Optimization of Water Quality Sensor Placement in Sewer Networks
Optimization of Water Quality Sensor Placement in Sewer Networks
复制标题
污水管网中水质传感器放置的优化
DOI：
10.1061/9780784484852.102
复制
发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Abokifa, Ahmed A.
中科院分区：
文献类型：
--
作者：
Salem, Aly K.;Abokifa, Ahmed A.
近年来，废水监测因其所揭示的宝贵的环境和流行病学信息而受到极大关注。然而，在以前的文献中，已经进行了有限的尝试，以确定样品采集的最佳位置。在这项研究中，我们引入了一个模型来解决传感器放置（SP）的问题，认为源识别（SI）作为传感器放置的主要标准。本研究的目的是最大化传感器设计识别注入源特性的能力（即， 注射位置和浓度）。为此，我们开发了一个基于Python的模型，该模型将SI模型与贪婪算法相结合，以确定放置水质传感器的最佳位置。开发的SP模型进行了演示的基准，中型污水管网。研究结果表明，传感器设计的整体可识别性和检测可靠性之间存在明显的权衡。一般来说，将传感器放置在网络的下游端会导致更高的整体可识别性，而放置在网络的上游部分的传感器会实现更好的检测可靠性。
Wastewater surveillance has received significant attention in recent years due to the valuable environmental and epidemiological information it reveals. Yet, limited attempts have been made in the previous literature to determine the best locations for sample collection. In this study, we are introducing a model to solve the sensor placement (SP) problem that considers source identification (SI) as the main criterion for sensor placement. The objective of this study is to maximize the ability of the sensor design to identify the characteristics of the injection source (i.e., the injection location and concentration) of any given species of interest. To that end, we developed a python-based model that couples an SI model with a greedy algorithm to determine the best locations to place water quality sensors. The developed SP model was demonstrated on a benchmark, mid-sized sewer network. The study results revealed that a clear tradeoff exists between the overall identifiability and the detection reliability of the sensor design. In general, placing the sensors in the downstream end of the network resulted in higher overall identifiability, while better detection reliability was achieved by the sensors placed in the upstream section of the network.
用于下水道系统污染源识别的 SWMM5 工具包开发
DOI：
--
发表时间：
2014
期刊：
影响因子：
--
作者：
B. K. Banik;C. D. Cristo;A. Leopardi
通讯作者：
A. Leopardi
基于遗传算法的明渠设计参数优化选择模型
影响因子：
4.3
作者：
Aly K. Salem;Y. E. Imam;Ashraf H. M. Ghanem;A. Bazaraa
通讯作者：
A. Bazaraa
DOI：
--
发表时间：
2015
期刊：
影响因子：
--
作者：
B. K. Banik;C. D. Cristo;A. Leopardi
通讯作者：
A. Leopardi