A three-dimensional (3-D) computational fluid dynamic model that predicts the performance of a full-scale medium-pressure lamp ultraviolet (UV) reactor for disinfection of drinking water is described. The model integrates velocity field, fluence rate distribution, and particle trajectory calculations with a microorganism inactivation kinetic model to arrive at predictions of reduction equivalent dose and microorganism inactivation for MS2 coliphage. A rational approach to determining an appropriate number of fluid particles that would generate the required computational precision is presented. Predictions of inactivation and equivalent dose were found to be sensitive to computational mesh geometry (hexahedral versus tetrahedral) but were less sensitive to the value of the Lagrangian empirical constant used in the random walk model and to choice of turbulence model (κ − ε versus Reynolds stress). Non-steady-state (dynamic) simulations produced results that were similar to those of steady-state simulations. Utility of the model for evaluating different lamp operating modes and alternative physical arrangements of the baffles and lamps was demonstrated.Résumé : Cet article décrit un modèle tridimensionnel de dynamique des fluides numérique qui prédit le rendement d'un réacteur UV, pleine échelle, à lampe à moyenne pression pour désinfecter l'eau potable. Le modèle intègre le champ de vitesse, la distribution du taux de fluence et les calculs de la trajectoire des particules dans un modèle de cinétique d'inactivation des microorganismes pour arriver à prédire la dose équivalente de réduction et d'inactivation des microorganismes par rapport au coliphage MS2. Une approche rationnelle pour déterminer le nombre approprié de particules de fluide qui généreraient la précision computationnelle requise est présentée. Les prévisions d'inactivation et de la dose équivalente se sont avérées sensibles à la géométrie computationnelle (hexaèdre p/r tétraèdre) mais elles étaient moins sensibles à la valeur de la constante empirique Lagrangienne utilisée dans le modèle de parcours aléatoire et au choix du modèle de turbulence (κ et ε p/r à la tension de Reynolds). Les simulations en régime non permanent (dynamique) ont produit des résultats similaires à ceux des simulations en régime permanent. L'utilité du modèle pour l'évaluation des différents modes de fonctionnement des lampes et des autres dispositions physiques des déflecteurs et des lampes a été démontrée.

A two-dimensional model was developed in this study. The model predicts the performance of a full-scale aerated grit chamber for grit removal from wastewater. The model numerically integrates Poisson’s equation, which describes the motion of the liquid induced by the rising air bubbles. The model makes use of finite element algorithms available in Mathcad to solve Poisson’s equation. The model was developed for predicting the velocity field in the chamber. The model was used to perform a sensitivity analysis of the design variables that affect the performance of an existing grit chamber at the Moose Jaw Wastewater Treatment Plant. The results of the sensitivity analysis indicate that predictions of velocity field are highly sensitive to energy transfer efficiency, air flowrate, and particle settling velocity but less sensitive to variations of wastewater flowrate, diffuser depth, and grid spacing.

No abstract

A two-dimensional model was developed in this study. The model predicts the performance of a full-scale aerated grit chamber for grit removal from wastewater. The model numerically integrates Poisson's equation, which describes the motion of the liquid induced by the rising air bubbles. The model makes use of finite element algorithms available in Mathcad to solve Poisson's equation. The model was developed for predicting the velocity field in the chamber. The model was used to perform a sensitivity analysis of the design variables that affect the performance of an existing grit chamber at the Moose Jaw Wastewater Treatment Plant. The results of the sensitivity analysis indicate that predictions of velocity field are highly sensitive to energy transfer efficiency, air flowrate, and particle settling velocity but less sensitive to variations of wastewater flowrate, diffuser depth, and grid spacing.