Developing Multi-Scale Models for Water Quality Management in Drinking Water Distribution Systems

Drinking water supply systems belong to the group of critical infrastructure systems that support the socioeconomic development of our modern societies. In addition, drinking water infrastructure plays a key role in the protection of public health by providing a common access to clean and safe water for all our municipal, industrial, and firefighting purposes. Yet, in the United States, much of our national water infrastructure is now approaching the end of its useful life while investments in its replacement and rehabilitation have been consistently inadequate. Furthermore, the aging water infrastructure has often been operated empirically, and the embracement of modern technologies in infrastructure monitoring and management has been limited. Deterioration of the water infrastructure and poor water quality management practices both have serious impacts on public health due to the increased likelihood of contamination events and waterborne disease outbreaks. Water quality reaching the consumers’ taps is largely dependent on a group of physical, chemical, and biological interactions that take place as the water transports through the pipes of the distribution system and inside premise plumbing. These interactions include the decay of disinfectant residuals, the formation of disinfection by-products (DBPs), the corrosion of pipe materials, and the growth and accumulation of microbial species. In addition, the highly dynamic nature of the system’s hydraulics adds another layer of complexity as they control the fate and transport of the various constituents. On the other hand, the huge scale of water distribution systems contributes dramatically to this deterioration mainly due to the long transport times between treatment and consumption points. Hence, utilities face a considerable challenge to efficiently manage the water quality in their aging distribution systems, and to stay in compliance with all regulatory standards. By integrating on-line monitoring with real-time simulation and control, smart water networks offer a promising paradigm shift to the way utilities manage water quality in their systems. Yet, multiple scientific gaps and engineering challenges still stand in the way towards the successful implementation of such advanced systems. In general, a fundamental understanding of the different physical, chemical, and biological processes that control the water quality is a crucial first step towards developing useful modeling tools. Furthermore, water quality models need to be accurate; to properly simulate the concentrations of the different constituents at the points of consumption, and fast; to allow their implementation in real-time optimization algorithms that sample different operational scenarios in real-time. On-line water quality monitoring tools need be both reliable and inexpensive to enable the ubiquitous surveillance of the system at all times. The main objective of this dissertation is to create advanced computational tools for water quality management in water distribution systems through the development and application of a multi-scale modeling framework. Since the above-mentioned interactions take place at different length and time scales, this work aims at developing computational models that are capable of providing the best description of each of the processes of interest by properly simulating each of its underlying phenomena at its appropriate scale of resolution. Molecular scale modeling using tools of ab-initio quantum chemical calculations and molecular dynamics simulations is employed to provide detailed descriptions of the chemical reactions happening at the atomistic level with the aim of investigating reaction mechanisms and developing novel materials for environmental sensing. Continuum scale reactive-transport models are developed for simulating the spatial and temporal distributions of the different compounds at the pipe level considering the effects of the dynamic hydraulics in the system driven by the spatiotemporal variability in water demands. System scale models are designed to optimize the operation of the different elements of the system by performing large-scale simulations coupled with optimization algorithms to identify the optimal operational strategies as a basis for accurate decision-making and superior water quality management. In conclusion, the computational models developed in this study can either be implemented as stand-alone tools for simulating the fundamental processes dictating the water quality at different scales of resolution, or be integrated into a unified framework in which information from the small scale models are propagated into the larger scale models to render a high fidelity representation of these processes

Smart Urban Water Networks

This book presents the paper form of the Special Issue (SI) on Smart Urban Water Networks. The number and topics of the papers in the SI confirm the growing interest of operators and researchers for the new paradigm of smart networks, as part of the more general smart city. The SI showed that digital information and communication technology (ICT), with the implementation of smart meters and other digital devices, can significantly improve the modelling and the management of urban water networks, contributing to a radical transformation of the traditional paradigm of water utilities. The paper collection in this SI includes different crucial topics such as the reliability, resilience, and performance of water networks, innovative demand management, and the novel challenge of real-time control and operation, along with their implications for cyber-security. The SI collected fourteen papers that provide a wide perspective of solutions, trends, and challenges in the contest of smart urban water networks. Some solutions have already been implemented in pilot sites (i.e., for water network partitioning, cyber-security, and water demand disaggregation and forecasting), while further investigations are required for other methods, e.g., the data-driven approaches for real time control. In all cases, a new deal between academia, industry, and governments must be embraced to start the new era of smart urban water systems

Occupant-Centric Simulation-Aided Building Design Theory, Application, and Case Studies

This book promotes occupants as a focal point for the design process

Full Proceedings, 2018

Full conference proceedings for the 2018 International Building Physics Association Conference hosted at Syracuse University

Controlling Hazardous Releases While Protecting Passengers in Civil Infrastructure Systems

The threat of accidental or deliberate toxic chemicals released into public spaces is a significant concern to public safety, and the real-time detection and mitigation of such hazardous contaminants has the potential to minimize harm and save lives. Furthermore, the safe evacuation of occupants during such a catastrophe is of utmost importance. This research entails a comprehensive means to address such scenarios, through both the sensing and control of contaminants, and the modeling of and potential communication to occupants as they evacuate. First, a computational fluid dynamics model has been developed that is capable of detecting and mitigating the hazardous contaminant over several time horizons using model predictive control optimization. Next, an evacuation agent-based model has been designed and coupled with the flow control model to simulate agents evacuating while interacting with a dynamic, threatening environment. Finally, a physical prototype (blower wind tunnel) has been constructed with capability of detection (via Ethernet-connected camera) of and mitigation (via compressed-air operated actuators) of a `contaminant' (i.e. smoke) to test the real-time feasibility of the computational fluid dynamics flow control model.PHDEnvironmental EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/135812/1/srimer_1.pd

Salford postgraduate annual research conference (SPARC) 2012 proceedings

These proceedings bring together a selection of papers from the 2012 Salford Postgraduate Annual Research Conference (SPARC). They reflect the breadth and diversity of research interests showcased at the conference, at which over 130 researchers from Salford, the North West and other UK universities presented their work. 21 papers are collated here from the humanities, arts, social sciences, health, engineering, environment and life sciences, built environment and business

Risk Exposure to Particles – including Legionella pneumophila – emitted during Showering with Water-Saving Showers

The increase in legionellosis incidence in the general population in recent years calls for a better characterization of the sources of infection, such as showering. Water-efficient shower systems that use water atomization technology may emit slightly more inhalable bacteria-sized particles than traditional systems, which may increase the risk of users inhaling contaminants associated with these water droplets. To evaluate the risk, the number and mass of inhalable water droplets emitted by twelve showerheads—eight using water-atomization technology and four using continuous-flow technology— were monitored in a shower stall. The water-atomizing showers tested not only had lower flow rates, but also larger spray angles, less nozzles, and larger nozzle diameters than those of the continuous-flow showerheads. A difference in the behavior of inhalable water droplets between the two technologies was observed, both unobstructed or in the presence of a mannequin. The evaporation of inhalable water droplets emitted by the water-atomization showers favored a homogenous distribution in the shower stall. In the presence of the mannequin, the number and mass of inhalable droplets increased for the continuous-flow showerheads and decreased for the water-atomization showerheads. The water-atomization showerheads emitted less inhalable water mass than the continuous-flow showerheads did per unit of time; however, they generally emitted a slightly higher number of inhalable droplets—only one model performed as well as the continuous-flow showerheads in this regard. To specifically assess the aerosolisation rate of bacteria, in particular of the opportunistic water pathogen Legionella pneumophila, during showering controlled experiments were run with one atomization showerhead and one continuous-flow, first inside a glove box, second inside a shower stall. The bioaerosols were sampled with a Coriolis® air sampler and the total number of viable (cultivable and noncultivable) bacteria was determined by flow cytometry and culture. We found that the rate of viable and cultivable Legionella aerosolized from the water jet was similar between the two showerheads: the viable fraction represents 0.02% of the overall bacteria present in water, while the cultivable fraction corresponds to only 0.0005%. The two showerhead models emitted a similar ratio of airborne Legionella viable and cultivable per volume of water used. Similar results were obtained with naturally contaminated hoses tested in shower stall. Therefore, the risk of exposure to Legionella is not expected to increase significantly with the new generation of water-efficient showerheads

Cognitive Buildings

Cognitive building is a pioneering topic envisioning the future of our built environment. The concept of "cognitive" provides a paradigm shift that steps from the static concept of the building as a container of human activities towards the modernist vision of "machine à habiter" of Le Corbusier, where the technological content adds the capability of learning from users' behavior and environmental variables to adapt itself to achieve major goals such as user comfort, energy-saving, flexible functionality, high durability, and good maintainability. The concept is based on digital frameworks and IoT networks towards the concept of a smart city