Modelling techniques for the design and assessment of contact reactors for chemical disinfectants: from IDDF to CFD

Disinfection process plays a crucial role in water and wastewater treatment, being a barrier against pathogen diffusion, and an important tool to support design and optimization of this unit is process modelling, based on a conventional approach, as Integrated Disinfection Design Framework (IDDF), or an emerging advanced approach, as Computational Fluid Dynamics (CFD). In the last two decades CFD, thanks to the advancements of computational tools, proved its potential as a powerful and cost-effective tool. In the present work, the two modelling techniques, IDDF and CFD, were applied to the modelling of contact reactors at pilot scale and their performances in process description were compared. In detail, two configurations were assessed, namely an open channel and a pipe reactor, for which experimental data on tracer tests, disinfectant decay and microbial inactivation were available from previous research works. The first part of the work consisted in the proper application of the two modelling techniques, using experimental data for calibration purposes. In this phase, the fundamental parameters for model setup were assessed and the efficiency of most used models for disinfectant decay and microbial inactivation were evaluated. Then, in the second part, the two modelling techniques were compared in the view of supporting the design or the assessment of contact reactors. Based on hydrodynamics analysis, the closer the reactor behavior gets to ideality, due to its simple geometry (as a pipe reactor), the easier and more reliable is the prediction of process performance using simplified approaches, as IDDF or the assumption of ideal reactor (no hydrodynamic effects). These approaches proved to be effective tools to estimate both PAA decay and disinfection performances, independently from reactor geometry, but they consider the reactor as a black-box neglecting any information about local effects, unlike CFD, being their identification indispensable to determine and quantify possible sources of non-ideality.