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-5261 Conference paper 2022 Silva R.G.; AraΓΊjo A. Framework for the Development of a Digital Twin for Solar Water Heating Systems 2022 International Conference on Control, Automation and Diagnosis, ICCAD 2022 10.1109/ICCAD55197.2022.9853899 Energy efficiency in buildings is a key issue in the context of smart cities and should embrace a more intensive use of renewable energies. As such, many European countries are now promoting the use of solar energy for hot water production, giving financial incentives and introducing mandatory building regulations. It is proposed a framework for the development of a digital twin-based management system for a solar heating system. This is a concept framework and thus no results are yet available. The proposed framework takes advantage of the latest technologies, machine learning, IoT, experience-based information interchange between the physical system and the digital twin to achieve energy efficiency optimization. This novel approach integrates connectionist models and optimization techniques, bringing together complementary reasoning strategies for efficient energy use in real-time. This framework contributes to a better understanding of the effectiveness of digital twins on the automation of energy-dependent systems and explores new dimensions concerning the integration of autonomous intelligent management systems into physical systems. Β© 2022 IEEE.
publications-5262 Conference paper 2022 Yingxin W.; Xintong H.; Jiangang M. A digital twin-driven water plant flocculation and precipitation pharmacy control system 2022 IEEE International Conference on Artificial Intelligence and Computer Applications, ICAICA 2022 10.1109/ICAICA54878.2022.9844466 As an indispensable part of production and life, tap water has a large scale of consumption every year. Among them, coagulation drug injection is an important link in purifying water quality in the production process of tap water treatment. At present, the drug injection mode of domestic water purification plants is mainly feedforward control or single-factor closed-loop control based on flow current. The parameter response to multiple parameters cannot be responded quickly, which limits the control effect and causes the problem of flocculant drug waste. Therefore, in view of the above problems, the project has built an intelligent control system of waterworks flocculant drugs based on big data by comprehensively using big data, digital twin, Internet of Things and deep learning, so as to realize the precise dosage of flocculant. Β© 2022 IEEE.
publications-5263 Conference paper 2022 Karatvuo H.; Linde M.; Dolatshah A.; Mortensen S. IMPROVED CLIMATE CHANGE ADAPTATION in PORT of BRISBANE USING A DIGITAL TWIN CLOUD-BASED MODELLING APPROACH Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE 10.1115/OMAE2022-79613 Due to their low-lying coastal location, ports are vulnerable to climate change induced increases to flooding, waves, extreme winds, and the associated costly damages to port infrastructure and operational disruptions. For these reasons, there is an increasing need for ports to undertake regular risk assessments of the vulnerability of their infrastructure and operations due to the impacts of climate change. A digital twin, cloud-based climate change modelling solution has been developed to enable in-house risk assessments of climate change vulnerability to be undertaken for any port. Once set-up, the system supports the continued sustainable operation of ports and enhancing stakeholder confidence in corporate sustainability strategies by allowing in-house reevaluation of the ports climate risk as new predictions are released. The basis of the digital twin model of the port are numerical wave and hydrodynamic models, configured with the actual port geography and bathymetry enabling highly detailed simulations of the ports physical environment. The numerical model simulations are supplemented with observations of wind, rainfall, and sea level to identify trends and extreme event probabilities under the historic climate conditions. Scenarios describing the predicted impacts of climate change can be superimposed on the historical climate via a web-based interface where the user (port) selects a planning horizon (e.g., 2050), storm event frequency (e.g., 100-year storm), and climate change predictions (e.g. RCP8.5). The resulting climate change simulations shows great potential to enable port-specific predictions of future impacts of extreme occurrences of wind, waves, water levels, and currents. The ports asset portfolio is incorporated in the risk assessment through dynamic GIS layouts and damage curves identifying the damage cause and cost for each vulnerable port asset. As new climate science becomes available, this cloud-based digital twin model enables ports to rapidly complete updated risk assessments and respond to stakeholder queries and concerns. The capability of the tool was validated by comparing the model results against a large conventional study of the region, and a historical flood event of 2011. Both validation exercises displayed a reasonable agreement increasing confidence in the model's capacity as a predictive tool. Additionally, six climate change scenarios were modelled for one of Australia's fastest growing container ports, Port of Brisbane and the results were successfully incorporated in the ports overall sustainability strategy. Β© 2022 by ASME.
publications-5264 Conference paper 2022 Medagoda L.; Galea M.; Bargoti S.; Khan J.; Dunne T.; Potiris S.; Ul Abidin Z.; Anwar I.; Jolly J.; Windrim L.; Charolia F. Scalable Port Inspections Through Underwater, Terrestrial and Aerial Robotic Platforms Society of Petroleum Engineers - ADIPEC 2022 10.2118/210999-MS Asset management of a marine port or terminal requires inspection of the asset components below the water surface, at the water surface line and above the water surface. In order to determine asset health, high fidelity, multi-modal data is captured remotely using robotics, and subsequently analyzed. This facilitates the production of prioritized actionable insights to be produced. These insights can be scheduled as maintenance works. This paper outlines a novel multimodal inspection system that was deployed at a port to facilitate its remote inspection. Two inspections are detailed in this paper, with differing inspection requirements and constraints. The inspection operation can be broken down into multiple components, an underwater scan of the port, a water-surface scan, a ground level scan and an aerial scan. The Port Asset required the inspection of the wharf and quay walls. The Marine Terminal Asset required inspection of the complex pipework. The data collected from the different modalities were represented in the 3D space. The alignment of the different modalities could then be done in this representation. For the Port Asset, where multibeam sonar maps were collected, the difficulty in alignment of the different modalities is apparent due to no shared points below and under-water, which requires estimation using extended features as landmarks. There also exists slight warping between the data that must need localized scaling for certain sections, which may be done using local submaps and scaling. For the Marine Terminal Asset, artificial markers are used to allow scaling of the drone captured photogrammetry. High levels of coverage from the multiple views of the asset from different data collection strategies allowed the complex pipework to be well mapped, with further insights from the co-registered imagery. The novel information described in this paper is the unique combination of different modalities for a broadscale port inspection, with point clouds from sonar, lidar, photogrammetry and imagery, in a combined reference frame which acts as a digital twin for the port. This also allows unique insights, such as the exact context and magnitude of faults in the port environment, to allow corrective works to be targeted correctly. Copyright Β© 2022, Society of Petroleum Engineers.
publications-5265 Conference paper 2022 Zhang H.; Lu Y.; Zhang J.; Benigni A. Real-Time Simulation of an Electrolyzer with a Diode Rectifier and a Three-Phase Interleaved Buck Converter 2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022 10.1109/PEDG54999.2022.9923192 In this work, we implement an electrical equivalent model of a water electrolyzer in a real-time simulation environment. To power the electrolyzer, a chopper-rectifier with passive filter (CRPF) and a 3-phase interleaved buck converter (IBC) are implemented. We further analyze the performance of the electrolyzer when it is used for primary frequency control. At the end, we integrate the electrolyzer model into our campus digital twin to evaluate its real-time simulation compatibility and performance. The simulations are executed on an OPAL-RT real-time simulator. Β© 2022 IEEE.
publications-5266 Book chapter 2022 Harrison S.M.; Cohen R.C.Z.; Cleary P.W. Whole-body movement modeling in realistic environments for understanding performance and injury Digital Human Modeling and Medicine: The Digital Twin 10.1016/B978-0-12-823913-1.00021-X The body interacts mechanically with its environment every time we walk, run, participate in sport, or perform work activities. These interactions may include reaction forces between the ground and our feet, downwards acceleration due to gravity and drag forces from water - such as during swimming. An improved understanding of the relationship between body movement and external body forces can provide insight into the internal forces and torques experienced during activity. These can assist in determining strategies for reducing injury risk and improving performance outcomes. Experimental approaches have been typically limited to the laboratory and to external measurements, except when invasive procedures have been used. They have been limited in application to relatively small datasets due to the number of manual tasks required to capture and process data. However, recent advances in the areas of computer vision and biomechanics have enabled the development of fully non-invasive and continuous systems for measuring body motion. This enables advanced calculation of transient body loading using simulation in internal distribution of these loads. These types of information are then used to identify opportunities for improving work, sports or general health outcomes. Here we describe an analysis and simulation pipeline that comprises such markerless motion capture, biomechanical modelling of the body, and coupled particle-based modelling of the environment. Example applications are described, including elite swimming, diving, skiing and an example of manual handling in occupational injury scenarios. The design of software products based upon the workflow pipeline (implemented in the Workspace platform) is also discussed. Future challenges and extensions are explored. Β© 2023 Elsevier Inc. All rights reserved.
publications-5267 Conference paper 2022 Wong J.; Hoong P.; Teo E.; Lin A. Digital Twin: A Conceptualization of the Task-Technology Fit for Individual Users in the Building Maintenance Sector IOP Conference Series: Earth and Environmental Science 10.1088/1755-1315/1101/9/092041 There have been numerous research studies on understanding buildings better and finding ways to improve water and energy consumption while making them more comfortable for occupants. With technologies such as Building Automation Systems, IoT devices, mobile applications and BIM software, more data can be generated and stored for intelligence and more effective facility management. The next big thing is the digital twin concept, where a virtual model is created from the physical building that brings together real-time information from all data capture devices, allows monitoring, historical analysis, predictive analytics, and simulation as well as interaction and intervention to be carried out. Many research studies have covered the characteristics, architecture, and benefits of digital twins and examined the potential implementation issues. However, the literature on evaluating return on investment (ROI) and acceptance of digital twins for the built environment at the individual user level is limited. This study aims to develop a conceptual model to examine the motivational intent and behavioural choice by individual users to utilise the digital twin technology to improve their performance. The objectives of this study are to examine technology acceptance theories and develop a conceptual model that measures the relationship between the tasks involved and the digital twin technology characteristics. Β© Published under licence by IOP Publishing Ltd.
publications-5268 Conference paper 2022 Zhang W.; Zhu P.; Wang J.; Ling H.; Cheng J.; Shi J.; Wu Y.; Xu Y.; Chen H.; Liu S.; Peng S. Research on the New Operation Mode of Digital Twin Farm System Proceedings of SPIE - The International Society for Optical Engineering 10.1117/12.2658662 Nowadays, China's agricultural development has entered a new stage of transformation from traditional agriculture to high-standard farmland construction. The development of intelligent, high-standard and water-saving agriculture has become the development direction of modern agriculture. However, although my country’s agricultural sector has achieved a certain degree of mechanization, there are still pain points that are not water-saving, unintelligent, and non-interactive. It is urgent to strengthen the promotion and application of today’s advanced technologies in the agricultural field to achieve refined agricultural production management. To achieve the purpose of rational use of agricultural resources, reducing production costs, improving the ecological environment, and improving the quality and quality of agricultural products. Taking wheat planting as an example, this article focuses on the construction of digital twin farms. First, establish a health monitoring infnsor networks to collect farmland information and facilities operation. The rapid identification of the water; combined with meteorological and soil moisture data, the use of deep learning algorithms to build an information processing system based on multi-source data fusion, build a wheat digital twin information model, and carry out irrigation risk prediction; finally apply irrigation strategies on the wheat entity, The information model of wheat and the physical model are interacted, and the purpose of intelligent water-saving irrigation can be realized through multi-mode irrigation and fertilization control. © 2022 SPIE.
publications-5269 Conference paper 2022 Kruger K.; Human C.; Basson A. Towards the Integration of Digital Twins and Service-Oriented Architectures Studies in Computational Intelligence 10.1007/978-3-030-99108-1_10 Digital twins and service-orientated architectures have developed in different research communities, but share some similar target uses. This paper proposes a general architecture that connects aggregations of digital twins with a services network to create digital decision support systems for complex cyber-physical systems. The proposed architecture is intended for complex cyber-physical systems, allows multiple stakeholders to contribute to the development and operation of the system. The architecture provides the ability for the digital system to evolve over time as the physical system evolves and to adapt the functionality of the digital system to information needs and resources change over time. The architecture is expected to be applicable to manufacturing scenarios ranging from SMEs to larger enterprises, and also to areas such as management of complex facilities (such as a university campus), water distribution systems and railway infrastructure. Some challenges associated with the proposed architecture, related to the integration of digital twin and service-oriented architectures, are outlined in the paper. Β© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
publications-5270 Article 2022 Zhou D.; Gao H.; Wang W.; Cao J.; Yang W.; Zeng R.; He Y. Application of Three-Flow Fusion Technology Based on Modelica in Thermal Power Digital Twin IEEE Journal of Radio Frequency Identification 10.1109/JRFID.2022.3205855 Thermal power plants gather large energy infrastructure; therefore, massive historical and real-time data of equipment operation will be generated in daily operation. Digital industrialization puts forward higher requirements for the use of big data than simple tasks, such as generating reports. MWorks is a multidomain unified modeling and simulation platform based on the Modelica language. In this study, MWorks is used to realize the modeling of multidomain systems, including electrical, thermal, mechanical, fluid, and heat transfer, in power plants. The test, calibration, verification, parameter optimization, and fault diagnosis of the thermal power plant mathematical models, which are historical and real-time data-driven, are discussed. The technology of three-flow fusion, including material flow, energy flow, and information flow, and its application in thermal power digital twin are explored. Β© 2017 IEEE.