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-5101 Conference paper 2023 Gall V.; Martin T.; Boyd L. A novel holistic approach to rehabilitation of underground structures Expanding Underground - Knowledge and Passion to Make a Positive Impact on the World- Proceedings of the ITA-AITES World Tunnel Congress, WTC 2023 10.1201/9781003348030-321 Water infiltration into subgrade infrastructure can cause major impacts on their performance. In addition to damaging the structure, water intrusion leads to deterioration of installations including electrical and mechanical components and in patron discomfort. To remedy these impacts, leak remediation is often carried out to halt water infiltration. Remediation methods include coatings, drainage, injection/stitch grouting, curtain (backside) grouting, and/or internal umbrella systems. Selection of the rehabilitation method depends on the structure’s use, owners’ priorities, its installations, structural conditions, surrounding ground, and hydrogeologic conditions. Since many factors influence the rehabilitation method chosen, a novel holistic approach is undertaken to understand leakage causes and consequences to develop the most appropriate, efficient, and reliable solution to extend the structure’s life. A reconnaissance phase combines geologic, hydrogeologic, and as-built information with detailed digital scans and visual observations to develop a database of existing conditions. This database, called a tunnelband, is used to develop the rehabilitation solution and made part of the contract documents, allowing for an informed bid by specialty contractors. Tunnelband and the preferred rehabilitation system are portrayed in contract documents, which are procured in various contract types depending on the owner’s preference and project characteristics. The pool of contractors are required to submit their understanding of this holistic approach by developing and supplying the owner with a detailed workplan. The completed rehabilitation is portrayed in detailed as-built drawings which also provide the owner with an operation and maintenance manual outlining for periodic observation of the structure and checking of its performance. Ultimately, this information is implemented into a β€_x009c_BIM Digital Twinβ€_x009d_ that is used by the operations and maintenance staff for long-term observations. This proposed novel framework for leak rehabilitation is currently being used successfully in a number of projects throughout the United States. Β© 2023 The Author(s).
publications-5102 Article 2023 Guo X.; Li Y.; Chang T.; Cao G.; Ma R.; Yanjiaming Construction thought and implementation pathway of β€_x009c_jingchu’anlanβ€_x009d_ modern water network Water Resources Protection 10.3880/j.issn.1004-6933.2023.03.001 The construction basis of β€_x009c_Jingchu’anlanβ€_x009d_ modern water network is analyzed from two aspects of natural river and lake water system and artificial water conservancy facilities. The significance of β€_x009c_Jingchu’anlanβ€_x009d_ modern water network construction was analyzed from multiple perspectives. The construction ideas, target positioning and overall layout of β€_x009c_Jingchu’anlanβ€_x009d_ modern water network were elaborated in details. It was proposed to promote the coordinated integration of Hubei water network between the three major functions of water network, with different industries, between different levels of water networks and with adjacent water networks. The main tasks, major projects and actions of β€_x009c_Jingchu’anlanβ€_x009d_ modern water network construction were also introduced detailed. It will provide a solid water security guarantee for the high-quality development of Hubei Province replying on building a modern water network. Β© 2023, Editorial Board of Water Resources Protection. All rights reserved.
publications-5103 Conference paper 2023 Posio J.; Maljamäki P.; Haavikko M.; Tepsa T.; Väätäjä H. EXPERIENCES AND LEARNING OUTCOMES OF USING VIRTUAL REALITY IN BUILDING SERVICES ENGINEERING EDUCATION SEFI 2023 - 51st Annual Conference of the European Society for Engineering Education: Engineering Education for Sustainability, Proceedings 10.21427/KCVD-PH95 Virtual Reality (VR) is a promising learning environment in vocational and higher education as it enables learning by doing. We developed a digital twin (DT) for learning the most common maintenance procedures of an air-to-water heat pump using game engine technology, targeted for students and professionals in the building services engineering industry. 22 HVAC (heating, ventilation and air conditioning) students participated in a user study to evaluate their experience with the DT, their usage preferences, and learning outcomes. Results of an online post-test questionnaire show that participants found the use of the DT easy and useful for learning maintenance procedures, regardless of their previous experience with VR devices or video gaming. More than half of the participants reported preferring to use the DT before practicing with the physical device. Learning outcomes measured with eight questions indicate that most of the students learned the tasks and safety issues correctly and in correct order (72-95% answered correctly). However, the questions measuring the learning related to adjusting the pressure was challenging for almost all students. The functional and task correspondence as well as the visual similarity of the digital twin to the real-world context is important for learning outcomes. The reported perceived usefulness by students for using VR in learning the maintenance procedures was related to realism of working with the digital twin, illustrating the maintenance procedures and tasks, as well as safety issues in the learning phase. The transfer of learning to real maintenance situations could be tested on the physical device. © 2023 SEFI 2023 - 51st Annual Conference of the European Society for Engineering Education: Engineering Education for Sustainability, Proceedings. All Rights Reserved.
publications-5104 Conference paper 2023 Zhao X.; Dao M.H.; Le Q.T. TOWARD ENVIRONMENTAL AND STRUCTURAL DIGITAL TWIN OF OFFSHORE WIND TURBINE Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE 10.1115/OMAE2023-101859 In the wind energy industry, a digital twin (DT) is very useful for managing the operation of a wind turbine and predicting structural health conditions in real-time as well as projections in the near future. A real-time surrogate model is a very crucial part in building a DT. Towards that end, we employ a Reduced-Order Modelling (ROM) approach to construct a surrogate model for the environment-structure system of a bottom-fixed offshore wind turbine (OWT). The entire environment-structure system is broken down into major sub-systems of wind, wave, and structure. Based on the high-fidelity Computational Fluid Dynamics (CFD) data, the wind ROM model can quickly provide the loadings on the components above water level in the parameter space spanned by the incoming wind speed, the rotational speed of the rotor, the pitch and tilt angles of the turbine. The hydro loadings on the underwater components of the OWT are solved by the empirical Morison formula. The OWT structural ROM model is component-based consisting of blades, hub, nacelle, tower, and monopile. The structural ROM model takes the loading data feeds from the wind and wave models to predict the structure responses of the OWT system, including stress. Since the DT is constructed via the component-based, it can also be used to play out β€_x009c_what ifβ€_x009d_ scenarios when there are component level changes. For instance, the model can predict the system response of OWT when certain parts undergo structure failures. Benefiting from the cost-efficient ROM models, the DT is over two orders of magnitude faster than high-fidelity simulations while maintaining good accuracy. Copyright Β© 2023 by ASME.
publications-5105 Conference paper 2023 Jiang H.; He Z.; Liu S.; Hai Y.; Liu C.; Miao S. Intelligent Sewage Treatment Control System Based on Digital Twin Lecture Notes in Electrical Engineering 10.1007/978-981-99-1252-0_63 With the development of economy, people pay more and more attention to urban sewage treatment. At present, the operation and management of sewage treatment plants are gradually changing from digital to intelligent. As an emerging technology, digital twin can make an important contribution to the development of intelligent water. Based on digital twin, machine learning, Internet of Things, and other technologies, this study constructed a smart control system applied to sewage treatment plants. Water quality information such as COD, TN, and TP collected on site is driven into the 3D model of the system. At the same time, based on the historical data, the effluent quality is predicted. Assist staff in dosing and equipment maintenance according to forecast results. Preliminary experimental results show that the system realizes the data-driven 3D model, completes the data prediction and remote interaction, and runs stably. It can save a lot of manpower and material resources and has feasibility. Β© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
publications-5106 Conference paper 2023 Borges S.; Jöhnk L.; Klebig T.; Vering C.; Müller D. Fault Detection and Diagnosis by Machine Learning Methods in Air-to-Water Heat Pumps: Evaluation of Evaporator Fouling 36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, ECOS 2023 10.52202/069564-0074 Heat pumps have emerged as key technology to pave the way for a sustainable heat supply in buildings. However, the ongoing shortage of trained experts counteracts the current heat pump trend. Increasing the capacity of experts, services like Fault Detection and Diagnosis (FDD) can support the identification of malfunctions and integration of methods for predictive maintenance. The primary objective of FDD is to detect faults, diagnose their causes, and possibly enable correction to prevent efficiency losses as well as system damage or downtime. This involves a comparison between a fault-free reference case and the real system. In research, machine-learning methods like Artificial Neural Networks (ANN) show the capability to learn the behavior of fault-free systems. In practice, however, the implementation of ANN is limited due to missing data in operation for training. Therefore, it is common to utilize physically simulated data for pre-training. One way to achieve high efficiency in heat pumps is to maximize heat transfer in the evaporator. Fouling within this component therefore leads to significant performance degradation and reduced system lifespan. As a result, this work introduces and evaluates an extendable FDD method for evaporator fouling in air-to-water heat pumps. To detect evaporator fouling during operation using an ANN, a transient model of a refrigerant cycle provides the training data. Based on literature, the fouling effect is emulated afterwards, serving the data for the reference system considering faulty operation. Applying the present concept, we reveal a reduction in COP due to evaporator fouling of approximately 3 % over a whole year, while our fault detection methodology detects 55.65 % of the faults within the given heat pump model. Overall, this study provides insights into the performance of FDD methods for evaporator fouling in air-to-water heat pumps, which can help to improve the efficiency and reliability within the system lifespan. The results of this study demonstrate that the concept of FDD offers the potential to be applied in practice, and proposes recommendations for future perspectives about ANN within FDD in heat pump systems. © (2023) by ECOS 2023 All rights reserved.
publications-5107 Conference paper 2023 Blachnik M.; Ε_x009a_ciegienka P.; DaΜ§browski D. Preliminary Study onΒ Unexploded Ordnance Classification inΒ Underwater Environment Based onΒ theΒ Raw Magnetometry Data Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 10.1007/978-3-031-48232-8_40 Unexploded ordnance (UXO) dumped in water reservoirs pose a serious environmental and human safety hazard. Various ways of economically solving this problem are being sought. One of them is the use of machine learning methods for the automatic classification of dangerous objects based on the recorded signals. The paper presents the preliminary results on the use of machine learning methods applied to raw magnetometry data generated in a virtual environment based on the concept of a digital twin. This introduces a different approach to a standard approach, which is based on the inverse problem, where the signals are mapped to the magnetic dipole model. Conducted research points out that the highest performance can be obtained with neural networks, and a direct classification based on the raw signals allows to achieve accuracy of up to 93% when no remanent magnetization is present. Β© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
publications-5108 Conference paper 2023 Balachandran P.A.; Padmanabhan K.V.K. Integrated Operations System: Implementation of a Truly Integrated Digital Oil Field and Development of Digital Twin Offshore Technology Conference Brasil, OTCB 2023 10.4043/32841-MS The global oil and gas companies are aggressively adopting new digital technologies for process improvement, enhancing safety, reducing asset down time, and reducing overall cost of production to stay competitive. The Digital Oil Field (DOF) is the idea of digitalizing the oil field operations to improve production performance and collaboration both within and outside the organization. This paper discusses the giant leap taken by ONGC towards digitalization of one of its largest deep-water oil and gas field development – the KG-DWN-98/2. Integrated Operations System (IOPS) presently being implemented in ONGC, comprises of data collection and analytics modules, automation tools and collaboration enablers integrated together for streamlined decision-making, easily accessible expertise and safe collaborative co-location of essential personnel. Paper discusses the existing challenges being faced by ONGC in production optimization, asset maintenance and collaboration. IOPS system is proposed as a solution to overcome these challenges. With the help of IOPS, the concept of "Digital-Twin" is introduced in ONGC. The method of developing a digital twin for the entire field from reservoir to separator using existing industry proven software with limited customization are discussed in detail. The methodology adopted for acquiring field data, analysis of the acquired data and utilizing the business intelligence acquired for optimizing production and ultimately leading to business transformation is discussed. The use of advanced digital collaboration environments to effectively utilize the technical expertise located at various geographical locations to solve complex technical issues and provide quick resolution to business problems are discussed in detail. The usage of Big data for predictive analytics to move the decision making from a post event reactive approach to proactive responsive approach is briefly discussed. The functioning of different components of the IOPS system, the interconnection between various analytics modules, the flow of data between modules to form a digital twin of the field and the expected benefits of the system are discussed in detail. The system is expected to improve production uplift by 2 to 3% and reduce the overall OPEX cost by 10 to 20%. The system is expected to increase the Mean Time Between Failures (MTBF) and Mean Time to Repair (MTTR) of the critical assets by enabling Reliability Centered Maintenance (RCM). © Copyright 2023, Offshore Technology Conference.
publications-5109 Conference paper 2023 Fukuda T.; Yoshikawa S.; Hosono K.; Iwanaga S. Development of a ground forecasting system based on the geological and groundwater conditions in mountain tunneling Expanding Underground - Knowledge and Passion to Make a Positive Impact on the World- Proceedings of the ITA-AITES World Tunnel Congress, WTC 2023 10.1201/9781003348030-320 In recent years, with the development of IoT and ICT technologies, an environment has been created in which digital data related to construction can be easily obtained. In this paper, we have developed a system based on the concept of digital twin, which integrates digital data and numerical simulation technology. First, the system reproduces in a virtual space the β€_x009c_water inflow rate at the faceβ€_x009d_ and β€_x009c_results of the geological survey at the time of construc-tion,β€_x009d_ which are acquired during tunnel excavation. Next, the system updates this information on time. Finally, the system uses numerical simulations to constantly predict signs (water inflow and geological changes) that will occur in the near future. The information predicted by this system can be disseminated on time in a form that can be easily understood by anyone. Therefore, this system is a technology that can contribute to safe and secure construction. Β© 2023 The Author(s).
publications-5110 Conference paper 2023 Wang C.; Yang X.; Zhang L.; Hu Y.; Li H.; Hao H.; Wang Z. Robot Path Verification Method for Automotive Glue-Coating Based on Augmented Reality and Digital Twin Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 10.1007/978-3-031-35602-5_19 The automotive glue-coating, as an important part of automobile manufacturing, has a crucial impact on automotive water-proof and rust-proof performances. The glue-coating robots need to be path planned with software, and the paths have to be repeatedly tested with the actual production line using prototype vehicles. There are multiple issues concerning nozzle damage and inefficiency by using the traditional glue-coating path verification method, which calls for a new method to solve these problems. This paper proposes a path verification method for automotive glue-coating based on augmented reality and digital twin. The results show that with this augmented reality and digital twin based method, the operator can observe the glue-coating process intuitively and immersively, so that he can adjust or re-plan the glue-coating path according to the verification results, even before the production of the actual prototype vehicle. The collision between the actual prototype vehicle and the nozzle of the glue-coating robot will be transformed into the collision between the virtual vehicle model and the robot digital twin, which can avoid nozzle damage, save a lot of time for waiting for the production of the prototype vehicle. This method is in line with the general trend of smart manufacturing development and effectively shortens the manufacturing cycle time. Β© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.