Publications

Abstract not provided.

Real-time water quality sensors are becoming commonplace in water distribution systems. However, field deployable, contaminant-specific sensors are still in the development stage. As development proceeds, the necessary operating parameters of these sensors must be determined to protect consumers from accidental and malevolent contamination events. This objective can be quantified in several different ways including minimization of: the time necessary to detect a contamination event, the population exposed to contaminated water, the extent of the contamination within the network, and others. We examine the ability of a sensor set to meet these objectives as a function of both the detection limit of the sensors and the number of sensors in the network. A moderately sized distribution network is used as an example and different sized sets of randomly placed sensors are considered. For each combination of a certain number of sensors and a detection limit, the mean values of the different objectives across multiple random sensor placements are calculated. The tradeoff between the necessary detection limit in a sensor and the number of sensors is evaluated. Results show that for the example problem examined here, a sensor detection limit of 0.01 of the average source concentration is adequate for maximum protection. Detection of events is dependent on the detection limit of the sensors, but for those events that are detected, the values of the performance measures are not a function of the sensor detection limit. The results of replacing a single sensor in a network with a sensor having a much lower detection limit show that while this replacement can improve results, the majority of the additional events detected had performance measures of relatively low consequence. © 2006 ASCE.

Abstract not provided.

Real-time water quality and chemical-specific sensors are becoming more commonplace in water distribution systems. The overall objective of the sensor network is to protect consumers from accidental and malevolent contamination events occurring within the distribution network. This objective can be quantified several different ways including: minimizing the amount of contaminated water consumed, minimizing the extent of the contamination within the network, minimizing the time to detection, etc. We examine the ability of a sensor network to meet these objectives as a function of both the detection limit of the sensors and the number of sensors in the network. A moderately-sized network is used as an example and sensors are placed randomly. The source term is a passive injection into a node and the resulting concentration in the node is a function of the volumetric flow through that node. The concentration of the contaminant at the source node is averaged for all time steps during the injection period. For each combination of a certain number of sensors and a detection limit, the mean values of the different objectives across multiple random sensor placements are evaluated. Results of this analysis allow the tradeoff between the necessary detection limit in a sensor and the number of sensors to be evaluated. Results show that for the example problem examined here, a sensor detection limit of 0.01 of the average source concentration is adequate for maximum protection.

The effect of variable demands at short time scales on the transport of a solute through a water distribution network has not previously been studied. We simulate flow and transport in a small water distribution network using EPANET to explore the effect of variable demand on solute transport across a range of hydraulic time step scales from 1 minute to 2 hours. We show that variable demands at short time scales can have the following effects: smoothing of a pulse of tracer injected into a distribution network and increasing the variability of both the transport pathway and transport timing through the network. Variable demands are simulated for these different time step sizes using a previously developed Poisson rectangular pulse (PRP) demand generator that considers demand at a node to be a combination of exponentially distributed arrival times with log-normally distributed intensities and durations. Solute is introduced at a tank and at three different network nodes and concentrations are modeled through the system using the Lagrangian transport scheme within EPANET. The transport equations within EPANET assume perfect mixing of the solute within a parcel of water and therefore physical dispersion cannot occur. However, variation in demands along the solute transport path contribute to both removal and distortion of the injected pulse. The model performance measures examined are the distribution of the Reynolds number, the variation in the center of mass of the solute across time, and the transport path and timing of the solute through the network. Variation in all three performance measures is greatest at the shortest time step sizes. As the scale of the time step increases, the variability in these performance measures decreases. The largest time steps produce results that are inconsistent with the results produced by the smaller time steps.

Fingering, nonmonotonicity, fragmentation, and pulsation within gravity/buoyant destabilized two-phase/unsaturated flow systems has been widely observed with examples in homogeneous to heterogeneous porous media, in single fractures to fracture networks, and for both wetting and nonwetting invasion. To model this phenomena, we consider a mechanistic approach based on forms of modified invasion percolation (MIP) that include gravity, the influence of the local interfacial curvature along the phase-phase interface, and the simultaneous invasion and reinvasion of both wetting and nonwetting fluids. We present example simulations and compare them to experimental data for three very different situations: (1) downward gravity-driven fingering of water into a dry, homogeneous, water-wettable, porous medium; (2) upward buoyancy-driven migration of gas within a water saturated, heterogeneous, water-wettable, porous medium; and (3) downward gravity-driven fingering of water into a dry, water-wettable, rough-walled fracture.

The authors reconceptualize macro modified invasion percolation (MMIP) at the near pore (NP) scale and apply it to simulate the non-wetting phase invasion experiments of Glass et al [in review] conducted in macro-heterogeneous porous media. For experiments where viscous forces were non-negligible, they redefine the total pore filling pressure to include viscous losses within the invading phase as well as the viscous influence to decrease randomness imposed by capillary forces at the front. NP-MMIP exhibits the complex invasion order seen experimentally with characteristic alternations between periods of gravity stabilized and destabilized invasion growth controlled by capillary barriers. The breaching of these barriers and subsequent pore scale fingering of the non-wetting phase is represented extremely well as is the saturation field evolution, and total volume invaded.