Abstract
Analysis of unit operations to separate particulate matter (PM) transported by urban drainage is challenged by coupled hydrologic and mass transport and is commonly based on statistical flow indices. In this study the response of a hydrodynamic separator (HS) to unsteady runoff is modeled with computational fluid dynamics (CFD). Flow is modeled by a k‐ɛ model of turbulence with Lagrangian unsteady tracking for particle size distributions (PSDs). CFD results reproduced HS‐captured PM mass within 10%. Validated unsteady CFD results are compared to steady flow and PM event mean concentrations, indicating that event‐based flow statistics do not represent unsteady HS behavior. Mean and median flows underestimate effluent PM mass, while peak flow overestimates to a lesser magnitude depending on hydrologic and PM coupling. Unsteady flow and PSD coupling in the CFD model yield accurate predictive capability for PM separation by a physically validated unit operation (HS) compared to common event‐based flow statistics. While steady flow indices do not reproduce PM behavior for unit operations loaded by unsteady urban drainage, such indices are pragmatic and heuristic for initial phase pilot‐scale testing.
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