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-5241	Conference paper	2022	Spasova T.	Assessment of monitoring and security on the Black Sea coast by Remote sensing and Open data	Proceedings of SPIE - The International Society for Optical Engineering	10.1117/12.2636343	Interoperability of data from different sources is the main purpose of this study. The survey covers the waters of the Black Sea in Bulgaria. Our country has a maritime border of 378 km, of strategic importance and is close to military conflicts (e.g. Ukraine). The use of different satellite and in situ data in hybrid models makes it possible to obtain much more information from one point or area of interest. Different satellite data have been used, which are collated with registers of open and spatial data from the Bulgarian Open Data Portal. Much of the ground information is extremely rich in detailed information on the chemical, environmental and climate status of the specific point or area of interest. The survey uses Copernicus data, Landsat, the Open Data Portal, the Black Sea Basin Directorate and Innovative Techniques and Methods for Reducing Marine Litter in the Black Sea Coastal Areas β€” (BSB552 RedMarLitter and etc. These interoperable data will be useful for coastal protection and security, environmental monitoring and adequate decision-making in the administration, business and various other groups of data users. The methodology aims to support work on Digital Twins of the Earth. Information from so many sources will at one point lead to a much more effective and efficient management of territories in the event of environmental disasters (e.g. plastic and oil pollution), various military conflicts and their consequences, as well as annual monitoring of tourist areas and many others. Β© 2022 SPIE.
publications-5242	Conference paper	2022	Raut S.; Schemminger J.; von Gersdorff G.; Mellmann J.; Sturm B.	Moving towards digital twin based smart drying systems for agricultural products	2022 ASABE Annual International Meeting	10.13031/aim.202200465	Drying is a widely used technique to extend product shelf life, reduce post-harvest losses and allow for retention of essential nutrients. Currently, processing conditions/parameters applied to minimise energy consumption and production costs result in significant loss of product quality. Therefore, there is a need to optimise the drying process in a holistic manner that includes a balance between costs, energy demand and product quality. To that end, smart/intelligent drying has a high potential as an effective and sustainable solution to improve resource and process efficiency and ensure high quality products. Smart drying encompasses real-time monitoring of food products using non-invasive measurement techniques, hybrid modelling and integrated control systems.. To shift towards smart drying, the first step includes the collection and analysis of multidisciplinary data that improves understanding of the process-product relationship. Thus, an experimental investigation was conducted with organic carrots to understand the effect of different drying conditions and strategies - namely (i) air temperature controlled, (ii) product temperature controlled and (iii) stepwise air temperature controlled - on the product quality. Moisture content, total carotenoid retention, water activity, and rehydration ratio were measured as quality control parameters. The results from the investigation revealed that the product temperature controlled strategy led to a shorter drying time and higher or similar retention of carotenoid content within the carrot slices in comparison to the other strategies. Water activity and rehydration ratio showed no significant differences among the three strategies. The extensive data set collected within this investigation provided further knowledge to understand the co-relationship between process parameters, energy consumption and product quality. Thus acting as a foundational base for the development of a digital twin in order to develop smart drying systems. Development of a digital twin is the next step in the shift of paradigm towards a smart drying process. The optical sensors (infrared, RGB, HSI) implemented within the above investigation provide insight for changes within the product. However, they are limited in their capacity as they fail to combine the information on the physical and chemical mechanisms. The development of a digital twin allows the agricultural product in question to be represented using a physics-based hybrid digital model that integrates all conditions while cross checking to the real time based sensor data. The current study will present the initial results, concerning the modelling of process and product quality, from the physics-based hybrid model digital twin developed to investigate efficient food and feed drying concerning process and product quality. Β© 2022 ASABE. All Rights Reserved.
publications-5243	Conference paper	2022	Ehlers S.; Abdussamie N.; Branner K.; Fu S.; Hoogeland M.; Kolari K.; Lara P.; Michailides C.; Murayama H.; Rizzo C.; Seo J.K.; Kaeding P.	COMMITTEE V.2 EXPERIMENTAL METHODS	Proceedings of the 21st International Ship and Offshore Structures Congress, ISSC 2022	10.5957/ISSC-2022-COMMITTEE-V-2	This report reviews the recent advances of the past years in ships and offshore structural testing area including scaling laws, DIC, hydrodynamic of flexible structures, wave-in-deck, hybrid model testing, corrosion testing, iced load measurements, health monitoring model and digital twin model. The following summary and recommendations are made for future work in the area of innovative experimental methods in ships and offshore industry. It is important to also note that as experimental techniques allow for a greater understanding of the underlying material and structural behaviour, and generate extensive data clouds for processing and evaluation. As a result, we recommend that a future chapter in the next committee report focus on data evaluation and statistical approaches; this can provide an in-depth look of state of the art of processes utilized for evaluating the extensive data captured/utilized during experiments. In chapter 2, a review of scaling laws is presented in systematic and recent advancements in structural testing related to ships and offshore structures. General scale modelling methods are provided and described the main characteristics of each method such as dimensional analysis, applied to governing equation, energy method, empirical similarity method through the literature review. Recent application of scale models can be found in field of offshore wind turbine structure and ice testing area. These structures are subjected to complex phenomena such as wave loads and drifting forces may also need to be considered in particular applications, ice flows, continuous winter sea ice, and icebergs. Application DIC in chapter 3, DIC techniques have certainly come into play in many recent experimental evaluations, as the methods allows for elucidating the surface strain behaviour of a component evaluated either in the laboratory and in the field. This chapter has been to give an updated review on applications of DIC techniques in ships and offshore structural tests classifying them by test articles, with a brief insight on commercial instrumentations available on the industry and related to DIC society and a deeper focus on the applied methodologies, providing recent references for those who are interested in this topic. Worth mentioning is that some DIC applications are included in the benchmark study performed by the Committee and reported in section 15. In chapter 4, A large amount of research has focused on better measuring and predicting the hydrodynamic loads, forming several practical hydrodynamic coefficients databases which have been widely used in VIV prediction tools for flexible structure manufacturing industry. Although these databases make great contributions to the field of VIV research, have not been sufficiently modelled in the coefficient database obtained from rigid cylinder experiments. Recently, the phase angle between cross-flow and in-line response had a strong influence on the hydrodynamic coefficients for both rigid and flexible cylinders. And variations of tension and flow velocity were strongly correlated with time-varying hydrodynamic coefficients, therefore, inputs to the prediction of vessel motion induced VIVs, making the prediction possible. Also, the effects of Re numbers and surface roughness on hydrodynamics of VIV and the effect of wake interference on hydrodynamics of a twin-tube submerged floating tunnel (SFT) can be found for can efficient way and requirement in the literature. In chapter 5, based on the challenges remaining in the problem of wave-in-deck impact on offshore structures discussed above, there are several research gaps that can be addressed in future. There is still considerable uncertainty about the magnitude and distribution of wave impact loads on structural deck elements near the free-surface. Effects of the columns of the floating platform on the wave-in-deck forces have not been systematically studied. The measurement, estimation and simulation of local pressures due to wave-in-deck impact events on all types of offshore structures remains challenging. Accurate measurements and prediction of global loads and dynamic response of floating offshore structures due to wave-in-deck impact events is extremely limited. Combined numerical-experimental wave-in-deck investigations on floating offshore structures are not currently available in the open literature. In chapter 6, this chapter focused on hybrid model testing (HMT) combines physical model test and numerical simulations to solve problems that physical model tests alone cannot conveniently or reliably address. In marine model testing, the challenges like ultra-deep water, multi-phase fluids, parameter traversal and so on cannot be avoided. HMT is regarded as the most promising technique to solve these issues. As of today, HMT is still immature, some advanced applications however have been developed. HMT allows researchers to impose mass-spring-damping parameters in virtual space and can artificially adjust and precisely control these critical parameters. It is a very helpful and exciting idea to solve the involved problems. In Chapter 7, a brief reviewed of friction test in terms of two main areas exist where friction is of importance: machineries and mechanical connections, and in cargo/mechanical handling operations. For maritime and offshore applications (e.g. Out-of-Plane Bending), surface conditions and environmental conditions are important parameters. Small and the smaller specimens may be used for screening the theoretical friction coefficients and find trends. Larger or even real size specimens should be used to confirm the actual behaviour. As per the results of literature, friction tests can be split it eh standard, small size specimen standard tests, and the large size, more representative tests. While the standard tests are well covered by standards and guidelines, the larger set-ups are to be tailor made and require goo understanding of the physics as results require interpretation by the experimenter. In chapter 8, the measurement, analysis and mitigation of vibrations in ship and offshore structures is rather well established. Nevertheless, measurement and mitigation methods are still being developed. Measurementβ€™s techniques may also include laser of video techniques. Mitigation measures include devices that cancel vibrations at a low weight penalty, such as absorbing supports or Tuned Mass Dampers. Numerical developments include methods that use sub-structuring or modal shapes to reduce the computational cost. In chapter 9, Material selection for ships and offshore structures exposed to sub-zero temperatures is traditionally based on Charpy and fracture toughness test results of the base materials and its welded connections. In the last years however, fatigue properties have been the focus of a couple of studies due to the acceleration of fatigue crack growth below the so-called fatigue transition temperature, where ductile crack growth is superimposed by cleavage burst. Concluding, fatigue testing at low temperatures demands special attention to the set-up and instrumentation. The testing temperature is normally lower than the application temperature, and liquid nitrogen may be needed to cool down the area of interest to -60 Β°C. Temperature compensation is required for sensor, either strain gauges or potential drop methods. In chapter 10, The corrosion process and the interpretation of the effect of corrosion on the structural integrity remains an area of uncertainty. In corrosion testing, a large spread may be observed in measured corrosion rates, as is confirmed by industrial thickness measurement. Including the geometrical effects of corrosion damage in a representative manner in numerical simulations requires the use of probabilistic methods, as a precise description would require model with too many details. Hence, simplifications and generalizations are needed. In chapter 11, large scale impact experimentation are unique options to verify developments in structures design, analysis and prediction of failure. In turn, this demands good command of the experimentation techniques, and the use of as many sensors as possible to make possible use of the results. In chapter 12, The chapter present a State-of-the-Art review, to include recent advances and future trends of industry challenge with current standard and out lookout. The wind industry is concerning with the long time-to-marked for future large turbine blades and are interested in ways to shorten the test time. It is a question at which size and when will it stop to make sense to test these long blades according to current standard. Trends of development of more advanced test methods investigated a dual or multi axis test methods to test blades under more representative loading compared to operational loads and ways to speed up the test and challenge with different SN-curves for different materials. Testing parts of blades captured testing with more complex and realistic loading at forced loading, challenges with boundaries, and using subcomponent testing to validate numerical models. In chapter 13, Full scale ice load measurements play a significant role in the design of ships and offshore structures in ice covered waters. Full scale measurements of fixed vertical offshore structure are dis-cussed here. Generalizability of the results can be summarised that as pointed out by KΓ¤rnΓ¤ (2009) it is likely that the experimental data recorded on vertical structures is only applicable for the conditions where the data was record-ed. Thus, data recorded for stiff structures might not be applicable for compliant structures. As discussed before, the compliancy might be one source of the observed rate dependency. The collected data is often incomplete: although local and global ice forces can be recorded during ice action, the ice properties (compressive strength, porosity...) might remain unknown. It is because the ice samples cannot be taken during ice action - when ice is moving. Actual local pressure is challenging to measure. It is known that the ice pressure is concentrated in a small area as shown by Joensuu & Riska (1989). They observed in laboratory scale experiments using PVDF-film that the ice pressure is concentrated on narrow, line like high pressure zones. But, the area of the load panels in full scale of often quite big, in the order of 1 m2. Thus, the actual local pressure exerted to structure is significantly higher than the average pressure measured with the big load panels. But there is no method available for more accurate local pressure measurements in full scale. Although field tests are important and can reveal phenomena that cannot be observed in laboratory scale, there are few things to consider when interpreting the results. In chapter 14, Bridging the relationship between the degradation in the material and the structure is an emerging field of research which requires advanced data fusion, signal processing, AI-based trend detection algorithms and the reliability analysis methods. Data fusion herein refers to combining the data gathered from different SHM sensors by using data fusion algorithms for better damage diagnosis (Eleftheroglou et al., 2018). Other research efforts are recommended for improving the durability of SHM sensors for offshore implementations, inclusion of SHM in the condition monitoring standards and guidelines, addressing big-data issues for developing real-time data collection and analysis frameworks and using the digital twins for real-time reliability assessment. In the Benchmark study, from this relatively simple experiment performed by 6 parties, it is clear that a vast range of choices can be made to carry out the tests. Understanding the effect of the choices on the end result is essential. For instance, a heavy sensor influences the natural frequency a lot. Also, the chosen instrumentation influences the information to be gained from an experiment. Only the natural frequency, by manual excitation, or also damping and higher order modes when using an instrumented hammer. In order to understand the many experiments that are done worldwide, sharing of the results and being transparent on the methodologies of experimentation is very beneficial for making the most of any experiment. Experimental data should be published as is in digital format and not only as a by-product in a publication as figures limiting the use of it. Β© The Author(s), 2022.
publications-5244	Article	2022	IllΓ©s B.; Medgyes B.; DuΕ΅ek K.; BuΕ΅ek D.; Skwarek A.; GΓ©czy A.	Numerical simulation of electrochemical migration of Cu based on the Nernst-Plank equation	International Journal of Heat and Mass Transfer	10.1016/j.ijheatmasstransfer.2021.122268	Electrochemical Migration (ECM) is getting more attention in the microelectronics industry due to the continuing miniaturization, which increases the possibility of short circuit formation caused by the ECM-induced dendrites. This work presents a 2D numerical model of the ECM based on the Nernst-Plank equation. The model contains the deterministic description of the metal dissolution, the changes of electrolyte properties, and the ion transport in the electrolyte. However, the reduction of the ions and the dendrite growth is described stochastically. The capability of the model was tested in the case of pure copper electrodes with a gap distance 200 Βµm, 10 VDC bias, 20 Β°C temperature, and a contaminant-free electrolyte. The results of the model were validated by experimental water-drop tests. The results showed very good agreement between the experimental and the calculated mean time to failure values, dendrite morphologies, and the kinetics of the dendrite formation. The model showed that the developing dendrites consume most of the Cu2+ ions around them, which answers why only some dominant dendrites can develop in a given area. The model proved that not only the electric field but the diffusion of the ions is also dominant in given phases of the ECM process. Our model could be a useful tool for ECM failure prediction and for further ECM researches as the digital twin of the ECM process. Also the approach can be applied in various aspects of failure-prediction in modern reflow-soldering. Β© 2021 The Author(s)
publications-5245	Book chapter	2022	Shin Y.; Oh J.; Jang D.; Shin D.	Digital Twin of Alkaline Water Electrolysis Systems for Green Hydrogen Production	Computer Aided Chemical Engineering	10.1016/B978-0-323-85159-6.50247-5	The digital twin which supports data-based decision making, optimization, control and anomaly detection and diagnosis, can contribute to the improvement of sustainability, agility and productivity in water electrolysis system, which is expected to provide to reduce green hydrogen production cost. In this study, we propose a digital twin for a 500kW alkaline water electrolysis (AWE) to be built at the Saemangeum Renewable Energy National Demonstration Complex in Korea to reduce green hydrogen production cost through optimal operation of AWE system. A simulation model, which is the basis of the digital twin, was developed with Python and gPROMS, and the system efficiency of the AWE process according to pressure was analyzed comparing between excluding the compression process and including the process of hydrogen compression to 200 bar. The optimum operating pressure with the compression showed at 10-30 bar. At high pressure, process equipment cost becomes higher, therefore, it is essential to consider hydrogen compression to the storage pressure in order to decide the optimal operating conditions. Β© 2022 Elsevier B.V.
publications-5246	Conference paper	2022	Liu Y.; Liu X.; Guo J.; Lou R.; Lv Z.	Digital Twins of Wave Energy Generation Based on Artificial Intelligence	Proceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022	10.1109/VRW55335.2022.00210	Ocean waves provide a large amount of renewable energy, and Wave energy converter (WEC) can convert wave energy into electric energy. This paper proposes a visualization platform for wave power generation. The platform can monitor various indicators of wave power generation in real time, combined with Long Short-Term Memory (LSTM) neural network to predict wave power and electricity consumption. We make digital twins of a wave power plant in a computer, allowing users to remotely view the factory through VR glasses. Β© 2022 IEEE.
publications-5247	Article	2022	Matsuda Y.; Ooka R.	DEVELOPMENT OF THE DIGITAL-TWIN FOR BUILDING FACILITIES (PART 3): A COMPARISON OF METAHEURISTICS AND REINFORCEMENT LEARNING FOR OPTIMAL CONTROLS; [ε»Ίη―‰θ¨ε‚™γ®γƒ‡γ‚Έγ‚Ώγƒ«γƒ„γ‚¤γƒ³η”_x009f_ζγ«ι–Άγ™γ‚‹η ”η©¶(η¬¬ 3 ε ±):ζ_x009c_€ι©ε¶εΎ΅γ«γ_x008a_γ‘γ‚‹γƒ΅γ‚Ώγƒ’γƒ¥γƒΌγƒγ‚Ήγƒ†γ‚£γ‚―γ‚Ήγ¨εΌ·ε_x008c_–ε¦ηΏ’γ®ζ―”θΌƒ]	Journal of Environmental Engineering (Japan)	10.3130/aije.87.222	In this study, to quantitatively evaluate a metaheuristic and a model-based reinforcement learning which are control methods using a predictive model, these methods were compared for energy costs and computational loads. As a result, it was revealed that a metaheuristic has more saving energy costs, whereas model-based reinforcement learning has lower computational loads. Therefore, it is necessary to select an appropriate method to a target system, for example, a metaheuristic is more suitable for a mode control, and a model-based reinforcement learning is more suitable for a water flow control of pumps. Β© 2022 Architectural Institute of Japan. All rights reserved.
publications-5248	Book chapter	2022	Lv Z.; Chen D.	Improving human living environment and human health through environmental digital twins technology	Digital Twin for Healthcare: Design, Challenges, and Solutions	10.1016/B978-0-32-399163-6.00013-5	The present work aims to improve the human living environment by using Digital Twins (DTs) technology. The DTs technology is applied to sewage treatment infrastructure to ameliorate the problems of sewage discharge management in current environmental protection management. First, the energy consumption of the water system of central air-conditioning is studied, and the DTs model of central air-conditioning is established. Then, a model parameter identification framework is constructed based on the genetic algorithm and multistrategy initial solution space optimization (MISSO). Moreover, a model prediction interval estimation method based on K-means clustering is proposed, and an artificial network model is used to compensate for the prediction results. The experimental results demonstrate that accurate models of chilled water pump and cooling water pump can be obtained based on the MISSO and genetic algorithm. Besides, the absolute relative errors of predicted and measured power consumption per hour of most water pump models are kept within 5%. The mean value of the prediction interval of chilled water outlet temperature and cooling water outlet temperature of the chiller model is 0.45% and 0.29%, respectively. In addition, the mean value of the absolute value of the Adaptive Communication Environment (ACE) of the prediction interval of chilled water pump's hourly power consumption is 1.21%; the average absolute value of ACE of the predicted range of cooling pump power consumption per hour is 1.74%. After error compensation, the error between the predicted value and measured value of chilled water outlet temperature by the Department of Energy (DOE-2) model decreases significantly. Therefore, the uncertainty estimation method of the central air-conditioning water system proposed here has good performance. This method can reduce air-conditioning energy consumption, effectively save energy, and reduce emissions, which is conducive to environmental governance, thus improving human health. Β© 2023 Elsevier Inc. All rights reserved.
publications-5249	Conference paper	2022	Dhoorjaty P.; Wold I.; Penmetsa D.	Development of a Hydrate Kinetics-Based Digital Twin for Blockage Detection and Production Optimization	Proceedings of the Annual Offshore Technology Conference	10.4043/32102-MS	Management of hydrate risk is a challenging problem in gas-condensate production systems. A "no inhibitor, no production" operational strategy is the norm due to the insufficiency of real-time knowledge of process conditions and hydrate kinetics in the field. This implies both lost-production costs and inadequate risk awareness. Recent advances in hydrate kinetics modeling in gas-dominated systems, based on fundamental research at the University of Western Australia (UWA), however, provide an opportunity for increased operational efficiencies and safety. This paper presents progress made in a joint-industry project (JIP) towards an integrated, real-time flow assurance model incorporating hydrate kinetics. This JIP leveraged existing data from UWA--including flowloopmeasurements and the modelling of hydrate growth and transport mechanisms--to achieve the integration of a hydrate kinetics model with an existing, field-proven multiphase flow simulator. This paper discusses the modeling, validation against experimental data, and the testing against historical data from a field system underhydrate-free and hydrating conditions. The model showed good agreement for multiphase flow prediction of laboratory experiments. Trends of pressure drop dependence on various flow parameters agreed as well. For field data of a large gas-condensate pipeline, the model correctly predicted when hydrates form and when they are absent. These simulations, further, revealed the sensitivity of overall hydrate holdup and distribution to several parameters, including ambient temperature, holdup profiles, water droplet entrainment, and the strength of hydrate-wall adhesion. Since number of these parameters are subjected to underlying uncertainties in field conditions, a viable hydrate monitoring/prediction tool ought to be based on ensembles of simulations (an analogy might be drawn to hurricane track prediction). This is particularly true for predicting the location of the hydrate blockage and the time-to-remediation. Currently, there is little modeling support to help manage hydrate risk in gas-condensate production operations without recourse to overly conservative strategies, such as overdosing. This model represents the first steps towards an online tool that can be integrated into digital twins of such fields. Such a tool will help optimize inhibitor consumption, reduce lost production costs, and provide early warning of hydrate blockage hazard. Potential end-user savings, from inhibitor consumption alone, are estimated at USD 500M in capital expenditure and USD 50M per annum in operational expenditure, for a typical moderate to large development. Β© 2022, Offshore Technology Conference. All rights reserved.
publications-5250	Conference paper	2022	Tepsa T.; Haavikko M.; Li O.; Ruismaki V.-M.; Kangas S.; Kattelus J.; Vaataja H.	A Digital Twin of a Heat Pump with a Game Engine for Educational Use	2022 45th Jubilee International Convention on Information, Communication and Electronic Technology, MIPRO 2022 - Proceedings	10.23919/MIPRO55190.2022.9803694	This study introduces a Digital Twin (DT) of an air-to-water heat pump to be used in the maintenance training of secondary and Higher Education (HE) students as well as personnel and customers of companies that sell and maintain heat pumps. The DT presented introduces the learner to two key maintenance procedures in a Virtual Reality (VR) environment. The learning is based on the progress of completing the sub-tasks in an intended order. The implementation of the solution is described. A preliminary user study confirms that a DT of a heat pump is an attractive option as a VR learning environment for training maintenance procedures and tasks due to the positive learning and user experience. However, a few participants would prefer using a real system in the learning of maintenance tasks as compared to the DT. The ratings of perceived immersiveness measured as the concentration on the tasks, rather than on using the system indicate that there is room for improvement. Realism and immersiveness of carrying out tasks and actions in VR could be improved by implementing more realistic haptics as well as more freedom to carry out the maintenance procedures in a user selected order after first learning the correct order. Β© 2022 Croatian Society MIPRO.