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	Abstract
publications-5031	Conference paper	2023	Kretschmer F.; Franziskowski S.; Huber F.; Ertl T.	Chances and barriers of building information modelling in wastewater management	Water Science and Technology	10.2166/wst.2023.079	The advancing digitalisation is one of the great challenges of our times. Related activities also concern the wastewater sector. In the field of building construction, one emerging approach is building information modelling (BIM). The presented work investigates to which extent BIM practices have already found their way to wastewater management, and what kind of benefits and constraints are incorporated. Information is collected by means of a literature review and international expert surveys. Results indicate that several BIM-related key elements are already well established in the sector, but not necessarily in the intended manner. Consequently, the digital transition in the wastewater sector is not about replacing existing procedures and techniques but to rethink and optimise them. This primarily concerns data and information management in combination with the application of digital tools. Furthermore, wastewater management requires more integrated approaches, involving interdisciplinary/collaborative concepts and life cycle perspectives. Appropriate change management is necessary to give support and guidance to employees during the transition process. Furthermore, also from the political side, a clear definition and communication of the pursued digital vision is important. This article aims at stimulating discussion and research to optimise wastewater management from the digital perspective. Β© 2023 IWA Publishing. All rights reserved.
publications-5032	Article	2023	Alabugin A.; Osintsev K.; Aliukov S.; Almetova Z.; Bolkov Y.	Mathematical Foundations for Modeling a Zero-Carbon Electric Power System in Terms of Sustainability	Mathematics	10.3390/math11092180	This article substantiates the relevance of mathematical methods and models for studying the management of the factorial parameters of regulating the decarbonization of regions of the Russian Federation. We present methods for the mathematical modeling of greenhouse gas emissions and for approximating functions for the study of processes in the thermal power industry and the economy. New models and methods are shown to increase the efficiency of designing electric power systems (EPSs). We establish that diverse companies must interact with institutions of education and science to achieve the main results of the study. This is achieved, firstly, by creating an EPS with a target of a zero-carbon footprint. Mathematical models of greenhouse gas emissions can be used to support this goal. We developed ways to account for carbon oxides and water streams. Stable interactions between systems in the innovation cycles of enterprises are ensured by methods combining a number of properties of the regulation of decarbonization. We describe methods to mathematically model greenhouse gas emissions and to approximate functions in the study of processes in the thermal power industry and economics. New research methods and techniques are proved to increase the efficiency of designing an EPS and can be used to reduce emissions. Digital twins should be modeled according to assessments on ensuring the stability of the balance area, with the goals of developing the EPS. Secondly, we substantiate methods for displaying singular processes of improving the balance of enterprise goals while coordinating the impact on the efficiency of standard and additional management functions. We additionally developed quality parameters for the use of additional functions in the foresight control of decarbonization goals. Thirdly, factorial parameters of additional control and regulation functions are implemented via a special system of technical accounting. This formed a big data database of new environmental quality and quality management indicators in the regulatory structure of industrial enterprises in the EPS. Additional functions of integration, combination, and acceleration of the impact of industrial enterprise quality indicators are organized on a digital platform to predict and plan indicators of integration and combination of these resources using neural networks. Β© 2023 by the authors.
publications-5033	Article	2023	Huang N.; Li X.; Xu Q.; Chen R.; Chen H.; Chen A.	Artificial Intelligence-Based Temperature Twinning and Pre-Control for Data Center Airflow Organization	Energies	10.3390/en16166063	Green and low-carbon has become the main theme of global energy development. Data centers are the core of the digital age, carrying huge arithmetic demand. Data centers must implement green low-carbon energy efficiency management to improve energy efficiency, reduce energy waste and carbon emissions, and achieve sustainable development. As a result, an intelligent management strategy for dynamic energy efficiency of data center networks with Artificial Intelligence (AI) fitting control is proposed. Firstly, a Long Short-Term Memory (LSTM) network is used for long sequence trend prediction to predict the temperature of the data center in the next sequence using the temperature of the past 15 sequences and the power consumption of the equipment as parameters. Then, based on the prediction results, the intelligent air conditioning controller based on Deep Q-Network (DQN) is designed to update the parameters by using the gradient of double-Q network and error backpropagation, and the optimal control action is selected by using the Ξµ-greedy strategy to ensure that the prediction of the hotspot does not occur. Experiments show that the average absolute errors of temperature prediction for supply air, return air, cold aisle as well as hot aisle are 0.32 Β°C, 0.21 Β°C, 0.36 Β°C and 0.19 Β°C, respectively. The Power Usage Effectiveness (PUE) and Water Usage Effectiveness (WUE) decreased by an average of 2.6% and 2.5%, respectively. The method achieves the purpose of predicting future temperatures and intelligently controlling the output so that the data center can satisfy the premise of normal operation and thus achieve more efficient energy use. Β© 2023 by the authors.
publications-5034	Article	2023	Guo Z.; Hu S.; Jin W.; Ye Y.; Shan C.	Application of Digital Twin in the Industry of Axial Hollow-Wall Pipes	Applied Sciences (Switzerland)	10.3390/app13148093	With the increasing demand for automation in agriculture, more and more researchers are exploring the application of digital twin in agricultural production. However, existing studies have predominantly focused on enhancing resource utilization efficiency and improving irrigation control systems in agricultural production through the implementation of digital twins. Unfortunately, there is a noticeable research gap when it comes to applying digital twins specifically to buried water conveyance pipelines within an agricultural irrigation infrastructure. Focusing on the long-term performance requirements of buried pipelines in agricultural irrigation and drainage, this study established a digital twin system for the industry of axial hollow-wall pipes with an outer diameter of 200 mm, specifically designed for this field of operation. The system was used to optimize the end-forming process of axial hollow-wall pipes, resulting in improved leak tightness under internal pressure and angular deflection of the pipes. The study suggests that the most effective method for the end-forming process of axial hollow-wall pipes is to heat the pipe for 60 s at the ambient temperature of 15 Β°C, with heating temperatures of 225 Β°C on both the inner and outer sides. Additionally, preheating the stamping equipment to 70 Β°C and controlling the cooling temperature, during pipe detachment, to between 35 Β°C and 45 Β°C is recommended. In terms of the leak tightness under internal pressure and angular deviation, the study found that increasing the thickness of the protruding end of the sealing ring to 16 mm, and shortening the chamfer length to 20 mm, while maintaining the same slope, can enhance the sealing effectiveness of the pipeline interface. The implementation of the digital twin system improves the production efficiency of the hollow pipe production line during the end-forming process, resulting in a yield rate of the pipe of up to 95% for qualified products. Moreover, the system provides intelligent closed-loop feedback which ensures the long-term operation and maintenance of the pipelines, making it easier to identify problems and implement design improvements. By doing so, it contributes to ensuring the long-term stability of related agricultural production. Β© 2023 by the authors.
publications-5035	Article	2023	Liu W.; Guan G.; Tian X.; Cao Z.; Chen X.	Exploiting a Real-Time Self-Correcting Digital Twin Model for the Middle Route of the South-to-North Water Diversion Project of China	Journal of Water Resources Planning and Management	10.1061/JWRMD5.WRENG-5965	Real-time monitoring and forecasting are essential to ensure an on-time and on-demand supply of water diversion projects. However, water transfer systems currently lack spatiotemporal data in a dense resolution, failing to monitor real-time conditions and test plausible scenarios. To address the problem, this paper proposes a novel digital twin framework. It includes a real-time self-correcting model, which combines (1) a hydraulic solver using the one-dimensional Saint-Venant equations; and (2) a method updating hydraulic states driven by field observed data. This framework consists of four phases: preparation, warming up, tuning, and monitoring and predicting. Particularly in monitoring and predicting, an identification method for diagnosing abnormal events is also proposed as one of the functions of the twin model. The model shows beyond 98% similarity to reality based on the metric similarity (S) proposed in this paper on both of two real-world scenarios: a large flow scenario and a normal one. The deviation is generally lower than 5 cm for water level 2 m3/s for discharge. The abnormal situation diagnosis method also provides timely fault detection for daily scheduling. It is anticipated that this framework can be a powerful tool to estimate current canal states and predict change trends, further ensuring the security and efficiency of operations for large-scale water diversion projects. Β© 2023 American Society of Civil Engineers.
publications-5036	Article	2023	Quaranta E.; Ramos H.M.; Stein U.	Digitalisation of the European Water Sector to Foster the Green and Digital Transitions	Water (Switzerland)	10.3390/w15152785	During the Digital Decade, the European Union (EU) is facing two important challenges: the green (and energy) transition and the digital transition, which are interconnected with one another. These transitions are of high relevance in several aspects of our life, e.g., in the industry, energy sector, transports, environmental management and our daily life. Digital technologies are particularly emerging also as multi-benefit solution in the water sector, as water is becoming more and more vulnerable to climate change (e.g., droughts and floods) and human activities (e.g., pollution and depletion). Within this context, in this study we assessed some of the several economic benefits that digital solutions can bring to the water sector, with a focus on leakage reduction in water distribution networks, reduction of combined sewer overflows and improvement of hydropower generation and operation. The benefits are calculated for each EU Member State and the UK, and then aggregated at the EU scale. Benefits were quantified in EUR 5.0, 0.14 and 1.7 billion per year (EUR 13.2 per person per year, on average), respectively, excluding environmental and social benefits, which may play a non-negligible role. Β© 2023 by the authors.
publications-5037	Review	2023	Berglund E.Z.; Shafiee M.E.; Xing L.; Wen J.	Digital Twins for Water Distribution Systems	Journal of Water Resources Planning and Management	10.1061/JWRMD5.WRENG-5786	Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal. Β© 2023 American Society of Civil Engineers.
publications-5038	Article	2023	Deng F.; Si Q.; Li F.; Wang P.; Yang H.; Yuan S.	Review On Water Carrying Equipment For Emergency Water Supply Systems In Mountain And Remote Disaster Areas; [ε±±ε_x008c_Ίε’_x008c_θΎΉθΏ_x009c_ηΎε_x008c_ΊεΊ”ζ€¥δΎ›ζ°΄η³»η»_x009f_ζ_x008f_ζ°΄θ£…ε¤‡ε_x008f_‘ε±•η_x008e_°η_x008a_¶]	Paiguan Jixie Gongcheng Xuebao/Journal of Drainage and Irrigation Machinery Engineering	10.3969/j.issn.1674-8530.22.0251	In order to improve the capacity of water supply in mountain and remote disaster areas in China, the development process of the equipment in the "water carrying" was discussed. The current water supply system and the main working principles of emergency equipment were introduced. The development status of specific rescue equipment such as feed pump, vehicle system and secondary pressure pump station was presented. The emergency water lifting equipment involves many pump products. The performance gap is gradually narrowed with foreign countries. Although the products have high-cost performance and various models for choice, the quality and reliability need to be improved due to the limited range of processing and manufacturing accuracy and material selection. Vehicle platform constantly improves the fatigue strength, reliability, and lightweight frame. However, it is limited by various parts with complex layout. It is also lack of the whole machine optimization. The mounting system has changed from a single objective optimization to multi-objective optimization based on computer calculation, which has greatly improved the riding experience and the vibration of the carriage. Pipeline water hammer and pipeline leak monitoring rely on the more robust algorithm and higher precision. What's more, digital twin is the trend of emergency water pipe network control, relying on the Internet of Things, 5G, big data and cloud computing, etc. From basic data to digital simulation, and then to scheduling command and decision support, it will realize change of the automation, informatization and the digital to the wisdom, which will greatly improve the efficiency of emergency rescue. Β© 2023 Editorial Department of Journal of Drainage and Irrigation Machinery Engineering. All rights reserved.
publications-5039	Article	2023	Isah A.; Shin H.; Oh S.; Oh S.; Aliyu I.; Um T.-W.; Kim J.	Digital Twins Temporal Dependencies-Based on Time Series Using Multivariate Long Short-Term Memory	Electronics (Switzerland)	10.3390/electronics12194187	Digital Twins, which are virtual representations of physical systems mirroring their behavior, enable real-time monitoring, analysis, and optimization. Understanding and identifying the temporal dependencies included in the multivariate time series data that characterize the behavior of the system are crucial for improving the effectiveness of Digital Twins. Long Short-Term Memory (LSTM) networks have been used to represent complex temporal dependencies and identify long-term links in the Industrial Internet of Things (IIoT). This paper proposed a Digital Twin temporal dependency technique using LSTM to capture the long-term dependencies in IIoT time series data, estimate the lag between the input and intended output, and handle missing data. Autocorrelation analysis showed the lagged links between variables, aiding in the discovery of temporal dependencies. The system evaluated the LSTM model by providing it with a set of previous observations and asking it to forecast the value at future time steps. We conducted a comparison between our model and six baseline models, utilizing both the Smart Water Treatment (SWaT) and Building Automation Transaction (BATADAL) datasets. Our modelβ€™s effectiveness in capturing temporal dependencies was assessed through the analysis of the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF). The results of our experiments demonstrate that our enhanced model achieved a better long-term prediction performance. Β© 2023 by the authors.
publications-5040	Article	2023	Tasmurzayev N.; Amangeldy B.; Nurakhov Y.; Shinassylov S.; Bekele S.D.	Development of an Intelligent Oil Field Management System based on Digital Twin and Machine Learning	WSEAS Transactions on Electronics	10.37394/232017.2023.14.12	This article introduces an innovative approach to oil field management using digital twin technology and machine learning. A detailed experimental setup was designed using oil displacement techniques, equipped with sensors, actuators, flow meters, and solenoid valves. The experiments focused on displacing oil using water, polymer, and oil, from which valuable data was gathered. This data was pivotal in crafting a digital twin model of the oil field. Utilizing the digital twin, ML algorithms were trained to predict oil production rates, detect potential equipment malfunctions, and prevent operational issues. Our findings highlight a notable 10-15% improvement in oil production efficiency, underscoring the transformative potential of merging DT and ML in the petroleum industry. Β© 2023 World Scientific and Engineering Academy and Society. All rights reserved.