suwss-dev.ust.hkSmart Urban Water Supply System (Smart

UWSS) Smart Urban Water Supply Systems (Smart UWSS) Developing a Sustainable Environment Introduction Mission Tasks Our team Advisory Collaboration Management Facilities Publication Publicity Job vacancies Events Downloads LinksWe have a new website We have a new website in google site ( http://sites.google.com/view/smartuwss ). For whose who has difficulty accessing google, please stay in this site. Introduction Urban water supply systems (UWSS) are the lifeline of 3 billion people globally; however, these vital systems are aging and fraught with deficiencies and inefficiencies. In Hong Kong (HK), UWSS, comprised of thousands of devices and about 7,800km of conduits. They leak water at an annual cost of more than HK$1 billion. Pipe failures can paralyze businesses and cause devastating urban floods. Worldwide, UWSS are challenged by urban growth and climate change. And yet current methods to diagnose leakage and defects in complex underground UWSS networks are deficient. Water infrastructure has been highlighted as a critical issue nationally—in the 2011 No. 1 document” issued by the Chinese Central Government; the 2011 Green Quality Living in Greater Pearl River Delta” study, and the 2008 Total Water Management” and 2015 Water Intelligent Network ( WIN )” policy of HK government. Many other countries have critical needs for massive UWSSBoth the Singapore and HK systems are passive in that they have no mechanism to inject waves to probe the system. Such systems target faults that generate sudden large transients (e.g., bursts), but not blockages, pre-existing leaks and poorly performing devices, and small cracks. For example, the acoustic noise that emanates from a leak is local (i.e., does not propagate far in the fluid); thus, it cannot be detected by passive measurements of pressure signals. By contrast, the Smart UWSS envisioned here would use active wave probing, where it has been shown that wave reflections from leaks and other imperfections propagate far (~kilometers). A pipe system can be viewed as essentially a confined space with a longitudinal dimension much larger than a highly bounded lateral dimension. The pipes serve the function of flow conveyance and are inherently passive. However, dynamic controls are created at the ends of pipe mains over long distances – at pumps, valves, storage elements, and demand connections – the 3D turbulent flow behavior (e.g., pressure – flow) of these devices are inherently complex and boundary conditions must be introduced to describe their role in pressure wave propagation. These devices range from a simple isolation valve (that is normally either open or closed) to an active air valve with transient two-phase flow character, to an operating pump station. The dynamic response of the pipe system to any excitation is created, maintained and modified by actions at boundaries. Yet, LFW methodologies use models that originate in steady state theory, where inertial effects are neglected and their parameters are associated with steady turbulent flows, to represent these important actions. In this proposal, particular attention is paid to the study of critical boundary elements and the proper formulation of boundary conditions in the theoretical model ( Tasks 1, 2 , 4 ). PART B: The Proposed System The effective solution of the Smart UWSS problem requires a two-order-of-magnitude increase in the speed, range and accuracy with which UWSS faults can be pinpointed and rectified – the goal of this project. Indeed, it is evident that massive improvements in the management of UWSS are needed to safeguard health and sustainability issues brought about by rapid urbanization (in China alone ~200 million more people are expected to move to cities by 2030). We envisage a smart UWSS infrastructure as illustrated in the figure below. Currently, there is no system capable of producing reliable high-resolution images” (we use images” to mean that the Smart UWSS ’s output will provide accurate identification & localization of anomalies) of the pipe system. The bottom plate depicts a small section of a pipe system situated under roads and buildings. Its state and condition are unknown. The sensors in the pipes generate, transmit and receive pressure wave signals, and the data is communicated using acoustic waves to SCADA base-stations in real-time. This wave data is then relayed to remote servers using (an often existing) wireless communication platform. The data is then transformed into sharp images of system state. The top portion is a depiction of the type of defects to be identified. The proposed system is firmly founded on wave theory which is widely used to probe and characterize various media and to convey information in various applications that include non-destructive material testing, medical diagnostics, and underwater communications. The spatial range and spatial resolution of the probing waves are two essential properties underlying the system design. The spatial range, R , of waves travelling within the fluid in the pipe flow is of the order of a 2 /f 2 DVF 0.5 , where a = wave speed, f = frequency, D= pipe diameter, and V is the average fluid velocity; F is a damping coefficient. The spatial resolution, l , is of the order of a/f . It is clear that as an increase in the wave frequency is accompanied by a reduction in range and increase in resolution, and vice-versa. Using typical values of a , D , V and F , LFW have spatial resolution in the order of 50-100 m and range of the order of ~10 km. Therefore, LFW have a wide range but relatively low spatial resolution; high frequency waves (HFW) have the opposite attributes. The proposed work represents the marriage of the relative strengths of both LFW and HFW techniques. Currently LFW techniques are limited in several ways (see paragraphLimitations of LFW ”). With better device characterization (Tasks 1, 2 ), better signal design, conditioning and analysis ( Tasks 1 , 3 ), LFW methods can be usefully deployed on restrictive parts of the system such as within District Metering Area (DMA) boundaries - the approach is ideally suited for obtaining rapid but blurred images of a large part of the pipe system, where zones that contain potential problems are delineated for further investigation ( Task 4 ). On the other hand, the HFW (10 to 40 kHz) methods, developed in Tasks 1 , 2 have the potential to provide high resolution images when applied to problematic zones identified by LFW ( Task 4 ). Such waves have resolution of the order of centimeters to meters and are less susceptible to interference from the ever-present system noise (frequencies1 kHz). Their range is of the order of 100 m to a few kilometres which is sufficient to investigate the zones that are deemed problematic by LFW. This HFW approach is supported by our preliminary numerical and experimental research. In particular, the use of the HFW method in pipe diagnostics has been successfully tested in proof-of-concept field trials across 30 sites in NZ and China in collaboration with a leading water utility company. Preliminary results showed that HFW can be transmitted across distances of over 300 m. A comprehensive theoretical and experimental understanding of HFW propagation in a turbulent pipe flow will be developed in this research ( Tasks 1 , 2 ) – which would lead to paradigm shifts in real-time pipeline condition assessment ( Tasks 3 , 4 ). HFW will be generated by compact, piezoelectric actuators that result in no water loss or system disruption ( Tasks 1 , 3 ). In addition to their imaging capability, HFW are also essential to the novel concepts of both acoustic communication between in-pipe sensors and executing hydraulic controls ( Task 3 ). Existing systems (e.g., WaterWise@SG) use a network of integrated multi-sensor probes to acquire and transmit data in real-time through wireless sensing nodes, where the connection of the sensing nodes to the pipes require specific access points. Issues...