Scientific Results

This catalogue is obtained by conducting a systematic literature review of scientific studies and reviews related to monitoring, forecasting, and simulating the inland water cycle. The analysis maps scientific expertise across research groups and classifies findings by the type of inland water studied, application focus, and geographical scope. A gap analysis will identify missing research areas and assess their relevance to policymaking.

ID â–² Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-4421 article 2014 Tao, Tao and Tao, Tao and Tao, Tao and Huang, Haidong and Huang, Haidong and Li, FΔ“i and Li, Fei and Xin, Kunlun and Xin, Kunlun and Xin, Kunlun Burst Detection Using an Artificial Immune Network in Water-Distribution Systems Journal of Water Resources Planning and Management 10.1061/(asce)wr.1943-5452.0000405 AbstractA new method using artificial immune network is presented to identify pipe burst in water-distribution systems. Burst detection is considered as the problem of pattern recognition in the proposed method. An artificial database that includes information on burst events (BEs) is first established. Using the clonal selection algorithm, the artificial immune network is constructed based on the principle of immune system. The burst location is finally identified using the nearest neighbor method. Three offline case studies are illustrated in detail to evaluate the current method. A total of five possible burst locations are identified from 34 nodes in Case Study 1, whereas four possible burst locations are identified from 77 nodes in Case Study 2. The results derived from the first two case studies show that the method can identify the possible burst areas, including the true burst location, using model-simulated results. The data derived from real BEs in Case Study 3 are used to evaluate the proposed ...
publications-4422 article 2014 Mounce, S. R. and Mounce, Stephen R. and Mounce, Richard and Mounce, Richard and Jackson, Thomas W. and Jackson, Thomas and Jackson, Thomas and Jackson, Thomas and Jackson, Thomas J. and Austin, J. and Austin, Jim and Austin, Jim and Boxall, Joby and Boxall, Joby Pattern matching and associative artificial neural networks for water distribution system time series data analysis Journal of Hydroinformatics 10.2166/hydro.2013.057 Water distribution systems, and other infrastructures, are increasingly being pervaded by sensing technologies, collecting a growing volume of data aimed at supporting operational and investment decisions. These sensors monitor system characteristics, i.e. flows, pressures and water quality, such as in pipes. This paper presents the application of pattern matching techniques and binary associative neural networks for novelty detection in such data. A protocol for applying pattern matching to automatically recognise specific waveforms in time series based on their shapes is described together with a system called Advanced Uncertain Reasoning Architecture (AURA) Alert for autonomous determination of novelty. AURA is a class of binary neural network that has a number of advantages over standard artificial neural network techniques for condition monitoring including a sound theoretical basis to determine the bounds of the system operation. Results from application to several case studies are provided including both hydraulic and water quality data. In the case of pattern matching, the results demonstrated some transferability of burst patterns across District Metered Areas; however limitations in performance and difficulties with assembling pattern libraries were found. Results for the AURA system demonstrate the potential for robust event detection across multiple parameters providing valuable information for diagnosis; one example also demonstrates the potential for detection of precursor information, vital for proactive management.
publications-4423 article 2016 Schroeder, Greyce N. and Schroeder, Greyce and Steinmetz, Charles and Steinmetz, Charles and Pereira, Carlos Eduardo and Pereira, Carlos Eduardo and Pereira, Carlos Eduardo and Pereira, Carlos Eduardo and EspΓ­ndola, DanΓΊbia and Espindola, Danubia Digital Twin Data Modeling with AutomationML and a Communication Methodology for Data Exchange IFAC-PapersOnLine 10.1016/j.ifacol.2016.11.115 Abstract: In the context of the Cyber Physical Systems toward the realization of a Digital Twin system for future manufacturing and product service systems we propose the use of AutomationML to model attributes related to the Digital Twin. Also, we propose that this model is very useful for data exchange between different systems that are connected with the Digital Twin. We present a case study where a industrial component was modeled and simulated to prove that our methodology works.
publications-4424 article 2016 Canedo, Arquimedes and Canedo, Arquimedes Industrial IoT lifecycle via digital twins 10.1145/2968456.2974007 Currently, the IoT discussion is focused primarily on the operational phase. This includes how a IoT device behaves, operates, communicates, and interacts with other IoT devices during operation. However, IoT devices and systems have other lifecycle phases before and after operation. This extended abstract provides an overview of how other IoT lifecycle phases (e.g., design and service) can be improved with information feedback and feedforward flows between them. Digital Twins are a new mechanism to manage IoT devices and IoT systems-of-systems throughout their lifecycle. We present our vision on the industrial IoT lifecycle managed and optimized at scale via Digital Twins.
publications-4425 article 2016 Gong, Weijiao and Gong, Weijiao and Suresh, Mahima Agumbe and Suresh, Mahima Agumbe and Smith, Lidia and Smith, Lidia and Ostfeld, Avi and Ostfeld, Avi and Stoleru, Radu and Stoleru, Radu and Rasekh, Amin and Rasekh, Amin and Banks, M. Katherine and Banks, M. Katherine Mobile sensor networks for optimal leak and backflow detection and localization in municipal water networks Environmental Modelling and Software 10.1016/j.envsoft.2016.02.001 Leak and backflow detections are essential aspects of Water Distribution Systems (WDSs) monitoring and are commonly fulfilled using approaches that are based on static sensor networks and point measurements. Alternatively, we propose a mobile, wireless sensor network solution composed of mobile sensor nodes that travel freely inside the pipes with the water flow, collect and transmit measurements in near-realtime (called sensors) and static access points (called beacons). This study complements the tremendous progress in mobile sensor technology. We formulate the sensor and beacon optimal placement task as a Mixed Integer Nonlinear Programming (MINLP) problem to maximize localization accuracy with budget constraint. Given the high time complexity of MINLP formulation, we propose a disjoint scheme that follows the strategy of splitting the sensor and beacon placement problems and determining the respective number of sensors and beacons by exhaustive search in linear time. We present a mathematical model for the joint optimization of sensor and beacon placement to minimize localization error.We propose a computationally less expensive disjoint formulation for sensor and beacon placement.We demonstrate the advantage of our solution on a sample WDS from EPANET and a virtual model city called Micropolis.
publications-4426 article 2017 Alam, Kazi Masudul and Alam, Kazi Masudul and Saddik, Abdulmotaleb El and Saddik, Abdulmotaleb El C2PS: A Digital Twin Architecture Reference Model for the Cloud-Based Cyber-Physical Systems IEEE Access 10.1109/access.2017.2657006 Cyber-physical system (CPS) is a new trend in the Internet-of-Things related research works, where physical systems act as the sensors to collect real-world information and communicate them to the computation modules (i.e. cyber layer), which further analyze and notify the findings to the corresponding physical systems through a feedback loop. Contemporary researchers recommend integrating cloud technologies in the CPS cyber layer to ensure the scalability of storage, computation, and cross domain communication capabilities. Though there exist a few descriptive models of the cloud-based CPS architecture, it is important to analytically describe the key CPS properties: computation, control, and communication. In this paper, we present a digital twin architecture reference model for the cloud-based CPS, C2PS, where we analytically describe the key properties of the C2PS. The model helps in identifying various degrees of basic and hybrid computation-interaction modes in this paradigm. We have designed C2PS smart interaction controller using a Bayesian belief network, so that the system dynamically considers current contexts. The composition of fuzzy rule base with the Bayes network further enables the system with reconfiguration capability. We also describe analytically, how C2PS subsystem communications can generate even more complex system-of-systems. Later, we present a telematics-based prototype driving assistance application for the vehicular domain of C2PS, VCPS, to demonstrate the efficacy of the architecture reference model.
publications-4427 article 2017 Candelieri, Antonio and Candelieri, Antonio and Candelieri, Antonio Clustering and Support Vector Regression for Water Demand Forecasting and Anomaly Detection Water 10.3390/w9030224 This paper presents a completely data-driven and machine-learning-based approach, in two stages, to first characterize and then forecast hourly water demand in the short term with applications of two different data sources: urban water demand (SCADA data) and individual customer water consumption (AMR data). In the first case, reliable forecasting can be used to optimize operations, particularly the pumping schedule, in order to reduce energy-related costs, while in the second case, the comparison between forecast and actual values may support the online detection of anomalies, such as smart meter faults, fraud or possible cyber-physical attacks. Results are presented for a real case: the water distribution network in Milan.
publications-4428 article 2017 Uhlemann, Thomas H.-J. and Uhlemann, Thomas H.-J. and Lehmann, Christian W. and Lehmann, Christian and Lehmann, Christian and Lehmann, Christian and Steinhilper, Rolf and Steinhilper, Rolf The Digital Twin: Realizing the Cyber-Physical Production System for Industry 4.0☆ Procedia CIRP 10.1016/j.procir.2016.11.152 Abstract Concerning current approaches to planning of manufacturing processes, the acquisition of a sufficient data basis of the relevant process information and subsequent development of feasible layout options requires 74\% of the overall time-consumption. However, the application of fully automated techniques within planning processes is not yet common practice. Deficits are to be observed in the course of the use of a fully automated data acquisition of the underlying process data, a key element of Industry 4.0, as well as the evaluation and quantification and analysis of the gathered data. As the majority of the planning operations are conducted manually, the lack of any theoretical evaluation renders a benchmarking of the results difficult. Current planning processes analyze the manually achieved results with the aid of simulation. Evaluation and quantification of the planning procedure are limited by complexity that defies manual controllability. Research is therefore required with regard to automated data acquisition and selection, as the near real-time evaluation and analysis of a highly complex production systems relies on a real-time generated database. The paper presents practically feasible approaches to a multi-modal data acquisition approach, its requirements and limitations. The further concept of the Digital Twin for a production process enables a coupling of the production system with its digital equivalent as a base for an optimization with a minimized delay between the time of data acquisition and the creation of the Digital Twin. Therefore a digital data acquisition approach is necessary. As a consequence a cyber-physical production system can be generated, that opens up powerful applications. To ensure a maximum concordance of the cyber-physical process with its real-life model a multimodal data acquisition and evaluation has to be conducted. The paper therefore presents a concept for the composition of a database and proposes guidelines for the implementation of the Digital Twin in production systems in small and medium-sized enterprises.
publications-4429 article 1997 Ormsbee, Lindell and Ormsbee, Lindell and Lingireddy, Srinivasa and Lingireddy, Srinivasa Calibrating hydraulic network models Journal American Water Works Association 10.1002/j.1551-8833.1997.tb08177.x Although calibration should always be included in any hydraulic analysis, it is often neglected or done haphazardly. As a result, inappropriate data may be used or data errors may be overlooked so the resulting hydraulic model is of limited value. The novice may see calibrating a hydraulic network model as a task as daunting as climbing Mt. Everest. This article presents a seven-step method for use in calibrating a hydraulic network model. The last and most difficult step is microlevel calibration, which involves the adjustment of demand loadings and pipe roughnesses until computed and observed field pressures or flow rates are within reasonable agreement for various levels and extremes of demand, pumping, and storage. Various explicit calibration algorithms have reduced the need for trial-and-error procedures and have improved the reliability of the resulting calibration. There remains little justification for failing to develop good calibrated network models prior to network analysis.
publications-4430 article 1999 Tryby, Michael E. and Tryby, Michael E. and Boccelli, Dominic L. and Boccelli, Dominic L. and Koechling, Margarete T. and Koechling, Margarete T. and Uber, James G. and Uber, James G. and Summers, R. Scott and Summers, R. Scott and Rossman, Lewis A. and Rossman, Lewis A. Booster chlorination for managing disinfectant residuals Journal American Water Works Association 10.1002/j.1551-8833.1999.tb08574.x Booster chlorination is an approach to residual maintenance in which chlorine is applied at strategic locations within the distribution system. Situations in which booster chlorination may be most effective for maintaining a residual are explained informally in the context of a conceptual distribution system. To form the basis of a quantitative analysis of booster conditions. These experiments suggested a conceptual model for bulk chlorine decay, which is used to analyze an example representing a header pipe serving two distinct zones in a distribution system. The chlorine mass savings associated with booster chlorination in this example are derived and used to show the influence of flow rates, residence times, and decay kinetics on the effectiveness of booster chlorination. The role of booster chlorination is also discussed as part of coordinated treatment efforts meant to manage the risks associated with biological regrowth and disinfection by-products.