Using surface flow image velocimetry to analyse flow approaching grated inlets

This paper describes the use of surface flow image velocimetry (SFIV) to analyse flow velocity fields near grated inlets. This will help to understand the flow-capture process of grated inlets and improve their design. The technique allows approximation of the surface flow velocity field where other...

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Detalles Bibliográficos
Autores: Tellez Alvarez, Jackson David|||0000-0003-1428-9872, Gómez Valentín, Manuel|||0000-0001-7042-5897, Russo, Beniamino|||0000-0001-9437-0085, Redondo Apraiz, José Manuel
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/407438
Acceso en línea:https://hdl.handle.net/2117/407438
https://dx.doi.org/10.1680/jwama.18.00103
Access Level:acceso abierto
Palabra clave:Urban runoff
Drainage & irrigation
Hydraulics & hydrodynamics
Sewers & drains
Escolament urbà
Àrees temàtiques de la UPC::Enginyeria civil::Enginyeria hidràulica, marítima i sanitària::Enginyeria sanitària
Descripción
Sumario:This paper describes the use of surface flow image velocimetry (SFIV) to analyse flow velocity fields near grated inlets. This will help to understand the flow-capture process of grated inlets and improve their design. The technique allows approximation of the surface flow velocity field where other techniques can fail. Especially in cases when the flow near the inlet is supercritical, and with small depths, the introduction of other devices to measure velocity fields can dramatically modify the flow pattern around the gauge and lead to unreliable measurements. SFIV provides a non-intrusive way of estimating flow velocities in the area covered by the images. Full-scale experiments were carried out using a high-resolution camera and commercial codes to characterise the flow patterns approaching grated inlets commonly used in Barcelona, Spain. The results from image processing algorithms were used to differentiate frontal and lateral flows reaching the inlets.