CFD with Evolutionary Optimization for Stormwater Basin Retrofits

Abstract

Stormwater basins, which are subject to highly unsteady flows and loads, function as clarifiers for particulate matter (PM) and PM-bound constituents. Quasi-steady flow hydrodynamics in water and wastewater treatment plant units, from grit to contact chambers, are known to impact treatment. In contrast, there is sparse basin design guidance for unsteady hydrodynamics and clarification interactions. Basins can become impaired with needed retrofits. Lumped models, such as surface overflow rate (SOR), are less suitable for complex geometries, hydrodynamics, and loadings. A computational fluid dynamics (CFD) and evolutionary optimization framework as higher-fidelity tools is proposed for relatively shallow basins with permeable baffle retrofits. This study extends previous research and optimizes baffle configuration by further considering routing effects and unsteady loading on clarification. For an influent heterodisperse particle size distribution (PSD), baffles improve PM clarification by 58.8% based on baffle number. Strategically altering the baffle position, length, and angle yields an optimal configuration with improved clarification of 32% in comparison to conventional baffle configurations. Baffle optimization leads to construction costs that are one-third to one-fifth those of conventional baffle configurations.