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-4721 article 2013 Lee, Jay and Lee, Jay and Lee, Jay and Lee, Jay and Lapira, Edzel and Lapira, Edzel and Yang, Shanhu and Yang, Shanhu and Kao, Ann and Kao, Ann Predictive Manufacturing System - Trends of Next-Generation Production Systems IFAC Proceedings Volumes 10.3182/20130522-3-br-4036.00107 With rising competition abroad, US manufacturers are looking to reinvest manufacturing capabilities to counterbalance costs by increasing productivity. Being a dynamic and technologically advanced industry, as well as constantly to meet changing market demands, manufacturers are now forced to evolve strategies to manage larger capacity with faster speed, and more sophisticated machinery systems. This paper discusses the principles of predictive manufacturing system as a strategy to allow manufacturing industry to increase competitiveness through a highly transparent and worry-free manufacturing process, as well as an analytic framework how it can be implemented using a coupled-model approach.
publications-4722 article 2023 Wikström, Håkan and de Juan, Luis Martín and Remmelgas, Johan and Meier, Robin and Altmeyer, Andreas and Emanuele, Daniel and Jormanainen, M. and Juppo, Anne and Tajarobi, Pirjo Drying capacity of a continuous vibrated fluid bed dryer – Statistical and mechanistic model development International journal of pharmaceutics 10.1016/j.ijpharm.2023.123368 The drying capacity of a continuous vibrated fluid bed dryer was studied using a DoE by varying microcrystalline cellulose content in the formulation, water amount in the twin-screw granulation, inlet air temperature, air flow rate and the acceleration of the horizontal fluid-bed. Temperature and humidity profiles were measured along the dryer using wireless sensors. For the parameter space explored in this study, acceleration was the most influential process parameter of the dryer regarding the resulting granule moisture content. An empirical model was developed that allowed for fast and accurate moisture content prediction that could be incorporated into an enhanced control strategy. In addition, a mechanistic model was formulated that allow for prediction of temperature and moisture profiles, and most importantly the moisture content of the granules inside the dryer. The mechanistic model can be integrated to other unit operation models to provide overall understanding of an integrated continuous process line. The mechanistic model also makes it possible to define the equipment design requirements (e.g., length of the dryer) to meet the specific needs in terms of drying capacity, temperature and moisture profile.Copyright © 2023 Elsevier B.V. All rights reserved.
publications-4723 article 2024 Chiu, WK and Kuen, T and Vien, BS and Aitken, H and Rose, LRF and Buderath, M Advancing a Non-Contact Structural and Prognostic Health Assessment of Large Critical Structures. Sensors (Basel, Switzerland) 10.3390/s24113297 This paper presents an overview of integrating new research outcomes into the development of a structural health monitoring strategy for the floating cover at the Western Treatment Plant (WTP) in Melbourne, Australia. The size of this floating cover, which covers an area of approximately 470 m Γ— 200 m, combined with the hazardous environment and its exposure to extreme weather conditions, only allows for monitoring techniques based on remote sensing. The floating cover is deformed by the accumulation of sewage matter beneath it. Our research has shown that the only reliable data for constructing a predictive model to support the structural health monitoring of this critical asset is obtained directly from the actual floating cover at the sewage treatment plant. Our recent research outcomes lead us towards conceptualising an advanced engineering analysis tool designed to support the future creation of a digital twin for the floating cover at the WTP. Foundational work demonstrates the effectiveness of an unmanned aerial vehicle (UAV)-based photogrammetry methodology in generating a digital elevation model of the large floating cover. A substantial set of data has been acquired through regular UAV flights, presenting opportunities to leverage this information for a deeper understanding of the interactions between operational conditions and the structural response of the floating cover. This paper discusses the current findings and their implications, clarifying how these outcomes contribute to the ongoing development of an advanced digital twin for the floating cover.
publications-4724 article 2024 Michaux, P. and Gaume, Benjamin and Yu, Chan and QuΓ©mΓ©ner, Olivier Human body numerical simulation: An accurate model for a thigh subjected to a cold treatment Computers in biology and medicine 10.1016/j.compbiomed.2023.107689 This article presents the development of a digital twin model of a thigh portion subjected to various thermal treatments. Two scenarios are investigated: cold water immersion (CWI) and whole body cryotherapy (WBC), for which the comparison of numerical results with experimental measurements validates the consistency of the developed model. The use of real geometry on a first subject demonstrates the high heterogeneity of the temperature field and the need for accurate geometry. A second subject with thicker adipose tissue highlights the impact of the subject's actual morphology on the validity of the treatment and the necessity to work with real geometry in order to optimize cold modalities and develop personalized treatments.Copyright Β© 2023 Elsevier Ltd. All rights reserved.
publications-4725 article 2024 Cavalieri, S and Gambadoro, S Digital Twin of a Water Supply System Using the Asset Administration Shell. Sensors (Basel, Switzerland) 10.3390/s24051360 The concept of digital twins is one of the fundamental pillars of Industry 4.0. Digital twin allows the realization of a virtual model of a real system, enhancing the relevant performance (e.g., in terms of production rate, risk prevention, energy saving, and maintenance operation). Current literature presents many contributions pointing out the advantages that may be achieved by the definition of a digital twin of a water supply system. The Reference Architecture Model for Industry 4.0 introduces the concept of the Asset Administration Shell for the digital representation of components within the Industry 4.0 ecosystem. Several proposals are currently available in the literature considering the Asset Administration Shell for the realization of a digital twin of real systems. To the best of the authors' knowledge, at the moment, the adoption of Asset Administration Shell for the digital representation of a water supply system is not present in the current literature. For this reason, the aim of this paper is to present a methodological approach for developing a digital twin of a water supply system using the Asset Administration Shell metamodel. The paper will describe the approach proposed by the author and the relevant model based on Asset Administration Shell, pointing out that its implementation is freely available on the GitHub platform.
publications-4726 article 2024 Daneshgar, S and Polesel, F and Borzooei, S and SΓΈrensen, HR and Peeters, R and Weijers, S and Nopens, I and Torfs, E A full-scale operational digital twin for a water resource recovery facility-A case study of Eindhoven Water Resource Recovery Facility. Water environment research : a research publication of the Water Environment Federation 10.1002/wer.11016 Digital transformation for the water sector has gained momentum in recent years, and many water resource recovery facilities modelers have already started transitioning from developing traditional models to digital twin (DT) applications. DTs simulate the operation of treatment plants in near real time and provide a powerful tool to the operators and process engineers for real-time scenario analysis and calamity mitigation, online process optimization, predictive maintenance, model-based control, and so forth. So far, only a few mature examples of full-scale DT implementations can be found in the literature, which only address some of the key requirements of a DT. This paper presents the development of a full-scale operational DT for the Eindhoven water resource recovery facility in The Netherlands, which includes a fully automated data-pipeline combined with a detailed mechanistic full-plant process model and a user interface co-created with the plant's operators. The automated data preprocessing pipeline provides continuous access to validated data, an influent generator provides dynamic predictions of influent composition data and allows forecasting 48 h into the future, and an advanced compartmental model of the aeration and anoxic bioreactors ensures high predictive power. The DT runs near real-time simulations every 2 h. Visualization and interaction with the DT is facilitated by the cloud-based TwinPlant technology, which was developed in close interaction with the plant's operators. A set of predefined handles are made available, allowing users to simulate hypothetical scenarios such as process and equipment failures and changes in controller settings. The combination of the advanced data pipeline and process model development used in the Eindhoven DT and the active involvement of the operators/process engineers/managers in the development process makes the twin a valuable asset for decision making with long-term reliability. PRACTITIONER POINTS: A full-scale digital twin (DT) has been developed for the Eindhoven WRRF. The Eindhoven DT includes an automated continuous data preprocessing and reconciliation pipeline. A full-plant mechanistic compartmental process model of the plant has been developed based on hydrodynamic studies. The interactive user interface of the Eindhoven DT allows operators to perform what-if scenarios on various operational settings and process inputs. Plant operators were actively involved in the DT development process to make a reliable and relevant tool with the expected added value.Β© 2024 Water Environment Federation.
publications-4727 article 2024 EscribΓ -Gelonch, M and Liang, S and Van, P Schalkwyk and Fisk, I and Long, NVD and Hessel, V Digital Twins in Agriculture: Orchestration and Applications. Journal of agricultural and food chemistry 10.1021/acs.jafc.4c01934 Digital Twins have emerged as an outstanding opportunity for precision farming, digitally replicating in real-time the functionalities of objects and plants. A virtual replica of the crop, including key agronomic development aspects such as irrigation, optimal fertilization strategies, and pest management, can support decision-making and a step change in farm management, increasing overall sustainability and direct water, fertilizer, and pesticide savings. In this review, Digital Twin technology is critically reviewed and framed in the context of recent advances in precision agriculture and Agriculture 4.0. The review is organized for each step of agricultural lifecycle, edaphic, phytotechnologic, postharvest, and farm infrastructure, with supporting case studies demonstrating direct benefits for agriculture production and supply chain considering both benefits and limitations of such an approach. Challenges and limitations are disclosed regarding the complexity of managing such an amount of data and a multitude of (often) simultaneous operations and supports.
publications-4728 article 2024 Aliya·Abulimiti and Wang, PY and Wang, XH [N(2)O Emission Factors from Wastewater Treatment Plants Based on Literature Statistics and Model Fitting]. Huan jing ke xue= Huanjing kexue 10.13227/j.hjkx.202307028 The emission of nitrous oxide （N2O） during wastewater treatment cannot be ignored. The analysis of statistical data from literature based on 126 empirical studies revealed that the geographical factors of wastewater treatment plants （WWTPs） had a significant impact on N2O emission factors. However, the N2O emission factors of WWTPs in all regions of the world were generally lower than the Intergovernmental Panel on Climate Change （IPCC） recommended values. In China, the N2O emission factors （in N2O-N/Ninfluent） of WWTPs were approximately 0.000 35-0.065 20 kg·kg-1. Meanwhile, the N2O emission factors of different wastewater treatment processes were also significantly different, especially since the sequencing batch reactor （SBR） process had higher emissions. The use of uniform default emission factors for accounting was prone to overestimate N2O emissions, and it is recommended that countries conduct actual monitoring or modeling studies to develop categorical emission factors suitable for local conditions. In addition, the N2O emission factor based on total nitrogen （TN） removal was weakly negatively correlated with TN removal in 126 empirical data, which was more in line with bioprocessing stoichiometry and could provide an accurate accounting method for N2O. To this end, a digital twin model was developed to dynamically simulate a case anaerobic-anoxic-aerobic （AAO） WWTP to comprehensively quantify the dynamic emission behavior of N2O, which demonstrated that N2O emissions had significant seasonal and daily variability and were only equivalent to 11\% of the calculated value of the emission factor based on the IPCC recommendation. Comparing the scatter linear fitting and categorical mean exponential fitting methods, it was found that the latter could more accurately reflect the negative correlation between the N2O emission factors and the TN removal rate, and an exponential regression equation between the average N2O emission factor based on the amount of TN removed and the TN removal rate was further developed to predict the N2O emission. The dynamic simulation and categorical index fitting methods provided in this study are important references for the accurate accounting of N2O emissions in similar WWTPs and provide help for understanding and responding to the N2O emission problems.
publications-4729 article 2024 RodrΓ­guez-Alonso, C and Pena-Regueiro, I and GarcΓ­a, Γ“ Digital Twin Platform for Water Treatment Plants Using Microservices Architecture. Sensors (Basel, Switzerland) 10.3390/s24051568 The effects of climate change and the rapid growth of societies often lead to water scarcity and inadequate water quality, resulting in a significant number of diseases. The digitalization of infrastructure and the use of Digital Twins are presented as alternatives for optimizing resources and the necessary infrastructure in the water cycle. This paper presents a framework for the development of a Digital Twin platform for a wastewater treatment plant, based on a microservices architecture which optimized its design for edge computing implementation. The platform aims to optimize the operation and maintenance processes of the plant's systems, by employing machine learning techniques, process modeling and simulation, as well as leveraging the information contained in BIM models to support decision-making.
publications-4730 article 2022 Torfs, Elena and Torfs, Elena and NicolaΓ―, Niels and NicolaΓ―, Niels and Daneshgar, Saba and Daneshgar, Saba and Copp, John B. and Copp, John B. and Haimi, Henri and Haimi, Henri and Ikumi, David and Ikumi, David and Johnson, Bruce and Johnson, Bruce R. and Plosz, Benedek B. and PlΓ³sz, Benedek G. and Snowling, Spencer and Snowling, Spencer and Townley, Lloyd R. and Townley, Lloyd R. and Valverde-PΓ©rez, Borja and Valverde-PΓ©rez, Borja and Vanrolleghem, Peter A. and Vanrolleghem, Peter and Vezzaro, Luca and Vezzaro, Luca and Nopens, Ingmar and Nopens, Ingmar The transition of WRRF models to digital twin applications Water Science and Technology 10.2166/wst.2022.107 Abstract Digital Twins (DTs) are on the rise as innovative, powerful technologies to harness the power of digitalisation in the WRRF sector. The lack of consensus and understanding when it comes to the definition, perceived benefits and technological needs of DTs is hampering their widespread development and application. Transitioning from traditional WRRF modelling practice into DT applications raises a number of important questions: When is a model's predictive power acceptable for a DT? Which modelling frameworks are most suited for DT applications? Which data structures are needed to efficiently feed data to a DT? How do we keep the DT up to date and relevant? Who will be the main users of DTs and how to get them involved? How do DTs push the water sector to evolve? This paper provides an overview of the state-of-the-art, challenges, good practices, development needs and transformative capacity of DTs for WRRF applications.