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–˛ Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-5311 Conference paper 2021 Carlberg B.S. The Autonomous Mill: Utilizing Digital Twins to Optimize the Pulp & Paper Mill of the Future IEEE Conference Record of Annual Pulp and Paper Industry Technical Conference 10.1109/PPIC47846.2021.9620318 This paper will describe the Autonomous Mill of the future as a mill that benefits from the use of Digital Twins utilizing a Process Model coupled with a Control Model of the real-time Control System to allow the Autonomous Mill to 'run itself' with little or no human intervention.This paper will then give an overview of the unit operations and equipment common to pulp and paper mills and conclude with several examples of specific opportunities where control systems optimization through Advanced Process Control (APC) and Model-Based Predictive Control (MPC) can increase production; reduce costs, and autonomously operate the mill of the future.The pulp and paper mill is often divided into six main 'islands' of automation; raw material receiving and preparation (the woodyard), the pulp mill, the powerhouse, the paper mill, converting and finishing, and effluent treatment. Each of these islands presents their own, unique set of unit operations; but, perhaps not surprisingly, you can see similar unit operations in various industries besides pulp and paper. For example, the powerhouse equipment, besides the main difference being that the fuel is 'black liquor', the equipment can be found in any other industrial power plant. In the paper machine 'island', the use of cascaded variable-speed drives to control the paper sheet tension is also seen in the draw line of a steel, textile, or fiber mill. And, as a final example, the effluent treatment facility of the paper mill has many of the same equipment you will find in a municipal water/wastewater plant.Several examples of specific control systems optimization included for each of these 'islands' include chemical savings in the lime kiln and causticizing, pulping, screening and refining, washing, and bleaching processes of the pulp mill; energy savings in recovery boiler sootblowing and the lime kiln, pulp stock preparation including cleaning and refining and the paper pressing and drying sections of the paper mill; and the environmental savings involved in effluent treatment and recycling water.Lessons learned:1.What is an Autonomous Mill?2.What is a Digital Twin?3.understand the equipment and the processes in a pulp and paper mill4.understand the similarities to other industries5.understand specific areas where control system optimization can decrease costs and/or increase production. Β© 2021 IEEE.
publications-5312 Conference paper 2020 Mo J.P.T.; Beckett R.C. Transdisciplinary system of systems development in the trend to X4.0 Advances in Transdisciplinary Engineering 10.3233/ATDE200055 Since the announcement of Industry 4.0 in 2012, multiple variants of this industry paradigm have emerged and built on the common platform of Internet of Things. Traditional engineering driven industries such as aerospace and automotive are able to align with Industry 4.0 and operate on requirements of the Internet of Things platform. Process driven industries such as water treatment and food processing are more influenced by societal perspectives and evolve into Water 4.0 or Dairy 4.0. In essence, the main outcomes of these X4.0 (where X can be any one of Quality, Water or a combination of) paradigms are facilitating communications between socio-technical systems and accumulating large amount of data. As the X4.0 paradigms are researched, defined, developed and applied, many real examples in industries have demonstrated the lack of system of systems design consideration, e.g. the issue of training together with the use of digital twin to simulate operation scenarios and faults in maintenance may lag behind events triggered in the hostile real world environment. This paper examines, from a high level system of systems perspective, how transdisciplinary engineering can incorporate data quality on the often neglected system elements of people and process while adapting applications to operate within the X4.0 paradigms. Β© 2020 The authors and IOS Press.
publications-5313 Conference paper 2021 Zhabitskii M.; Andrienko Y.; Malyshev V.; Chuykova S.; Zhosanov A. A Digital Twin of Intensive Aquabiotechnological Production Based on a Closed Ecosystem Modeling & Simulation European Modeling and Simulation Symposium, EMSS 10.46354/i3m.2021.emss.034 Currently, intensive fish farming using closed water circulation technology is becoming one of the breakthrough technologies in the aquaculture production. Digital transformation for such production is necessary for the effective management of ultra-high-density aquaculture farms. This transformation is based on the digital twin of aqua-biotechnological farms. The authors performed digital modeling & simulation of the biotechnological component of intensive aqua farm. The main equations of the model are presented in the article. Models of lungfish and trout ecosystems are considered. The models were tested as part of the digital twin for the real aqua farm. The qualitative coincidence of the results of modeling & simulation with the behavior of the ecosystem is obtained. The model has not yet achieved sufficient accuracy for commercial use. The reasons for the insufficient accuracy of the simulation are discussed. Some variants of the simulation model's development for simple closed aquatic ecosystems with a large biological load are considered. It is concluded that it is necessary to integrate a digital twin based on a simulation model of a biosystem with the technology of the Industrial Internet of Things to achieve the necessary accuracy of describing a complex engineering and biotechnological system. Β© 2021 The Authors.
publications-5314 Conference paper 2021 Ciliberti F.G.; Berardi L.; Laucelli D.B.; Giustolisi O. Digital Transformation Paradigm for Asset Management in Water Distribution Networks Proceedings of 2021 10th International Conference on ENERGY and ENVIRONMENT, CIEM 2021 10.1109/CIEM52821.2021.9614864 This work proposes a novel structured paradigm for digital transformation for Water Distribution Network asset management. The novel framework has been developed by integrating the Digital Twin concept with well-established algorithms and methodologies, to support technicians and water utilities in solving Water Distribution Networks life-cycle management issues. The digital water services, implemented in the WDNetXL/WDNetGIS platform, provide such integration as to support users on specific technical tasks. Two of these services, recently adopted to support real-life asset management design on several WDN, are briefly presented: the Digital Water DMA Analyzer supports the analysis and customization for the design of district metering areas, aimed WDN monitoring and leakage reduction through pressure control; the Digital Water Rehabilitation enables the creation of pipes replacements planning, returning explicit performances in terms of leakages reduction a efficiency. Β© 2021 IEEE.
publications-5315 Article 2021 Bartos M.; Kerkez B. Pipedream: An interactive digital twin model for natural and urban drainage systems Environmental Modelling and Software 10.1016/j.envsoft.2021.105120 Faced with persistent flooding and water quality challenges, water managers are now seeking to build digital twins of surface water systems that combine sensor data with online models to better understand and control system dynamics. Towards this goal, this study presents pipedreamβ€”an end-to-end simulation engine for real-time modeling and state estimation in natural/urban drainage networks. The engine combines (i) a new hydraulic solver based on the one-dimensional Saint-Venant equations and (ii) a Kalman filtering scheme that efficiently updates hydraulic states based on observed data. Using sensor data from a real-world watershed, we find that the simulation engine is effective at both interpolating hydraulic states and forecasting future states based on current measurements. By providing a complete, real-time view of system hydraulics, our software will enable rapid detection of flooding, improved characterization of maintenance and remediation needs, and robust real-time control for both small-scale (stormwater) and large-scale (river/reservoir) networks. Β© 2021 The Author(s)
publications-5316 Article 2021 Bongartz P.; Bator I.; Baitalow K.; Keller R.; Tiso T.; Blank L.M.; Wessling M. A scalable bubble-free membrane aerator for biosurfactant production Biotechnology and Bioengineering 10.1002/bit.27822 The bioeconomy is a paramount pillar in the mitigation of greenhouse gas emissions and climate change. Still, the industrialization of bioprocesses is limited by economical and technical obstacles. The synthesis of biosurfactants as advanced substitutes for crude-oil-based surfactants is often restrained by excessive foaming. We present the synergistic combination of simulations and experiments towards a reactor design of a submerged membrane module for the efficient bubble-free aeration of bioreactors. A digital twin of the combined bioreactor and membrane aeration module was created and the membrane arrangement was optimized in computational fluid dynamics studies with respect to fluid mixing. The optimized design was prototyped and tested in whole-cell biocatalysis to produce rhamnolipid biosurfactants from sugars. Without any foam formation, the new design enables a considerable higher space–time yield compared to previous studies with membrane modules. The design approach of this study is of generic nature beyond rhamnolipid production. © 2021 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals LLC
publications-5317 Article 2021 Seo D.; Huh T.; Kim M.; Oh J.W.; Cho S.G.; Jeong S.C. A predictive model for oscillating water column wave energy converters based on machine learning ICIC Express Letters, Part B: Applications 10.24507/icicelb.12.08.733 Research on digital twin technology for efficient operation in various indus-trial and manufacturing sites is being actively conducted currently in South Korea. The gradual depletion of fossil fuels and environmental pollution issues require new renewable and eco-friendly power generation methods such as wave power plants. However, in wave power generation, which generates electricity by the energy of waves, it is criti-cal to understand and predict the amount of power generation and operational efficiency factors such as breakdown because these are closely related to highly variable wave ener-gy. Therefore, firstly, it is necessary to derive a meaningful correlation between highly volatile data such as wave height and sensor data in oscillating water column (OWC) chamber. Secondly, methodological study that can predict desired information should be conducted by learning the prediction situation with the extracted data based on the derived correlation. In this study, we design a workflow-based training model using a machine learning framework to predict the pressure of the OWC and verify the validity of pressure prediction analysis through the verification and evaluation dataset, using Internet of Things sensor data to enable smart operation and maintenance with the digital twin of the wave generation system. Β© 2021 ICIC International.
publications-5318 Conference paper 2021 Nishimoto K.; Sampaio C.M.P.; Vale R.J.; Ruggeri F. Numerical Simulation of Hybrid Platform Supply Vessel (PSV) Fuel Consumption for the Pre-Salt Layer in Brazil Lecture Notes in Civil Engineering 10.1007/978-981-15-4680-8_34 The new regulations regarding ship emissions based on IMO regulations combined to the high fuel prices require the application of new technologies to improve ship efficiency and to reduce the CO2, NOX, SOX and BC emissions. The application of LNG as fuel and battery packs to improve the conventional engines performance are already a reality in offshore supply vessels (OSV) around the world. However, the reduction in OPEX and payback time of the additional investment is very dependent of the ship operational profile, which are related to the FPSOs and port facilities particularities in Brazil. In order to estimate the advantages of these technologies in the PSV overall performance several different simulators regarding DP operation, sailing, waiting and anchored mode are combined to obtain a digital twin of the vessel. These simulators are combined to the real data monitored from the ships regarding ship speed, position and heading collected in Brazil based on AIS/AIS-Sat database. This database is combined to the environmental conditions regarding wave, current and wind obtained based on global numerical models to provide the environmental loads acting in the ship during the different stages of the operation. The DP simulations are performed applying a thrust allocation algorithm, the calm water resistance is obtained based on regression models and the added resistance due to waves are computed based on strip theory. The forces are converted into electric load by considering the propeller, generators, switchboard, electric drive and engine efficiency curves combined to a power management system (PMS) algorithm, which balance the loads in the engines according to the operational mode. The baseline for comparison is the current PSV without dual-fuel engines or battery pack. Β© 2021, Springer Nature Singapore Pte Ltd.
publications-5319 Conference paper 2020 Alekseev A.; Mikhailovsky E. Development of information and computing technologies for modelling of pipeline and hydraulic systems E3S Web of Conferences 10.1051/e3sconf/202020902002 The paper is devoted to the development of information and computational technologies for creating digital twins of real pipeline systems of various types and purposes. The main results of work in the direction of creating the information computing environment ANGARA, as a basic technology for setting up and using the information and computing environment, describe its information, computing and analytical functions is presented. The technology of information and mathematical models integration for the creation of information computing systems for pipeline systems calculating of different types is presented. The concept of enterprise unified digital space developing, as well as technologies for remote access to it, is described. The article presents an object-oriented technology of computer modelling of pipeline systems and an example of its application when creating an online application for hydraulic calculations. The technology used by the authors for testing and comparing the effectiveness of various mathematical methods for calculating the flow distribution is presented. Prospective directions of calculation technologies development related to the use of parallel computing technology are presented. Β© The Authors, published by EDP Sciences, 2020.
publications-5320 Book chapter 2021 Malé C.; Lagier T. Simulating the interactions of environmental and socioeconomic dynamics at the scale of an ecodistrict: urban modeling of Gerland (Lyon, France) Ecosystem and Territorial Resilience: A Geoprospective Approach 10.1016/B978-0-12-818215-4.00011-0 The cities’ makers have to build more sustainable, more liveable, and more efficient cities. Accountability of their choice is growing and conventional way to do is showing limits. Cities are highly systemic system and digital software, in particular, Digital Making Decision Software offer disruptive solution to assess different scenarios on economic point of view but also on environmental, quality of life, and extrafinancial Kpi. This chapter presents the project MUG, located in the Gerland district of Métropole de Lyon (France). The main objective aimed at building digital twin of the Lyon city (with more than 140 datasets) and to able cities maker to elaborate and test scenarios of urban development (road, public transportation, urban project, infrastructures, building, etc.) based on coupled models (20+). The city consists in systems (population, housing, transport, economy, networks of water, energy, waste production and treatment, etc.) interacting together. The presented approach is based on the comparison of scenarios from now to 2040 to help the decision-maker to take the best strategic decision for their cities. © 2021 Elsevier Inc. All rights reserved.