Computational Fluid Dynamics Modelling and Analysis Approach for Estimating Internal Short-Circuiting in Clearwells

Abstract

Disinfection is an effective microorganism inactivation method that has contributed historically to decreasing waterborne diseases. It is necessary to improve hydraulic efficiency for ensuring disinfection ability without creating disinfection by-products. However, many hydraulic efficiency indices, which are a type of black-box analyses based on residence time distribution curves, have been used to assess short-circuiting and mixing. We propose a novel index (internal short-circuiting index, ISI) and analysis approach (internal short-circuiting estimation method, ISEM) based on computational fluid dynamics (CFD) modelling for understanding the local hydrodynamics. Then, we implement ISEM to quantify the effect of the clearwell configuration with the different length-to-width and shape ratios on the hydraulic efficiency. As the hydraulic efficiency surrogated by T10/T converges to the maximum value, the ISI values at inlet and outlet reduce rapidly, and the recirculation and dead zones shrink in the channel zones. Thus, the ISI curve changes from a V shape to U shape. The ISEM demonstrates that it is applicable under various conditions and it enables engineers to design clearwells for optimizing the disinfection ability. Furthermore, the CFD model in this study can be combined with machine learning techniques in future studies to extract knowledge for reducing the computational cost.

Keywords

• clearwell
• internal short-circuiting estimation method (ISEM)
• computational fluid dynamics
• length-to-width ratio
• shape ratio
• machine learning