Note on sediment removal efficiency in oil-grit separators

Oil-grit separators (OGSs) are one type of best management practice, designed to remove oil and grit from stormwater runoff (e.g., from parking lots and paved roads). This note examines scaling parameters for OGS removal efficiency. Three dimensionless parameters are chosen as scaling parameters: Ha...

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Veröffentlicht in:Water science and technology : a journal of the International Association on Water Pollution Research. - 1986. - 2017(2018), 3 vom: 25. Juli, Seite 729-735
1. Verfasser: Tang, Yangbo (VerfasserIn)
Weitere Verfasser: Zhu, David Z, van Duin, Bert
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2018
Zugriff auf das übergeordnete Werk:Water science and technology : a journal of the International Association on Water Pollution Research
Schlagworte:Journal Article Petroleum Water Pollutants
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520 |a Oil-grit separators (OGSs) are one type of best management practice, designed to remove oil and grit from stormwater runoff (e.g., from parking lots and paved roads). This note examines scaling parameters for OGS removal efficiency. Three dimensionless parameters are chosen as scaling parameters: Hazen number (Ha), Reynolds number (Re) and Froude number (Fr). The Hazen number is a ratio of hydraulic residence time to particle settling time. The Reynolds number measures the surrounding turbulence effects on sediment removal efficiency. The Froude number represents the ratio of inertial and gravitational forces, which indicates the influence of gravity on fluid motion. The collected data from the literature on sediment removal in OGSs can be represented by a single curve when the Hazen, Reynolds, and Froude numbers are combined into a new scaling parameter (HRF = Ha(Re/Fr)). A general form is proposed to correlate the sediment removal efficiency with this new parameter. This generalized prediction method can be used as a preliminary performance indicator for OGS units. The obtained curve can also be used to adjust raw laboratory and field measurement data to improve the evaluation of the performance of various OGSs 
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700 1 |a van Duin, Bert  |e verfasserin  |4 aut 
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