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Dynamics of Geysers in Stormsewer Systems and Novel Retrofitting Methods

Dynamics of Geysers in Stormsewer Systems and Novel Retrofitting Methods
雨水管道系统中间歇泉的动力学和新颖的改造方法
批准号:
1928850
负责人:
Arturo Leon
金额:
$32.97万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-01-01 至 2024-12-31

项目摘要

项目成果

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中文摘要
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英文摘要
Combined sewer overflows (CSOs) are the release of raw sewage and stormwater into receiving waterways when the system becomes filled. CSOs constitute a major source of water pollution for 860 municipalities across the United States. Combined sewer systems consist of a network of deep tunnels to move both stormwater and sewage. These systems can be filled rapidly with stormwater during rainfall events, resulting in the entrapment of large amounts of air. When the trapped air is released through vertical drop shafts, geyser eruptions are often produced. These geysers can exceed 30 meters in height and can cause massive flooding events that lead to the pollution of streams, rivers, and lakes. Many combined sewer systems are operated below design capacity to prevent geyser formation during rain events, but this increases the likelihood of CSOs. This research project will develop a mechanistic understanding of geyser formation that can be used to design retrofitting methods for drop shafts that allow the smooth release of air pockets without producing geysers. When geysers are no longer a concern, the full capacity of storm sewer systems can be utilized during rain events and hence CSO discharges will be reduced significantly. An outreach program will educate and train researchers, middle-school and college students from underrepresented groups, sewer system operators, and other stakeholders on the control of geysers and the impact of CSOs on water quality. The goal of the research project is to develop a fundamental understanding of the two-phase flow physics that triggers geysering in storm sewer systems. The research will utilize integrated high-speed optical imaging, digital particle image velocimetry, and 3-D computational fluid dynamics to model and confirm results from the laboratory-scale reproduction of geysers. Studies will be performed to understand the relationship between geyser eruption, system geometry, and initial flow conditions. A reduced order geyser model will be developed from these relationships and implemented in an open-source software format for modeling flow dynamics in storm sewer systems. Retrofitting strategies to permit the smooth release of air pockets will be preliminarily tested and validated using a 3-D model, and the most promising methods will be tested experimentally and confirmed numerically. The outcomes of this research will be used by scientists, hydraulic engineers, and other practitioners to inform future design and retrofitting strategies to prevent geyser formation in storm sewer systems. Students, regulators, and other stakeholders will learn from the software packages and educational outreach how to prevent geyser formation and reduce CSOs and their associated impacts on the environment.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(3)
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科研奖励(0)
会议论文
DOI: 10.1061/9780784484258.110
发表时间: 2022-06
期刊: World Environmental and Water Resources Congress 2022
影响因子: --
作者: [Sumit R. Zanje;Pratik Mahyawansi;Arturo S. Leon;Cheng-Xian Lin]
通讯作者: Sumit R. Zanje;Pratik Mahyawansi;Arturo S. Leon;Cheng-Xian Lin
An Affordable PIV Technique for Water Using Potato Starch with Diode Laser and Smartphones
一种经济实惠的 PIV 技术,使用马铃薯淀粉、二极管激光器和智能手机来供水
DOI: 10.1061/9780784484258.036
发表时间: 2022
期刊: . World Environmental and Water Resources Congress 2022: Adaptive Planning and Design in an Age of Risk and Uncertainty
影响因子: --
作者: [Mahyawansi, Pratik, Zange, Sumit R., Lin, Cheng-Xian, Leon, Arturo S.]
通讯作者: Leon, Arturo S.
DOI: 10.1615/tfec2022.fnd.040491
发表时间: 2022
期刊: 7th Thermal and Fluids Engineering Conference (TFEC
影响因子: --
作者: [Mahyawansi, Pratik, Lin, Cheng-Xian, Leon, Arturo S.]
通讯作者: Leon, Arturo S.
A Physics-Based Artificial Intelligence General Framework for Optimal Control of Sewer Systems to Minimize Sewer Overflows
  • 批准号:
    2203292
  • 项目类别:
    Standard Grant
  • 资助金额:
    $40.0万
  • 财政年份:
    2022
  • 负责人:
    Arturo Leon
  • 依托单位:
Dynamic Management of Water Storage in Watersheds for Reducing the Magnitude of Floods
  • 批准号:
    1805417
  • 项目类别:
    Standard Grant
  • 资助金额:
    $30.78万
  • 财政年份:
    2018
  • 负责人:
    Arturo Leon
  • 依托单位:
Dynamic Management of Water Storage in Watersheds for Reducing the Magnitude of Floods
  • 批准号:
    1843038
  • 项目类别:
    Standard Grant
  • 资助金额:
    $30.78万
  • 财政年份:
    2018
  • 负责人:
    Arturo Leon
  • 依托单位:
海外基金