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-5141 Conference paper 2023 Kang Y.; Ling A.; Liang Y.; Jin X. Research on Jacket Digital Twin Prediction Technology Based on LSTM 2023 IEEE International Conference on Image Processing and Computer Applications, ICIPCA 2023 10.1109/ICIPCA59209.2023.10257887 In this paper a prediction technique for deep-water jacket digital twin model based on long short term memory network (LSTM) is proposed. By studying the long and short memory network technology, the random effect of environmental parameters was studied. Combined with the environmental parameters of the area where the jacket is located and operating time database of the jacket, the digital twin model of the jacket structure is predicted. Realize the synchronization and real-time update of the digital twin physical model of the jacket. It obtain more accurate jacket structure prediction results. Compared with the simulation model database, the jacket digital twin prediction model base on LSTM technology has higher accuracy and saves training time of the model. Β© 2023 IEEE.
publications-5142 Conference paper 2023 Spasova T.; Avetisyan D. A synchronized Remote sensing monitoring approach in the Livingstone island region of Antarctica Proceedings of SPIE - The International Society for Optical Engineering 10.1117/12.2682162 Data-driven innovations bring significant benefits to societies directly affected by global warming, as they underpin Global and European climate change policy. The application of a synchronous approach and interoperability of data from different sources for environmental monitoring in one of the most vulnerable to climate change regions in the World is the aim of this research. The research was conducted at Hannah Point peninsula, near the Bulgarian Antarctic base "St. Kliment Ohridski"on Livingstone Island, South Shetland Islands, Antarctica. The study area has high ecological importance for tracking the dynamics of processes not only on a local but also on a global scale. Various research sites with different groups of objects serving as environmental benchmarks were selected to be studied. The study objects include snow cover, wet snow, water, ice (including sea ice), herbaceous vegetation, lichens, mosses, soils, and sand. For each of the objects, ground GPS points were defined and in situ spectrometric measurements were performed. Data from an innovative automatic recording weather station (AWG), as well as various indicators and indices based on the spectral reflectance characteristics of the investigated objects in the optical and microwave range, were used. For their generation were used satellite images from Sentinel-1 and Sentinel-2 sensors of European Space Agency. Multiple optical indices were used to demonstrate the changes in the state of the objects for the summer season of 2022-2023. The data obtained and models used will serve the Bulgarian initiative for the construction of the Digital Twins, which is being on pilot developed in the Department of Aerospace Information (SRTI-BAS) and could be used by a wide range of scientists in the field of polar research as well as for climate change education. Open Data were used in this study, to promote the Open science policy and FAIR principles as much as possible. Β© 2023 SPIE.
publications-5143 Conference paper 2023 Sindi W. Developing a Digital Twin for Offshore Wells using Physics-Rooted Models Proceedings of the Annual Offshore Technology Conference 10.4043/32635-MS Accurate understanding of the physics of the wellbore and knowledge of production rates are essential as they serve as a key input to modelling and therefore affect results and the decisions made based on those. This paper presents a methodology to create a physical representation of the wellbore and to compute production rates from monitoring parameters utilizing physics-rooted models. When connected to real-time measurements, the process enables continuous production surveillance and integration into a digital oilfield solution. The approach is validated against data from literature and a real North Sea offshore field. This work consists of an integrated methodology using a mechanistic approach to replicate the physics of the wellbore. The process utilizes transient heat transfer calculation between a deviated wellbore and formation. Black oil models are used to determine the properties of the produced fluids, which may comprise mixtures of gas/oil/water. Basic fluid properties and static information including wellbore design are required for the initial model setup. The dynamic input comprises choke downstream pressure, choke valve setting, pressure and temperature at wellhead and downhole. Dynamic data may come from either SCADA (supervisory control and data acquisition) for near real-time calculation, or manual readings. The methodology is validated with two quality data points from various fields used by other authors such as (Hasan & Kabir, Fluid Flow and Heat Transfer in Wellbores, 2002), including an onshore and an offshore well. Moreover, the process is also tested against the publicly available historical dataset of the Norwegian offshore field Volve, which was in production from 2008 to 2016. This allows simulation of daily production rates throughout entire well life cycles. The simulation of the real field cases achieves an average error MAPE (mean absolute percentage error) of 11.75 % for the liquid rate. The novelty of this approach is the ability to run a digital twin of a wellbore based on data that is already acquired as part of standard well monitoring operations. production allocation and quality control (QC) physical MPFM (multiphase flowmeter). Having such a model-based approach offers significant potential for cost savings, for instance reducing OPEX (operating expenditure) by stretching physical metering cycles and lowering CAPEX (capital expenditures) by saving metering infrastructure. Β© 2023, Offshore Technology Conference.
publications-5144 Conference paper 2023 Melancon C.; Kaur K.; Gascon-Samson J.; Saad M. Towards Smart Distributed Robotics Solution using Digital Twin Proceedings of the International Conference on Power Electronics and Drive Systems 10.1109/PEDS57185.2023.10246745 The global COVID-19 pandemic has put a strain on the healthcare system, further compounded by the aging population and the staffing shortage. As a result, the demand for healthcare exceeds the available offer, and health professionals are forced to compensate the best they can. On the other hand, some tasks can easily be offloaded to robots. Some solutions already exist, but they are not necessarily scalable, and exhibit a very high price point. This paper outlines our vision of a new distributed robotics approach to mitigate these constraints. We propose a prototype of an autonomous robot to assist healthcare professionals (e.g., nurses) in their work - for instance, by gathering equipment and delivering water and food to give them more time for human-centric tasks. The solution incorporates the ideas of cloud-fog-edge robotics to enable AI-based control with digital twin notions to help with the training. Preliminary work is introduced on the robot platform and the framework to facilitate communication at every infrastructure layer. Β© 2023 IEEE.
publications-5145 Conference paper 2023 Dean C.; Norton J., Jr.; Bell G.E.C. Development and Testing of an AWWA Class IV Lining System: Steel Composite Lining System Pipelines 2023: Construction and Rehabilitation - Proceedings of Sessions of the Pipelines 2023 Conference 10.1061/9780784485026.019 The general requirements for structural classification systems are defined in AWWA Manual M28. Currently, there is no specific protocol or procedure for development and testing of AWWA Class IV lining system. The steel composite lining system (SCL) has been developed, tested, and installed for over the past 13 years. This paper will describe the liner design methodology, the materials, component, and full-scale model testing for the SCL system, which documents the AWWA Class IV classification. Rigorous testing with innovative technology at three levels transformed the SCL system from original concept to a Class IV lining system. The data collected during each level is used to better understand the design and construction methodology and their impacts on system performance. Full-scale mockup and testing along with posttest digital twin computational modeling verifies the design approach and Class IV lining system performance. As an additional proof of performance, an instrumented installation was monitored for more than one year, in situ. The long-term measurement further verified material and system performance while in water delivery service. Not all SCL tests were successful on the path to becoming a Class IV system. The SCL story is indicative of the need for testing on all levels to make sure the system in its final form can be designed using industry standards, is constructible as designed, and provides the functionality required. Β© ASCE.
publications-5146 Conference paper 2023 Mahmoud M.M.M.; Darwish R.; Bassiuny A.M. Development of a Smart Aquaponic System Based on IoT International Conference on Control, Automation and Systems 10.23919/ICCAS59377.2023.10317034 Aquaponics is a sustainable farming practice that combines aquaculture and hydroponics in a recirculating system. The nutrients from the fish waste are used by the plants to grow, and the plants filter the water for the fish. This process is self-sustaining and requires little human intervention. Monitoring and controlling aquaponic systems is a complex task. In this paper, the Internet of Things (IoT) is used to monitor and control the system. In addition, a digital twin (DT) is deployed to digitize physical systems. The findings demonstrate that IoT and DT can improve aquaponic systems by collecting data about environmental conditions such as light levels, humidity, and temperature, which is used to regulate plant growth, monitor fish health, optimize crop production, and optimize nutrient recycling. Β© 2023 ICROS.
publications-5147 Conference paper 2023 Tripathi I.; Froese T.; Mallory-Hill S. Envisioning Digital Twin-Enabled Post-occupancy Evaluations for UVic Engineering Expansion Project Lecture Notes in Civil Engineering 10.1007/978-3-031-34593-7_8 The University of Victoria is in the process of expanding its engineering and computer science department to meet the growing demand for post-graduate programs by building two new buildings. UVic’s Green Civil Engineering department is actively involved in the project and planning to use the buildings as experimental apparatuses for various building science and systems research such as energy, water, and indoor environmental quality. These buildings aspire to achieve net zero carbon certifications to promote innovations in sustainability. Post-occupancy evaluations (POE) provide scientific methods and tools to analyze how buildings function and to quantify their performance. First, this paper establishes the semantics of POE in the context of the new engineering expansion project along with project phases. Second, this paper discusses the digital twin execution plan that can guide the evolution of digital twins during each phase of the project life cycle for the purpose of POE. Third, this paper compares the proposed digital twin-based POE methodology with the conventional POE methodology. Conducting the POE on the UVic ECS expansion project will enable the researchers to determine the effectiveness of sustainable features by comparing the performance of existing and proposed facilities. © 2023, Canadian Society for Civil Engineering.
publications-5148 Conference paper 2023 Han X.; Salimi S.; Malkawi A.; Wang X.; Li N. A Validated High-Fidelity Simulator for an Ultra-efficient Office Building Based on Coupled EnergyPlus-Modelica Models Building Simulation Conference Proceedings 10.26868/25222708.2023.1680 This paper presents the development and validation of a high-fidelity simulator for an ultra-efficient office building, which functions as a living laboratory that integrates natural ventilation with automated windows, and geothermal heat pump assissted thermally active building systems. Specifically, The simulator is developed with coupled EnergyPlus-Modelica models, in which the building envelop, equipment and occupant profile are modeled in EnergyPlus, and the radiant floor, HVAC system and controls are modeled in Modelica. The natural ventilation under different wind conditions is simulated with Computational Fluid Dynamics, which is integrated into the Modelica model for ventilation rate prediction through interpolation from a lookup table. The developed models are calibrated and validated with the measured building operational data from the extensive senor network in the building. The normalized Mean Bias Error (MBE%) and the Coefficient of Variation of the root mean square error (CV (RMSE)) for heating/cooling loads simulated by the EnergyPlus model are 2%/1% and 11%/16%, respectively. The RMSEs of the simulated hourly water loop temperature and slab temperature range from 0.48 K to 1.06 K. The RMSE of the simulated daily heat pump power is 236.4 W. The use of the simulator is then demonstrated to improve the control of the room and slab temperature. To conclude, the developed simulator shows effectiveness to serve as a digital twin to support optimal operation of the studied building as well as a virtual testbed for advanced controls development, evaluation and benchmarking for ultra-efficient buildings. Β© 2023 IBPSA.All rights reserved.
publications-5149 Conference paper 2023 Barkakoti C.; Joshi S. Advancement of Digital Twin in Irrigation and Smart Farming 2nd International Conference on Sustainable Computing and Data Communication Systems, ICSCDS 2023 - Proceedings 10.1109/ICSCDS56580.2023.10104641 Agriculture and food production has been immensely impacted by digitalization; paving the way for advanced data processing techniques and technologies possible in the field of agriculture. The aim of Smart farming is to extract information from agricultural entities to resolve issues and challenges faced with regard to rising demand, food security, and climate change. Digital Twin is a concept that has the potential to increase production and efficiency while reducing the use of energy and other materials. The potential for digital twins to succeed in sustainable agriculture is enormous. Since the agriculture sector is dynamic and complicated, it needs an advanced management system. The necessity for automatic and self-reliant agriculture set up at the initial level is critical due to the frequent occurrence of natural disasters like floods and diseases. Due to problems with soil-based systems such as erosion, heavy manual labor, water availability, and productivity issues, soilless agriculture is becoming more and more popular. Digital techniques are expected to increase the optimization of processes and assist in agricultural decision-making. Β© 2023 IEEE.
publications-5150 Conference paper 2023 James Akande A.; Hou Z.; Foo E.; Li Q. A Runtime Verification Framework forΒ Cyber-Physical Systems Based onΒ Data Analytics andΒ LTL Formula Learning Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 10.1007/978-981-99-7584-6_19 Safeguarding individuals and valuable resources from cyber threats stands as a paramount concern in the digital landscape, encompassing realms like cyber-physical systems and IoT systems. The safeguarding of cyber-physical systems (CPS) is particularly challenging given their intricate infrastructure, necessitating ongoing real-time analysis and swift responses to potential threats. Our proposition introduces a digital twin framework built upon runtime verification, effectively harnessing the capabilities of data analytics and the acquisition of Linear Temporal Logic (LTL) formulas. We demonstrate the efficacy of our approach through an application to water distribution systems. Β© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.