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Published, Version of Record (VoR)CC BY V4.0, Open
Journal article
Numerical 3D Model Development and Validation of Curb-Cut Inlet for Efficiency Prediction
Water (Basel), v 12(6), 1791
01 Jun 2020
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Green infrastructure (GI) is a decentralized stormwater management strategy that can simultaneously enhance the resilience of the urban landscape to weather-related stressors. The effectiveness of individual GI facilities is determined by the physical characteristics of the tributary area and inlet, including factors such as slope and geometry, apron configuration, roughness, and clogging, all of which have been inadequately studied. In this paper, we construct, calibrate, and validate a computational fluid dynamics (CFD) model using field survey data collected at a Bronx, NY GI facility. The validated CFD model is used to evaluate how inlet clogging and flow rate affect GI inlet performance. Seven flow rates ranging from 0.00044 to 0.00755 CMS were simulated. As the flow rate increased, the inlet efficiency dropped from 100% to 60% at one location (the SW inlet) and from 100% to 25% at another location (the NW inlet). At a fixed flow rate, the inlet efficiency dropped from 100% efficient (with no clogging) to 0% (with the inlet fully clogged). The stage-discharge relationship for the inlet based on the simulated field conditions deviated from that assumed based on normative flow and was revised. We suggest that GI facilities installed on mild- slope, or rough streets be fitted with non-clogging inlets to maintain free outfall conditions.
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Details
- Title
- Numerical 3D Model Development and Validation of Curb-Cut Inlet for Efficiency Prediction
- Creators
- Leena Jaydeep Shevade - Drexel UniversityL. James Lo - Drexel UniversityFranco A. Montalto - Drexel University
- Publication Details
- Water (Basel), v 12(6), 1791
- Publisher
- MDPI AG
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Web of Science ID
- WOS:000553982200001
- Scopus ID
- 2-s2.0-85087547105
- Other Identifier
- 991019168506204721
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- Web of Science research areas
- Environmental Sciences
- Water Resources