Savvas Xanthos

Entropy-Based Sensor Placement Optimization for Waterloss Detection in Water Distribution Networks

The work presented herein addresses the problem of sensor placement optimization in urban water distribution networks by use of an entropy-based approach, for the purpose of efficient and economically viable waterloss incident detection. The proposed method is applicable to longitudinal rather than spatial sensing, thus to devices such as acoustic, pressure, or flow sensors acting on pipe segments. The method utilizes the maximality, subadditivity and equivocation properties of entropy, coupled with a statistical definition of the probability of sensing within a pipe segment, to assign an entropy metric to each pipe segment and subsequently optimize the location of sensors in the network based on maximizing the total entropy in the network. The method proposed is a greedy-search heuristic.

Critical modeling parameters identified for 3D CFD modeling of rectangular final settling tanks for New York City wastewater treatment plants

New York City Environmental Protection is in the process of incorporating biological nitrogen removal (BNR) in its wastewater treatment plants (WWTPs) which entails operating the aeration tanks with higher levels of mixed liquor suspended solids (MLSS) than a conventional activated sludge process. The objective of this paper is to discuss two of the important parameters introduced in the 3D CFD model that has been developed by the City College of New York (CCNY) group: (a) the development of the discrete particle measurement technique to carry out the fractionation of the solids in the final settling tank (FST) which has critical implications in the prediction of the effluent quality; and (b) the modification of the floc aggregation (K(A)) and floc break-up (K(B)) coefficients that are found in Parkers flocculation equation (Parker et al. 1970, 1971) used in the CFD model. The dependence of these parameters on the predictions of the CFD model will be illustrated with simulation results on one of the FSTs at the 26th Ward WWTP in Brooklyn, NY.

Implementation of CFD modeling in the performance assessment and optimization of secondary clarifiers: the PVSC case study

The water industry and especially the wastewater treatment sector has come under steadily increasing pressure to optimize their existing and new facilities to meet their discharge limits and reduce overall cost. Gravity separation of solids, producing clarified overflow and thickened solids underflow has long been one of the principal separation processes used in treating secondary effluent. Final settling tanks (FSTs) are a central link in the treatment process and often times act as the limiting step to the maximum solids handling capacity when high throughput requirements need to be met. The Passaic Valley Sewerage Commission (PVSC) is interested in using a computational fluid dynamics (CFD) modeling approach to explore any further FST retrofit alternatives to sustain significantly higher plant influent flows, especially under wet weather conditions. In detail there is an interest in modifying and/or upgrading/optimizing the existing FSTs to handle flows in the range of 280-720 million gallons per day (MGD) (12.25-31.55 m(3)/s) in compliance with the plants effluent discharge limits for total suspended solids (TSS). The CFD model development for this specific plant will be discussed, 2D and 3D simulation results will be presented and initial results of a sensitivity study between two FST effluent weir structure designs will be reviewed at a flow of 550 MGD (∼24 m(3)/s) and 1,800 mg/L MLSS (mixed liquor suspended solids). The latter will provide useful information in determining whether the existing retrofit of one of the FSTs would enable compliance under wet weather conditions and warrants further consideration for implementing it in the remaining FSTs.

Disaster Resilience of Water Distribution Networks

Water distribution networks are infrastructure threatened by natural or man-made disasters. WDNs are primary lifelines that should be able to provide their full or partial services immediately after a disaster. Designing a WDN taking into consideration its resilience and robustness is a must today. Moreover, WDNs are part of a citys infrastructure system and thus are interconnected to all essential lifeline networks. Recent studies of failures highlight the increased vulnerability of lifelines due to their interconnectivity and the need to consider mutually dependent network properties in designing resilient systems.

Chapter 3 – Vulnerability Assessment of Water Distribution Networks Under Abnormal Operating Conditions and Nonseismic Loads – The Case of Intermittent Water Supply (IWS)

The chapter presents, as a reference to the increased levels of vulnerability stemming from abnormal operating conditions, the case of intermittent water supply (IWS) and of related mathematical models. The chapter starts with a basic statistical and proceeds with a more detailed analysis, by use of the survival, proportional hazard rate, and regression tree methods. The analysis covers both normal and abnormal operating WDN conditions, varying levels of data complexity, and various WDN component classes. The goal is to demonstrate how historical records can be processed with analytical and numerical models, to identify underlying data patterns, and to eventually assess the corresponding risk of failure for each network element.

Hydraulic Vulnerability Assessment of Water Distribution Networks

The chapter presents a methodology for the seismic and hydraulic assessment of the reliability of urban water distribution networks (WDN) based on general seismic assessment standards, as per the American Lifelines Alliance (ALA) guidelines, localized historical records of critical risk-of-failure metrics pertaining to the specific WDN under assessment, and hydraulic simulations using adapted EPANET models. The proposed methodology is applicable to WDN under either normal or abnormal operating conditions (such as intermittent water supply), and the assessment of reliability incorporates data of past nonseismic damage, the vulnerabilities of the network components against seismic loading, hydraulic modeling, and the topology of a WDN. The network reliability is subsequently assessed using Graph Theory, while the system reliability is calculated using Monte Carlo simulation coupled with a hydraulic analysis identifying various methodology options for hydraulic quantity evaluation and hence hydraulic network performance. The methodology proposed is demonstrated on a real-scale district metered area (DMA) in a city-wide WDN.

Chapter 8 – From Historical and Seismic Performance to City-Wide Risk Maps

Following the discussion on the vulnerability of water distribution networks stemming from normal and abnormal operating conditions, under both nonseismic and seismic loads, the chapter discusses spatio-temporal aspects in vulnerability analysis. Spatial analysis (in the form of vulnerability “heatmaps”) is used to demonstrate the effects of nonseismic historical performance of WDNs on their seismic vulnerability and to discuss the various implications of network connectivity on WDN vulnerability. Utilized in the proposed spatio-temporal analysis are the American Lifelines Alliance (ALA) guidelines for the seismic vulnerability assessment of water distribution networks and the proposed friendly amendments to them (provided in Chapter 5 ), incorporating historical performance data and survival analysis to localize the probability of failure per WDN component.

Vulnerability Assessment of Water Distribution Networks Under Normal (Continuous Water Supply, CWS) Operating Conditions and Nonseismic Loads

Abstract The chapter discusses the basic concepts of vulnerability assessment, from WDN component to network assessment, and provides a short introduction to survival analysis. Survival analysis is then utilized in the development of vulnerability curves for several WDN components (such as water mains and house connections) and various classes (such as various pipe materials, diameters, and number of previously observed breaks). The analysis focuses on WDN vulnerability under normal operating conditions, and it leads itself to vulnerability considerations for WDNs under abnormal operating conditions (discussed in Chapter 3 ).

Vulnerability Assessment of Water Distribution Networks Under Seismic Loads

A methodology is presented for the reliability assessment of urban water distribution networks (UWDN), based on component analysis, network topology and, most importantly, survival analysis, in order to include the effects of a networks past performance on its seismic and/or nonseismic reliability assessment. The chapter investigates the effects of a networks historical performance on seismic vulnerability, through the introduction of the “ Number of Observed Previous Breaks (NOPB) ” risk factor. It discusses how “ Repair Rate (RR) pipe fragilities underestimate the seismic effects on the vulnerability of a network and recommends how the damaged (“prior performance”) and undamaged network states can be included in the calculation of a pipes probability of failure.

Real-Time Monitoring

An evaluation is presented of the utilization of change-point methods for the detection of anomalies in water consumption time series, and their applicability to water loss detection in water distribution networks. Special attention is given to the relative unconstrained least-squares importance fitting (RuLSIF) change-point detection method [106] xa0; [173] , whose suitability to WDN streaming data is examined by use of a two-month-long hourly water consumption signal. The RuLSIF method successfully detects unusual fluctuations in the water consumption patterns, and classifies them as anomalies. The first water consumption anomaly type examined relates to a discontinuity in the signal (a break in the consumers water consumption patterns), whereas the second type relates to an unusual increase in the signal (water loss incidents). Even though the proposed analysis does not predict future anomalies, it is suitable for past and near-real-time anomaly detection; an attribute that is sufficient for water loss management as it allows for a timely detection of anomalies is streaming water flow data. Further, the method dynamically assigns anomaly scores to the detected changes in the signal, thus easing water loss detection and appraising the severity of each detected incident.