Lina Perelman

An adaptive heuristic cross-entropy algorithm for optimal design of water distribution systems

The optimal design problem of a water distribution system is to find the water distribution system component characteristics (e.g. pipe diameters, pump heads and maximum power, reservoir storage volumes, etc.) which minimize the systems capital and operational costs such that the system hydraulic laws are maintained (i.e. Kirchhoffs first and second laws), and constraints on quantities and pressures at the consumer nodes are fulfilled. In this study, an adaptive stochastic algorithm for water distribution systems optimal design based on the heuristic cross-entropy method for combinatorial optimization is presented. The algorithm is demonstrated using two well-known benchmark examples from the water distribution systems research literature for single loading gravitational systems, and an example of multiple loadings, pumping, and storage. The results show the cross-entropy dominance over previously published methods.

Efficient Hydraulic State Estimation Technique Using Reduced Models of Urban Water Networks

This paper describes and demonstrates an efficient method for online hydraulic state estimation in urban water networks. The proposed method employs an online predictor-corrector (PC) procedure for forecasting future water demands. A statistical data-driven algo- rithm (M5 Model-Trees algorithm) is applied to estimate future water demands, and an evolutionary optimization technique (genetic algo- rithms) is used to correct these predictions with online monitoring data. The calibration problem is solved using a modified least-squares (LS) fit method (Huber function) in which the objective function is the minimization of the residuals between predicted and measured pressure at several system locations, with the decision variables being the hourly variations in water demands. To meet the computational efficiency requirements of real-time hydraulic state estimation for prototype urban networks that typically comprise tens of thousands of links and nodes, a reduced model is introduced using a water system-aggregation technique. The reduced model achieves a high-fidelity representation for the hydraulic performance of the complete network, but greatly simplifies the computation of the PC loop and facilitates the implemen- tation of the online model. The proposed methodology is demonstrated on a prototypical municipal water-distribution system. DOI: 10.1061/ (ASCE)WR.1943-5452.0000113.

Water-Distribution Systems Simplifications through Clustering

AbstractFor large water-distribution systems fully detailed models result in a substantial amount of data, making it difficult to manage, monitor, and understand how the main structure of the system works. A possible way to cope with this difficulty is to gain insight to the system behavior by simplifying its operation through topological/connectivity analysis. The objective of this study is to develop and demonstrate a generic topological-based scheme to aid in the analysis of water-distribution systems. The methodology relies on clustering, which divides the distribution system into strongly and weakly connected sub-graphs using the depth first search (DFS) and breadth first search (BFS) graph algorithms. The partitioning results in a connectivity matrix that represents the interconnections between clusters, which can support, for example, a response modeling plan in case of a contamination intrusion incident. A detailed illustrative example and a real complex water-distribution system are explored for ...

Operation of remote mobile sensors for security of drinking water distribution systems

The deployment of fixed online water quality sensors in water distribution systems has been recognized as one of the key components of contamination warning systems for securing public health. This study proposes to explore how the inclusion of mobile sensors for inline monitoring of various water quality parameters (e.g., residual chlorine, pH) can enhance water distribution system security. Mobile sensors equipped with sampling, sensing, data acquisition, wireless transmission and power generation systems are being designed, fabricated, and tested, and prototypes are expected to be released in the very near future. This study initiates the development of a theoretical framework for modeling mobile sensor movement in water distribution systems and integrating the sensory data collected from stationary and non-stationary sensor nodes to increase system security. The methodology is applied and demonstrated on two benchmark networks. Performance of different sensor network designs are compared for fixed and combined fixed and mobile sensor networks. Results indicate that complementing online sensor networks with inline monitoring can increase detection likelihood and decrease mean time to detection.

Sensor placement for fault location identification in water networks

This paper focuses on the optimal sensor placement problem for the identification of pipe failure locations in large-scale urban water systems. The problem involves selecting the minimum number of sensors such that every pipe failure can be uniquely localized. This problem can be viewed as a minimum test cover (MTC) problem, which is NP-hard. We consider two approaches to obtain approximate solutions to this problem. In the first approach, we transform the MTC problem to a minimum set cover (MSC) problem and use the greedy algorithm that exploits the submodularity property of the MSC problem to compute the solution to the MTC problem. In the second approach, we develop a new augmented greedy algorithm for solving the MTC problem. This approach does not require the transformation of the MTC to MSC. Our augmented greedy algorithm provides in a significant computational improvement while guaranteeing the same approximation ratio as the first approach. We propose several metrics to evaluate the performance of the sensor placement designs. Finally, we present detailed computational experiments for a number of real water distribution networks.

Extreme Impact Contamination Events Sampling for Real-Sized Water Distribution Systems

AbstractContamination warning systems are being designed to protect water distribution systems against deliberate contamination intrusions. To design a contamination warning system, contamination intrusion events need to be selected. Because contamination intrusions are random, even for a medium-size network the theoretical number of possible injection events is huge, and thus the number of contamination events which can be considered in the design process is limited. To effectively cope with the threat of contamination events there is a need to identify those critical instances. A straightforward approach of enumerating all possible contamination intrusions from which critical events can be selected is limited to small systems. As critical events are rare the probability of revealing them using common Monte Carlo randomized simulations is very small or requires an extensive impractical computational amount of trials. In this study a methodology utilizing importance sampling and cross entropy based on a r...

A network interdiction model for analyzing the vulnerability of water distribution systems

This article presents a network interdiction model to assess the vulnerabilities of a class of physical flow networks. A flow network is modeled by a potential function defined over the nodes and a flow function defined over arcs (links). In particular, the difference in potential function between two nodes is characterized by a nonlinear flux function of the flow on link between the two nodes. To assess the vulnerability of the network to adversarial attack, the problem is formulated as an attacker-defender network interdiction model. The attackers objective is to interdict the most valuable links of the network given his resource constraints. The defenders objective is to minimize power loss and the unmet demand in the network. A bi-level approach is explored to identify most critical links for network interdiction. The applicability of the proposed approach is demonstrated on a reference water distribution network, and its utility toward developing mitigation plans is discussed.

Flexible Reconfiguration of Existing Urban Water Infrastructure Systems.

This paper presents a practical methodology for the flexible reconfiguration of existing water distribution infrastructure, which is adaptive to the water utility constraints and facilitates in operational management for pressure and water loss control. The network topology is reconfigured into a star-like topology, where the center node is a connected subset of transmission mains, that provides connection to water sources, and the nodes are the subsystems that are connected to the sources through the center node. In the proposed approach, the system is first decomposed into the main and subsystems based on graph theory methods and then the network reconfiguration problem is approximated as a single-objective linear programming problem, which is efficiently solved using a standard solver. The performance and resiliency of the original and reconfigured systems are evaluated through direct and surrogate measures. The methodology is demonstrated using two large-scale water distribution systems, showing the flexibility of the proposed approach. The results highlight the benefits and disadvantages of network decentralization.

Application of Graph Theory to Sensor Placement in Water Distribution Systems

Water distribution systems are one of the most vulnerable civil infrastructures having crucial consequences on public health and the environment. Degradation of water quality in the distribution system further away from the treatment plant may occur as a result of intentional of unintentional events, such as microbial growth within the pipes and injection of hazardous contaminants at system’s cross-connections. It has been agreed that a key component in contamination warning systems is real-time monitoring of water quality using online sensors, which can provide an earlier indication of a potential contamination incidences. Majority of work related to placement of such sensors rely on available and well-calibrated hydraulic and water quality models (e.g., EPANET) integrated with optimization techniques (e.g., MIP, GA). In reality, these well-calibrated simulation models are rarely available from water utilities and typically include only partial information such as network topology and representative demand loadings. This work adopts algorithms from graph theory to suggest the location of sensors in a water distribution system given accessible information. The proposed approach can provide a more realistic decision support to water utilities in real application.

BAYESIAN NETWORKS FOR ESTIMATING CONTAMINANT SOURCE AND PROPAGATION IN WATER DISTRIBUTION SYSTEM USING CLUSTER STRUCTURE

Bayesian belief networks are a probabilistic analysis tool for representing and analyzing problems involving uncertainty. The problem of monitoring the propagation of a contaminant in a water distribution system can be naturally represented using Bayesian networks (BN). The presented methodology proposes estimating the likelihoods of the injection location of a contaminant and its propagation in the system using BN statistics. A clustering method, previously developed by the authors, is first applied to formulate a simplified representation of the distribution system resulting in an aggregated system. The aggregated network is represented as a directed acyclic graph and facilitates in the construction of a legal BN. The data collected from monitoring stations located at any of the nodes of the system is exploited to inquire about the possible sources of contamination and the consequent polluted nodes. For small networks, the probabilities can be estimated using exact inference algorithms, for large networks – using approximated inference algorithms such as likelihood weighting. The proposed methodology is developed and tested on two water supply systems. The results demonstrate a promising potential of the proposed method.