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Machine Learning–Based Source Identification in Sewer Networks
Publisher: ASCE
Abstract: Motivated by the valuable epidemiological information it reveals, wastewater surveillance has received significant attention in recent years. Furthermore, monitoring the water quality in sewer systems has been shown to ...
Sensor Placement Optimization in Sewer Networks: Machine Learning–Based Source Identification Approach
Publisher: American Society of Civil Engineers
Abstract: Wastewater surveillance has recently emerged as a valuable tool for environmental and public health monitoring. By analyzing the constituents and biomarkers present in wastewater, stakeholders can gather critical information ...
Framework for Evaluating the Impact of Water Chemistry Changes in Full-Scale Drinking Water Distribution Networks on Lead Concentrations at the Tap
Publisher: ASCE
Abstract: Release of lead (Pb) in drinking water from lead service lines has been extensively studied in single pipes, and the importance of water chemistry has been reported. However, the impact of variations in water chemistry ...
Real-Time Identification of Cyber-Physical Attacks on Water Distribution Systems via Machine Learning–Based Anomaly Detection Techniques
Publisher: American Society of Civil Engineers
Abstract: Smart water infrastructures are prone to cyber-physical attacks that can disrupt their operations or damage their assets. An algorithm was developed to identify suspicious behaviors in the different cyber-physical components ...
Comprehensive Framework for Controlling Nonlinear Multispecies Water Quality Dynamics
Publisher: ASCE
Abstract: Tracing disinfectant (e.g., chlorine) and contaminants evolution in water networks requires the solution of one-dimensional (1D) advection-reaction (AR) partial differential equations (PDEs). With the absence of ...
Revisiting the Water Quality Sensor Placement Problem: Optimizing Network Observability and State Estimation Metrics
Publisher: ASCE
Abstract: Real-time water quality (WQ) sensors in water distribution networks (WDN) have the potential to enable network-wide observability of water quality indicators, contamination event detection, and closed-loop feedback control ...