| publications-3641 |
article |
2023 |
Ramos, Helena M. and Kuriqi, Alban and Besharat, Mohsen and Creaco, Enrico and Tasca, Elias SebastiΓ£o Amaral and Coronado-HernΓ΅ndez, Γ“scar E. and Pienika, Rodolfo and Iglesias-Rey, Pedro L. |
Smart Water Grids and Digital Twin for the Management of System Efficiency in Water Distribution Networks |
Water |
10.3390/w15061129 |
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One of the main factors contributing to water scarcity is water loss in water distribution systems, which mainly arises from a lack of adequate knowledge in the design process, optimization of water availability, and poor maintenance/management of the system. Thus, from the perspective of sustainable and integrated management of water resources, it is essential to enhance system efficiency by monitoring existing system elements and enhancing network maintenance/management practices. The current study establishes a smart water grid (SWG) with a digital twin (DT) for a water infrastructure to improve monitoring, management, and system efficiency. Such a tool allows live monitoring of system components, which can analyze different scenarios and variables, such as pressures, operating devices, regulation of different valves, and head-loss factors. The current study explores a case study in which local constraints amplify significant water losses. It develops and examines the DT model’s application in the Gaula water distribution network (WDN) in Madeira Island, Portugal. The developed methodology resulted in a significant potential reduction in real water losses, which presented a huge value of 434,273 m3 (~80\%) and significantly improved system efficiency. The result shows a meaningful economic benefit, with savings of about EUR 165k in water loss volume with limiting pressures above the regulatory maximum of 60 m w.c. after the district metered area (DMA) sectorization and the requalification of the network. Hence, only 40\% of the total annual volume, concerning the status quo situation, is necessary to supply the demand. The infrastructure leakage index measures the existing real losses and the reduction potential, reaching a value of 21.15, much higher than the recommended value of 4, revealing the great potential for improving the system efficiency using the proposed methodology. |
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| publications-3642 |
article |
2023 |
Alves, Rafael Gomes and Maia, Rodrigo Filev and Lima, Fabiana Roberto |
Development of a Digital Twin for smart farming: Irrigation management system for water saving |
Journal of Cleaner Production |
10.1016/j.jclepro.2023.135920 |
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| publications-3643 |
article |
2023 |
Sinagra, Marco and Creaco, Enrico and Morreale, Gabriele and Tucciarelli, Tullio |
Energy Recovery Optimization by Means of a Turbine in a Pressure Regulation Node of a Real Water Network Through a Data-Driven Digital Twin |
Water resources management |
10.1007/s11269-023-03575-0 |
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Abstract In recent years, various devices have been proposed for pressure regulation and energy recovery in water distribution and transport networks. To provide a real net benefit, they require a dedicated long-distance management system in order to carry on both hydraulic regulation and electricity production without direct human manual operations. This work presents a new proposal for the management of a pressure regulation system based on the PRS turbine. The proposal is applied to a real water distribution network, named Montescuro Ovest pipeline, at the San Giovannello station. The Real Time Control (RTC) logic currently applied at San Giovannello station is first presented and discussed. A new Advanced Real Time Control (ARTC) logic is then proposed, based on direct configuration of the turbine and the surrounding valves as computed by the solution of an optimization problem. In ARTC a digital twin, including the hydraulic model of the surrounding network, provides a one-to-one relationship between the configuration parameters and the state variables, i.e. flow rates and pressures. The digital twin model equations are continuously updated on the basis of the recorded measures. Besides providing almost identical performance to the current RTC logic in the current operational scenario, the improved ARTC is more robust, in that it guarantees better hydropower generation in modified operational scenarios, as shown in specific tests. The proposed methodology constitutes a new approach to regulating the valves in hydroelectric plants which are currently regulated with traditional automation algorithms. |
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| publications-3644 |
article |
2023 |
Sabri, Soheil and Alexandridis, K. and Koohikamali, Mehrdad and Zhang, Sonya and Ozkaya, H. E. |
Designing a Spatially-explicit Urban Digital Twin Framework for Smart Water Infrastructure and Flood Management |
2023 IEEE 3rd International Conference on Digital Twins and Parallel Intelligence (DTPI) |
10.1109/dtpi59677.2023.10365478 |
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This paper outlines the requirements and challenges of designing and applying spatially explicit urban digital twin technology for managing critical water infrastructure and flood impacts in Smart Cities. It emphasizes the significance of incorporating accurate and reliable location-based data and technologies using Geographic Information Science (GIScience) methods such as Geosimulation, spatial-visual intelligence, and GeoAI, in smart infrastructure systems. Two case studies, Orange County, California, and Victoria, Australia, exemplify this approach. The paper also discusses technical factors and provides a roadmap for creating spatially-explicit urban digital twins to enhance smart urban water and flood management systems. |
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| publications-3645 |
article |
2023 |
MΓΌcke, Nikolaj T. and Pandey, P. S. and Jain, Shashi and BohtΓ©, Sander M. and Oosterlee, Cornelis W. |
A Probabilistic Digital Twin for Leak Localization in Water Distribution Networks Using Generative Deep Learning |
Italian National Conference on Sensors |
10.3390/s23136179 |
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Localizing leakages in large water distribution systems is an important and ever-present problem. Due to the complexity originating from water pipeline networks, too few sensors, and noisy measurements, this is a highly challenging problem to solve. In this work, we present a methodology based on generative deep learning and Bayesian inference for leak localization with uncertainty quantification. A generative model, utilizing deep neural networks, serves as a probabilistic surrogate model that replaces the full equations, while at the same time also incorporating the uncertainty inherent in such models. By embedding this surrogate model into a Bayesian inference scheme, leaks are located by combining sensor observations with a model output approximating the true posterior distribution for possible leak locations. We show that our methodology enables producing fast, accurate, and trustworthy results. It showed a convincing performance on three problems with increasing complexity. For a simple test case, the Hanoi network, the average topological distance (ATD) between the predicted and true leak location ranged from 0.3 to 3 with a varying number of sensors and level of measurement noise. For two more complex test cases, the ATD ranged from 0.75 to 4 and from 1.5 to 10, respectively. Furthermore, accuracies upwards of 83\%, 72\%, and 42\% were achieved for the three test cases, respectively. The computation times ranged from 0.1 to 13 s, depending on the size of the neural network employed. This work serves as an example of a digital twin for a sophisticated application of advanced mathematical and deep learning techniques in the area of leak detection. |
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| publications-3646 |
article |
2023 |
Zhu, Jianwen and Li, Juan |
Application of Digital Twin Technology in the Operation and Management of Water Diversion Project |
International Journal of Frontiers in Engineering Technology |
10.25236/ijfet.2023.051013 |
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This paper analyzes the current situation of the operation and management of water diversion projects, combines digital twin technology, and preliminarily explores and forms a theoretical system for the application of digital twin technology in the operation of water diversion projects such as panoramic monitoring and unified water quantity scheduling management, and introduces the application of the above theoretical system in the operation and management of a water diversion project. |
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| publications-3647 |
article |
2023 |
Kim, Byungmo and Oh, Jaewon and Min, Cheonhong |
Development of a Simulation Model for Digital Twin of an Oscillating Water Column Wave Power Generator Structure with Ocean Environmental Effect |
Italian National Conference on Sensors |
10.3390/s23239472 |
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This research article focuses on developing a baseline digital twin model for a wave power generator structure located in Yongsu-ri, Jeju-do, South Korea. First, this study performs a cause analysis on the discrepancy of the dynamic properties from the real structure and an existing simulation model and finds the necessity of modeling the non-structural masses and the environmental factors. The large amounts of the ballast are modeled in the finite element model to enhance the accuracy of the digital twin. Considering the influence of environmental factors such as tide level and wave direction, the added mass effect of structural members, one of the hydrodynamic effects, depending on the change of the ocean environments is calculated based on the rule of Det Norske Veritas and applied. The results indicate that non-structural mass components significantly impact the dynamic characteristics of the structure. Additionally, environmental factors have a greater effect on the dynamic behavior of the box-type structure compared to lightweight offshore structures. |
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| publications-3648 |
article |
2023 |
Ciliberti, Francesco and Berardi, Luigi and Laucelli, Daniele Biagio and Giustolisi, Orazio |
Digital Water Services using Digital Twin paradigm |
IOP Conference Series: Earth and Environment |
10.1088/1755-1315/1136/1/012002 |
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Abstract In the last years, the digital transition concept has spread all over public and private life as a process designed for improving problem solving in industry by the combination of models, information, and connectivity technologies. In the Water Distribution Networks (WDNs) management sector, the innovations in the areas of ICT/IoT, virtual representation of infrastructure elements in GIS/BIM platforms and the advancements in hydraulic modelling offer the opportunity to open a new era for water engineering. Nonetheless, a unique consensus about the digital transformation meaning in WDNs management is still missing. In this paper a recent paradigm for the digital transformation for WDNs is exposed and further extended, starting from the concept of Digital Twin for WDNs management. It encompasses the virtual representation of features and devices of the network integrated with advanced hydraulic modelling and Artificial Intelligence for supporting WDNs management tasks. The WDN Digital Twin is used within tools, named Digital Water Services (DWSs), working on GIS platforms. DWSs are conceived to support distinct phases of WDNs management by improving engineering awareness on technical decisions. Several DWSs, previously adopted for real WDNs management and planning, are here presented, as support tools for technicians and water utilities for achieving short-term and long-term management tasks. |
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| publications-3649 |
article |
2023 |
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The digital twin application of the installation for electrochemical water activation in the educational process |
Automation. Modern Techologies |
10.36652/0869-4931-2023-77-6-247-251 |
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The issues of developing a digital twin of an installation for the electrochemical activation of water using the Trace Mode 6 SCADA system are considered. Keywords digital twin, electrochemical activation of water, control object, regulation, automation, transfer function, education |
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| publications-3650 |
article |
2023 |
Wang, Fenjia and Song, Yong and Liu, Chao and He, Anrui and Qiang, Yi |
Multi-objective optimal scheduling of laminar cooling water supply system for hot rolling mills driven by digital twin for energy-saving |
Journal of Process Control |
10.1016/j.jprocont.2023.01.004 |
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