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 ▲ Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-5271 Conference paper 2022 Wang L.; Jiang R.; Chen X.; Xie J.; Liu X.; Tian L.; Wang M. Design and Application of Digital Twin Platform Based Smart Weihe River Basin Proceedings of SPIE - The International Society for Optical Engineering 10.1117/12.2658268 With the comprehensively promoting the development of digital twins for large rivers and lakes on a national scale, the construction of a digital twin Weihe River Bain (WRB) has been given high priority. At present, WRB is generally still in the initial stages of smart water construction. The digital twin WRB is being built to address its problems in terms of information, intelligence and digitization. The overall framework of the digital twin Weihe River basin consists of a digital twin platform and an information infrastructure. The data base is used as the data construction support to supplement and generate the refined L2 data base of the WRB based on the national L1 data base. The professional model as the core of the algorithm provides physical mechanisms and data-driven models. The knowledge base is the driver for intelligent construction to broaden the data dimension of the digital twin WRB. The research has been designed to digitally map and intelligently simulate the entire physical elements of the smart WRB and the entire process of intelligent water management. The results have been applied in the construction of the digital twin based smart WRB. It can provide a reference for further improvement and development of digital twin river basin construction, which also provide ideas for a new phase of smart water development in the Wei River. Β© 2022 SPIE.
publications-5272 Conference paper 2022 Gyimah N.; Scheler O.; Rang T.; Pardy T. Digital twin for controlled generation of water-in-oil microdroplets with required size 2022 23rd International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems, EuroSimE 2022 10.1109/EuroSimE54907.2022.9758876 In this paper, we report a digital twin of a droplet microfluidic system with closed-loop droplet size control. Compared to the state-of-the-art, this digital twin allows evaluating the system for a wider range of droplet sizes. We constructed a digital twin of a microfluidic Flow-Focusing Device (FFD) that used a Proportional Integral (PI) controller to automatically adjust the flow rate of the dispersed phase, to obtain the required droplet size. The efficacy of the digital twin was evaluated using six droplet diameters ranging from 30-60 m. The simulation results show good agreement between the tested and measured droplet sizes (R2= 0.993). Β© 2022 IEEE.
publications-5273 Article 2022 Huang Y.; Yu S.; Luo B.; Li R.; Li C.; Huang W. Development of the digital twin Changjiang River with the pilot system of joint and intelligent regulation of water projects for flood management; [ι_x009d_Άε‘流ε_x009f__x009f_水工程防灾联合智能调度η_x009a_„ζ•°ε­—ε­η”_x009f_ι•Ώζ±_x009f_ζ_x008e_Άη΄Ά] Shuili Xuebao/Journal of Hydraulic Engineering 10.13243/j.cnki.slxb.20210865 The digital twin river is an inter-response relationship constructed between natural and management elements of a river, which is developed based on data-platform that integrates multi-source information such as spatial data, meteorological, hydrological, environmental data etc., using hybrid models that coupling physically-based mathematical models with data-driven approaches such as machine learning and knowledge graph, to realize the real-time mirroring of the whole process of water flow, information flow, application flow and value flow of the river, therefore to provide technical support for river management and the high-quality development of the river basin. Taking the application of flood management in the Changjiang River Basin as an example, aiming to realize the functionalities of river simulation, forecast and early warning, intelligent water engineering regulation, dynamic flood risk assessment, and system construction, the paper presents the framework for developing the digital twin river and its key technologies including the construction of data, models, intelligence and platform. The research results have been applied in the construction of the digital twin Changjiang River, and has obtained the complete processes for the intelligent regulation of engineering works for flood management, including"flood forecasting-early warning-rehearsals-pre-planning", and has provided technical support in 2020 the basin-scale flood management. The research results can provide demonstration and experience reference for the construction of digital twin river. Β© 2022, China Water Power Press. All right reserved.
publications-5274 Article 2022 Tian F.; Yuan X.; He L.; Wang X.; Wang L.; Guo L. Research progress on ice flood disasters risk assessment and prevention and control of the river channel-dike-flood plain in cold region; [ε―’ε_x008c_Ίζ²³ι“-ε ¤ι˜²-ζ³›ε_x008c_Ίε‡_x008c_汛灾害ι£_x008e_险评估防ζ_x008e_§η ”究进展] Shuili Xuebao/Journal of Hydraulic Engineering 10.13243/j.cnki.slxb.20210862 The gestationοΌ_x008c_occurrence and evolution of ice flood disasters in cold regions are closely related to the river channel-dike-flood plain system （RDFSοΌ‰οΌ_x008c_and the scientific assessment and prevention and control of ice flood disasters risk are of great importance. The "identification - calculation - assessment - prevention and control" of ice flood disasters risk was taken as the main line of thinking in this paper. The research progress from the following five aspectsοΌ_x009a_ causes and characteristics of ice flood disastersοΌ_x008c_numerical models of river ice and ice floodοΌ_x008c_river ice flood disasters risk assessmentοΌ_x008c_risk assessment of dyke failure and inundation during ice floodοΌ_x008c_and risk prevention and control measures of ice flood disasters were reviewed. The driving mechanism and chain effect of ice flood disasters in RDFSοΌ_x008c_disaster model of river ice evolution - ice flood backwater - dyke danger - ice flood inundationοΌ_x008c_risk quantitative assessment of ice backwater-dike burst-ice flood inundationοΌ_x008c_dyke freezing and thawing danger evolution mechanism and intelligent predictionοΌ_x008c_support system of ice flood disasters including monitoring-early warning-assessment-risk prevention and controlοΌ_x008c_the digital twin platform for "four presets" of ice flood disastersοΌ_x008c_were key directionsοΌ_x008c_which can provide important ideas for in-depth exploration and scientific management of the ice flood disasters risk in cold regions. Β© 2022 China Water Power Press. All rights reserved.
publications-5275 Article 2022 Tivay A.; Kramer G.C.; Hahn J.-O. Collective Variational Inference for Personalized and Generative Physiological Modeling: A Case Study on Hemorrhage Resuscitation IEEE Transactions on Biomedical Engineering 10.1109/TBME.2021.3103141 Objective: Individual physiological experiments typically provide useful but incomplete information about a studied physiological process. As a result, inferring the unknown parameters of a physiological model from experimental data is often challenging. The objective of this paper is to propose and illustrate the efficacy of a collective variational inference (C-VI) method, intended to reconcile low-information and heterogeneous data from a collection of experiments to produce robust personalized and generative physiological models. Methods: To derive the C-VI method, we utilize a probabilistic graphical model to impose structure on the available physiological data, and algorithmically characterize the graphical model using variational Bayesian inference techniques. To illustrate the efficacy of the C-VI method, we apply it to a case study on the mathematical modeling of hemorrhage resuscitation. Results: In the context of hemorrhage resuscitation modeling, the C-VI method could reconcile heterogeneous combinations of hematocrit, cardiac output, and blood pressure data across multiple experiments to obtain (i) robust personalized models along with associated measures of uncertainty and signal quality, and (ii) a generative model capable of reproducing the physiological behavior of the population. Conclusion: The C-VI method facilitates the personalized and generative modeling of physiological processes in the presence of low-information and heterogeneous data. Significance: The resulting models provide a solid basis for the development and testing of interpretable physiological monitoring, decision-support, and closed-loop control algorithms. Β© 1964-2012 IEEE.
publications-5276 Conference paper 2022 Han Z.; Wu J.; Li J.; Wang Y.; Hou X. Research on Digital Twin Modeling and Operation Energy Efficiency Improvement System of Wind-Solar Storage Base 2022 IEEE Conference on Telecommunications, Optics and Computer Science, TOCS 2022 10.1109/TOCS56154.2022.10016041 The transformation from a traditional city to an intelligent one requires a new energy system, and establishing a digital and interactive energy system is a very meaningful issue. The high-capacity wind and solar storage and output are random, which will lead to the dynamic instability of the power system of the power system, which will lead to the problem of load safety of the power system. Aiming at this problem, this paper studies the safety of a new type of power system load. On this basis, a new type of flexible configuration combination and on-site control method is proposed, which realizes the independent and complementary automatic conversion of wind and solar storage. Through experimental simulation, the results show that the proposed method and method have been practically applied in national wind-solar water storage demonstration projects. Β© 2022 IEEE.
publications-5277 Article 2022 Zekri S.; Jabeur N.; Gharrad H. SMART WATER MANAGEMENT USING INTELLIGENT DIGITAL TWINS Computing and Informatics 10.31577/CAI_2022_1_135 Providing and distributing fresh water to large communities is a major global concern. In addition to its scarcity as well as to its wastage, this vital resource is being affected by challenging environmental conditions. New approaches are, therefore, urgently needed for an optimized, fair, and efficient use of fresh water. The adoption of emergent technologies is giving high hopes to reach this objective. Among these technologies, digital twin is attracting increasing attention from the academic and industrial committees. This attention is particularly motivated by its expected values to any sector, including process optimization, cost reduction, and time to market shortening. In the specific field of water management, several solutions are being proposed, especially to detect leak detection and test water assets under a variety of working constraints. These solutions are still lacking intelligence and autonomy throughout the loop of data acquisition and processing as well as asset control and service generation and delivery. To this end, we are proposing in this paper a new framework based on multi-agent systems and DT paradigm to close gaps within this loop. Our multi-agent system is responsible of running data analytics mechanisms in order to assess water consumption and generate relevant feedbacks to users using, among others, a rewarding system to select the appropriate pricing policies. It is also responsible of simulating asset operations under specific working constraints for the purpose of failure and/or defect detection. Β© 2022 Slovak Academy of Sciences. All rights reserved.
publications-5278 Article 2022 Jin A.S.; Hogewood L.; Fries S.; Lambert J.H.; Fiondella L.; Strelzoff A.; Boone J.; Fleckner K.; Linkov I. Resilience of Cyber-Physical Systems: Role of AI, Digital Twins, and Edge Computing IEEE Engineering Management Review 10.1109/EMR.2022.3172649 Cyber-physical systems encompass multiple system domains (i.e., water, energy, networking) with heterogeneous goals and complexity of interactions. Existing technologies do not address the disparate time and spatial scales across the many system domains, especially with the latest threats and challenge spaces. New methods to manage resilience of systems, including integrating new computing and sensing strategies, machine learning and artificial intelligence, as well as advanced resilience analytics and prediction, are required to ensure that cyber-physical systems can withstand adverse events. This article summarizes the results of the December 2021 Society for Risk Analysis 'Workshop on Resilience Analytics: Methodology and Applications to Cyber-Energy Systems' in which a multidisciplinary team of researchers, policymakers, military, and industry professionals met to identify priorities for research. Β© 1973-2011 IEEE.
publications-5279 Conference paper 2022 Shrivastava S.; Furtado F.; Goh M.; Mathur A. The Design of Cyber-Physical Exercises (CPXS) International Conference on Cyber Conflict, CYCON 10.23919/CyCon55549.2022.9811000 This paper explores the objectives, tactics, and strategies for identifying, planning, conducting, and evaluating an international cyber-physical exercise (CPX). The goal of a CPX is to improve defense capabilities for defending national critical infrastructure via global coordination. Lessons about CPX have been derived from a series of annual cyber-physical defense exercises conducted since 2015, referred to as Critical Infrastructure Security Showdowns (CISS). The cyber range of a CISS consists of a realistic and operational enterprise network coupled to water treatment and distribution plants in the form of physical testbeds and digital twins. These systems simulate and integrate information technology (IT) and operational technology (OT) scenarios that are ubiquitous in modern-day critical infrastructure controlled by industrial control systems (ICS). Participants from the red, blue, green, and white teams are assigned specific roles to attack, defend, visualize, and manage the plant, respectively. Each of these roles is evaluated via a specific set of metrics by a panel of judges and automated systems. The scoring criteria incentivize the red teams to design and launch novel attacks to contribute to and improve the cybersecurity community's knowledge base regarding offense and defense. The lessons distilled from these positive-sum games are analyzed and shared in the form of post-event reports. From 2015 to 2021, CISS has constantly evolved to mimic contemporary cyber-physical security scenarios in the real world. These evolutions have forced the CISS organizing team to adapt and design novel infrastructure to support the changing needs of the event and its stakeholders, from tooling, logistics, and network infrastructure to scoring criteria and cross-disciplinary collaboration. The cited reports on techniques, tactics, and procedures will be valuable to stakeholders from the military, industry, government, and academia. Β© 2022 NATO CCDCOE.
publications-5280 Article 2022 Folgado F.J.; Orellana D.; GonzΓ΅lez I.; CalderΓ³n A.J. Processes Supervision System for Green Hydrogen Production: Experimental Characterization and Data Acquisition of PEM Electrolyzer β€ Engineering Proceedings 10.3390/ECP2022-12651 Green hydrogen is the term used to reflect the fact that hydrogen is generated from renewable energies. This process is commonly performed by means of water electrolysis, decomposing water molecules into oxygen and hydrogen in a zero emissions process. Proton exchange membrane (PEM) electrolyzers are applied for such a purpose. These devices are complex systems with non-linear behavior which impose the measurement and control of several magnitudes for an effective and safe operation. In this context, the modern paradigm of Digital Twin (DT) is applied to represent and even predict the electrolyzer behavior under different operating conditions. To build this cyber replica, a paramount previous stage consists of characterizing the device by means of the curves that relate current, voltage, and hydrogen flow. To this aim, this paper presents a processes supervision system focused on the characterization of a experimental PEM electrolyzer. This device is integrated in a microgrid for production of green hydrogen using photovoltaic energy. Three main functions must be performed by the supervision system: measurement of the process magnitudes, data acquisition and storage, and real-time visualization. To accomplish these tasks, firstly, a set of sensors measure the process variables. In second place, a programmable logic controller is responsible of acquiring the signals provided by the sensors. Finally, LabVIEW implements the user interface as well as data storage functions. The process evolution is observed in real-time through the user interface composed by graphical charts and numeric indicators. The deployed process supervision system is reported together with experimental results to prove its suitability. Β© 2022 by the authors.