TL;DR: PM discrete phase modeling and computational fluid dynamics are applied to model PM fate as a function of particle size and flow rate in two common types of hydrodynamic separator (HS) units and the fate of common heterodisperse PSDs is accurately predicted.
Abstract: Modeling the separation of dilute particulate matter (PM) has been a topic of interest since the introduction of unit operations for clarification of rainfall-runoff. One consistent yet controversial issue is the representation of PM and PM separation mechanisms for treatment. While Newton’s Law and surface overflow rate were utilized, many historical models represented PM as a lumped gravimetric index largely out of economy and lack of particle analysis methods. As a result such models did not provide information about particle fate in or through a unit operation. In this study, PM discrete phase modeling (DPM) and computational fluid dynamics (CFD) are applied to model PM fate as a function of particle size and flow rate in two common types of hydrodynamic separator (HS) units. The study examines the discretization requirements (as a discretization number, DN) and errors for particle size distributions (PSDs) that range from the common heterodisperse to a monodisperse PSD. PSDs are categorized based on ...
TL;DR: In this paper, a computational fluid dynamic model of a 1600 mm diameter prototype hydrodynamic separator has been developed, which was modelled without a baseflow and configured for grit removal in a manner typical of operation within a wastewater treatment works.
TL;DR: In this paper, the authors describe the practical use of wastewater characterisation, in the form of settling velocity distributions, for the design of primary sedimentation devices, such as the hydrodynamic separators used in the Swirl-Flo TM process.
TL;DR: A pollution control pit was developed with a hydrodynamic separator and a multistage filter made of coated porous concrete that treats runoff at source and protects soil, groundwater and receiving waterways.
TL;DR: In this article, 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 unsteby tracking for particle size distributions (PSDs).
Abstract: [1] 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.