertainties. Finally, it was found that the probability distribution function of the hemolysis index covers the experimental measurements.

Nondeterministic computational fluid dynamics modeling of Escherichia coli inactivation by peracetic acid in municipal wastewater contact tanks.

Wastewater disinfection processes are typically designed according to heuristics derived from batch experiments in which the interaction among wastewater quality, reactor hydraulics, and inactivation kinetics is often neglected. In this paper, a computational fluid dynamics (CFD) study was conducted in a nondeterministic (ND) modeling framework to predict the Escherichia coli inactivation by peracetic acid (PAA) in municipal contact tanks fed by secondary settled wastewater effluent. The extent and variability associated with the observed inactivation kinetics were both satisfactorily predicted by the stochastic inactivation model at a 95% confidence level. Moreover, it was found that (a) the process variability induced by reactor hydraulics is negligible when compared to the one caused by inactivation kinetics, (b) the PAA dose required for meeting regulations is dictated equally by the fixed limit of the microbial concentration as well as its probability of occurrence, and (c) neglecting the probability of occurrence during process sizing could lead to an underestimation of the PAA dose required by as much as 100%. Finally, the ND-CFD model was used to generate sizing information in the form of probabilistic disinfection curves relating E. coli inactivation and probability of occurrence with the average PAA dose and PAA residual concentration at the outlet of the contact tank.

The impact of spinal cord nerve roots and denticulate ligaments on cerebrospinal fluid dynamics in the cervical spine.

Cerebrospinal fluid (CSF) dynamics in the spinal subarachnoid space (SSS) have been thought to play an important pathophysiological role in syringomyelia, Chiari I malformation (CM), and a role in intrathecal drug delivery. Yet, the impact that fine anatomical structures, including nerve roots and denticulate ligaments (NRDL), have on SSS CSF dynamics is not clear. In the present study we assessed the impact of NRDL on CSF dynamics in the cervical SSS. The 3D geometry of the cervical SSS was reconstructed based on manual segmentation of MRI images of a healthy volunteer and a patient with CM. Idealized NRDL were designed and added to each of the geometries based on in vivo measurments in the literature and confirmation by a neuroanatomist. CFD simulations were performed for the healthy and patient case with and without NRDL included. Our results showed that the NRDL had an important impact on CSF dynamics in terms of velocity field and flow patterns. However, pressure distribution was not altered greatly although the NRDL cases required a larger pressure gradient to maintain the same flow. Also, the NRDL did not alter CSF dynamics to a great degree in the SSS from the foramen magnum to the C1 level for the healthy subject and CM patient with mild tonsillar herniation (∼ 6 mm). Overall, the NRDL increased fluid mixing phenomena and resulted in a more complex flow field. Comparison of the streamlines of CSF flow revealed that the presence of NRDL lead to the formation of vortical structures and remarkably increased the local mixing of the CSF throughout the SSS.

Modeling hydroxyl radical distribution and trialkyl phosphates oxidation in UV-H2O2 photoreactors using computational fluid dynamics.

Advanced Oxidation Processes (AOPs) promoted by ultraviolet light are innovative and potentially cost-effective solutions for treating persistent pollutants recalcitrant to conventional water and wastewater treatment. While several studies have been performed during the past decade to improve the fundamental understanding of the UV-H(2)O(2) AOP and its kinetic modeling, Computational Fluid Dynamics (CFD) has only recently emerged as a powerful tool that allows a deeper understanding of complex photochemical processes in environmental and reactor engineering applications. In this paper, a comprehensive kinetic model of UV-H(2)O(2) AOP was coupled with the Reynolds averaged Navier-Stokes (RANS) equations using CFD to predict the oxidation of tributyl phosphate (TBP) and tri(2-chloroethtyl) phosphate (TCEP) in two different photoreactors: a parallel- and a cross-flow UV device employing a UV lamp emitting primarily 253.7 nm radiation. CFD simulations, obtained for both turbulent and laminar flow regimes and compared with experimental data over a wide range of UV doses, enabled the spatial visualization of hydrogen peroxide and hydroxyl radical distributions in the photoreactor. The annular photoreactor displayed consistently better oxidation performance than the cross-flow system due to the absence of recirculation zones, as confirmed by the hydroxyl radical dose distributions. Notably, such discrepancy was found to be strongly dependent on and directly correlated with the hydroxyl radical rate constant becoming relevant for conditions approaching diffusion-controlled reaction regimes (k(C,OH) > 10(9) M(-1) s(-1)).